WorldWideScience

Sample records for machine readable features

  1. Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning.

    Science.gov (United States)

    Sung, Yao-Ting; Chen, Ju-Ling; Cha, Ji-Her; Tseng, Hou-Chiang; Chang, Tao-Hsing; Chang, Kuo-En

    2015-06-01

    Multilevel linguistic features have been proposed for discourse analysis, but there have been few applications of multilevel linguistic features to readability models and also few validations of such models. Most traditional readability formulae are based on generalized linear models (GLMs; e.g., discriminant analysis and multiple regression), but these models have to comply with certain statistical assumptions about data properties and include all of the data in formulae construction without pruning the outliers in advance. The use of such readability formulae tends to produce a low text classification accuracy, while using a support vector machine (SVM) in machine learning can enhance the classification outcome. The present study constructed readability models by integrating multilevel linguistic features with SVM, which is more appropriate for text classification. Taking the Chinese language as an example, this study developed 31 linguistic features as the predicting variables at the word, semantic, syntax, and cohesion levels, with grade levels of texts as the criterion variable. The study compared four types of readability models by integrating unilevel and multilevel linguistic features with GLMs and an SVM. The results indicate that adopting a multilevel approach in readability analysis provides a better representation of the complexities of both texts and the reading comprehension process.

  2. A Machine Learning Approach to Measurement of Text Readability for EFL Learners Using Various Linguistic Features

    Science.gov (United States)

    Kotani, Katsunori; Yoshimi, Takehiko; Isahara, Hitoshi

    2011-01-01

    The present paper introduces and evaluates a readability measurement method designed for learners of EFL (English as a foreign language). The proposed readability measurement method (a regression model) estimates the text readability based on linguistic features, such as lexical, syntactic and discourse features. Text readability refers to the…

  3. Machine Readable Passports & The Visa Waiver Programme

    CERN Multimedia

    2003-01-01

    From 1 October 2003, all passengers intending to enter the USA on the Visa Waiver Programme (VWP) will be required to present a machine-readable passport (MRP). Passengers travelling to the USA with a non-machine readable passport will require a valid US entry visa. Applying for a US visa is a lengthy process, which can take several weeks or even months. Therefore it is strongly recommended that: • All Visa Waiver nationals who hold a non-machine readable passport should obtain a MRP before their next visit to the USA. • Children travelling on a parent's passport (be it machine readable or non-machine readable) cannot benefit from the Visa Waiver Programme and should obtain their own MRP prior to travelling to the USA or request a visa. What is a Machine Readable Passport (MRP)? A MRP has the holders' personal details, e.g. name, date of birth, nationality and their passport number contained in two lines of text at the base of the photo page. This text may be read by machine. These 2 lines ...

  4. A survey of machine readable data bases

    Science.gov (United States)

    Matlock, P.

    1981-01-01

    Forty-two of the machine readable data bases available to the technologist and researcher in the natural sciences and engineering are described and compared with the data bases and date base services offered by NASA.

  5. Combined machine-readable and visually authenticated optical devices

    Science.gov (United States)

    Souparis, Hugues

    1996-03-01

    Optical variable devices are now widely used on documents or values. The most recent optical visual features with high definition, animation, brightness, special color tune, provide excellent first and second levels of authentication. Human eye is the only instrument required to check the authenticity. This is a major advantage of OVDs in many circumstances, such as currency exchange, ID street control . . . But, under other circumstances, such as automatic payments with banknotes, volume ID controls at boarders, ID controls in shops . . . an automatic authentication will be necessary or more reliable. When both a visual and automated authentication are required, the combination, on the same security component, of a variable image and a machine readable optical element is a very secure and cost effective solution for the protection of documents. Several techniques are now available an can be selected depending upon the respective roles of the machine readability and visual control.

  6. 6 CFR 37.19 - Machine readable technology on the driver's license or identification card.

    Science.gov (United States)

    2010-01-01

    ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Machine readable technology on the driver's..., Verification, and Card Issuance Requirements § 37.19 Machine readable technology on the driver's license or identification card. For the machine readable portion of the REAL ID driver's license or identification card...

  7. The compiled catalogue of galaxies in machine-readable form and its statistical investigation

    International Nuclear Information System (INIS)

    Kogoshvili, N.G.

    1982-01-01

    The compilation of a machine-readable catalogue of relatively bright galaxies was undertaken in Abastumani Astrophysical Observatory in order to facilitate the statistical analysis of a large observational material on galaxies from the Palomar Sky Survey. In compiling the catalogue of galaxies the following problems were considered: the collection of existing information for each galaxy; a critical approach to data aimed at the selection of the most important features of the galaxies; the recording of data in computer-readable form; and the permanent updating of the catalogue. (Auth.)

  8. USA - Postponement of Deadline for Machine-Readable Passports

    CERN Multimedia

    2003-01-01

    U.S. Secretary of State Colin Powell has granted a postponement until October 26, 2004, as the date by which travellers holding Swiss passports must present a machine-readable passport at a U.S. port of entry to be admitted to the country without a visa. As in the past, citizens of Switzerland and other visa waiver program countries are permitted to enter the United States for general business or tourist purposes for a maximum of 90 days without needing a visa. Other categories of travellers such as students, journalists, individuals employed in the U.S., and all individuals staying for more than 90 days still require a visa. The postponement granted by the Secretary of State applies to a total to the following countries: Australia - Austria - Denmark - Finland - France - Germany - Iceland - Ireland - Italy - Japan - Monaco - Netherlands - New Zealand - Norway - Portugal - San Marino - Singapore - Spain - Sweden - Switzerland - United Kingdom More information available: http://www.us-embassy.ch Your Carlson...

  9. A new TLD badge with machine readable ID for fully automated readout

    International Nuclear Information System (INIS)

    Kannan, S. Ratna P.; Kulkarni, M.S.

    2003-01-01

    The TLD badge currently being used for personnel monitoring of more than 40,000 radiation workers has a few drawbacks such as lack of on-badge machine readable ID code, delicate two-point clamping of dosimeters on an aluminium card with the chances of dosimeters falling off during handling or readout, projections on one side making automation of readout difficult etc. A new badge has been designed with a 8-digit identification code in the form of an array of holes and smooth exteriors to enable full automation of readout. The new badge also permits changing of dosimeters when necessary. The new design does not affect the readout time or the dosimetric characteristics. The salient features and the dosimetric characteristics are discussed. (author)

  10. Use of a New Set of Linguistic Features to Improve Automatic Assessment of Text Readability

    Science.gov (United States)

    Yoshimi, Takehiko; Kotani, Katsunori; Isahara, Hitoshi

    2012-01-01

    The present paper proposes and evaluates a readability assessment method designed for Japanese learners of EFL (English as a foreign language). The proposed readability assessment method is constructed by a regression algorithm using a new set of linguistic features that were employed separately in previous studies. The results showed that the…

  11. Migrant Student Record Transfer System (MSRTS) [machine-readable data file].

    Science.gov (United States)

    Arkansas State Dept. of Education, Little Rock. General Education Div.

    The Migrant Student Record Transfer System (MSRTS) machine-readable data file (MRDF) is a collection of education and health data on more than 750,000 migrant children in grades K-12 in the United States (except Hawaii), the District of Columbia, and the outlying territories of Puerto Rico and the Mariana and Marshall Islands. The active file…

  12. Evaluation of the Mechanical Durability of the Egyptian Machine Readable Booklet Passport

    Directory of Open Access Journals (Sweden)

    Ahmed Mahmoud Yosri

    2013-12-01

    Full Text Available In 2008 the first Egyptian booklet Machine Readable Passport/ MRP has been issued and its security and informative standard quality levels were proved in a research published in 2011. Here the durability profiles of the Egyptian MRP have been evaluated. Seven mechanical durability tests were applied on the Egyptian MRP. Such tests are specified in the International Civil Aviation Organization / ICAO standard requirements documents. These seven very severe durability tests resulted in that the Egyptian MRP has achieved better & higher results than the values detected in ICAO-Doc N0232: Durability of Machine Readable Passports - Version: 3.2. Hence, this research had proved the complete conformance between the Egyptian MRP mechanical durability profiles to the international requirements. The Egyptian booklet MRP doesn’t need any obligatory modification concerning its mechanical durability profiles.

  13. Toolsets for Airborne Data (TAD): Improving Machine Readability for ICARTT Data Files

    Science.gov (United States)

    Northup, E. A.; Early, A. B.; Beach, A. L., III; Kusterer, J.; Quam, B.; Wang, D.; Chen, G.

    2015-12-01

    NASA has conducted airborne tropospheric chemistry studies for about three decades. These field campaigns have generated a great wealth of observations, including a wide range of the trace gases and aerosol properties. The ASDC Toolsets for Airborne Data (TAD) is designed to meet the user community needs for manipulating aircraft data for scientific research on climate change and air quality relevant issues. TAD makes use of aircraft data stored in the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) file format. ICARTT has been the NASA standard since 2010, and is widely used by NOAA, NSF, and international partners (DLR, FAAM). Its level of acceptance is due in part to it being generally self-describing for researchers, i.e., it provides necessary data descriptions for proper research use. Despite this, there are a number of issues with the current ICARTT format, especially concerning the machine readability. In order to overcome these issues, the TAD team has developed an "idealized" file format. This format is ASCII and is sufficiently machine readable to sustain the TAD system, however, it is not fully compatible with the current ICARTT format. The process of mapping ICARTT metadata to the idealized format, the format specifics, and the actual conversion process will be discussed. The goal of this presentation is to demonstrate an example of how to improve the machine readability of ASCII data format protocols.

  14. Comparative Costs of Converting Shelf List Records to Machine Readable Form

    Directory of Open Access Journals (Sweden)

    Richard E. Chapin

    1968-03-01

    Full Text Available A study at Michigan State University Library compared the costs of three different methods of conversion: keypunching, paper-tape typewriting, and optical scanning by a service bureau. The record converted included call number, copy number, first 39 letters of the author's name, first 43 letters of the title, and date of publication. Source documents were all of the shelf list cards at the Library. The end products were a master book tape of the library collections and a machine readable book card for each volume to be used in an automated circulation system.

  15. The Machine / Job Features Mechanism

    Energy Technology Data Exchange (ETDEWEB)

    Alef, M. [KIT, Karlsruhe; Cass, T. [CERN; Keijser, J. J. [NIKHEF, Amsterdam; McNab, A. [Manchester U.; Roiser, S. [CERN; Schwickerath, U. [CERN; Sfiligoi, I. [Fermilab

    2017-11-22

    Within the HEPiX virtualization group and the Worldwide LHC Computing Grid’s Machine/Job Features Task Force, a mechanism has been developed which provides access to detailed information about the current host and the current job to the job itself. This allows user payloads to access meta information, independent of the current batch system or virtual machine model. The information can be accessed either locally via the filesystem on a worker node, or remotely via HTTP(S) from a webserver. This paper describes the final version of the specification from 2016 which was published as an HEP Software Foundation technical note, and the design of the implementations of this version for batch and virtual machine platforms. We discuss early experiences with these implementations and how they can be exploited by experiment frameworks.

  16. Documentation for the machine-readable version of the Morphological Catalogue of Galaxies (MCG) of Vorontsov-Velyaminov et al, 1962-1968

    Science.gov (United States)

    Warren, W. H., Jr.

    1982-01-01

    Modifications, corrections, and the record format are provided for the machine-readable version of the "Morphological Catalogue of Galaxies.' In addition to hundreds of individual corrections, a detailed comparison of the machine-readable with the published catalogue resulted in the addition of 116 missing objects, the deletion of 10 duplicate records, and a format modification to increase storage efficiency.

  17. Student Achievement Study, 1970-1974. The IEA Six-Subject Data Bank [machine-readable data file].

    Science.gov (United States)

    International Association for the Evaluation of Educational Achievement, Stockholm (Sweden).

    The "Student Achievement Study" machine-readable data files (MRDF) (also referred to as the "IEA Six-Subject Survey") are the result of an international data collection effort during 1970-1974 by 21 designated National Centers, which had agreed to cooperate. The countries involved were: Australia, Belgium, Chile, England-Wales,…

  18. A Study of Readability of Texts in Bangla through Machine Learning Approaches

    Science.gov (United States)

    Sinha, Manjira; Basu, Anupam

    2016-01-01

    In this work, we have investigated text readability in Bangla language. Text readability is an indicator of the suitability of a given document with respect to a target reader group. Therefore, text readability has huge impact on educational content preparation. The advances in the field of natural language processing have enabled the automatic…

  19. Machine parameters and characteristic features

    International Nuclear Information System (INIS)

    Le Duff, J.

    1979-01-01

    The design and operating characteristics of LEP are presented. Its probable performance, possible improvements and cost are discussed and some comparisons are drawn with machines currently in operation. (W.D.L.)

  20. Elementary epistemological features of machine intelligence

    OpenAIRE

    Horvat, Marko

    2008-01-01

    Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of in...

  1. A Modular Framework for Transforming Structured Data into HTML with Machine-Readable Annotations

    Science.gov (United States)

    Patton, E. W.; West, P.; Rozell, E.; Zheng, J.

    2010-12-01

    There is a plethora of web-based Content Management Systems (CMS) available for maintaining projects and data, i.a. However, each system varies in its capabilities and often content is stored separately and accessed via non-uniform web interfaces. Moving from one CMS to another (e.g., MediaWiki to Drupal) can be cumbersome, especially if a large quantity of data must be adapted to the new system. To standardize the creation, display, management, and sharing of project information, we have assembled a framework that uses existing web technologies to transform data provided by any service that supports the SPARQL Protocol and RDF Query Language (SPARQL) queries into HTML fragments, allowing it to be embedded in any existing website. The framework utilizes a two-tier XML Stylesheet Transformation (XSLT) that uses existing ontologies (e.g., Friend-of-a-Friend, Dublin Core) to interpret query results and render them as HTML documents. These ontologies can be used in conjunction with custom ontologies suited to individual needs (e.g., domain-specific ontologies for describing data records). Furthermore, this transformation process encodes machine-readable annotations, namely, the Resource Description Framework in attributes (RDFa), into the resulting HTML, so that capable parsers and search engines can extract the relationships between entities (e.g, people, organizations, datasets). To facilitate editing of content, the framework provides a web-based form system, mapping each query to a dynamically generated form that can be used to modify and create entities, while keeping the native data store up-to-date. This open framework makes it easy to duplicate data across many different sites, allowing researchers to distribute their data in many different online forums. In this presentation we will outline the structure of queries and the stylesheets used to transform them, followed by a brief walkthrough that follows the data from storage to human- and machine-accessible web

  2. The machine/job features mechanism

    Science.gov (United States)

    Alef, M.; Cass, T.; Keijser, J. J.; McNab, A.; Roiser, S.; Schwickerath, U.; Sfiligoi, I.

    2017-10-01

    Within the HEPiX virtualization group and the Worldwide LHC Computing Grid’s Machine/Job Features Task Force, a mechanism has been developed which provides access to detailed information about the current host and the current job to the job itself. This allows user payloads to access meta information, independent of the current batch system or virtual machine model. The information can be accessed either locally via the filesystem on a worker node, or remotely via HTTP(S) from a webserver. This paper describes the final version of the specification from 2016 which was published as an HEP Software Foundation technical note, and the design of the implementations of this version for batch and virtual machine platforms. We discuss early experiences with these implementations and how they can be exploited by experiment frameworks.

  3. Machine learning spatial geometry from entanglement features

    Science.gov (United States)

    You, Yi-Zhuang; Yang, Zhao; Qi, Xiao-Liang

    2018-02-01

    Motivated by the close relations of the renormalization group with both the holography duality and the deep learning, we propose that the holographic geometry can emerge from deep learning the entanglement feature of a quantum many-body state. We develop a concrete algorithm, call the entanglement feature learning (EFL), based on the random tensor network (RTN) model for the tensor network holography. We show that each RTN can be mapped to a Boltzmann machine, trained by the entanglement entropies over all subregions of a given quantum many-body state. The goal is to construct the optimal RTN that best reproduce the entanglement feature. The RTN geometry can then be interpreted as the emergent holographic geometry. We demonstrate the EFL algorithm on a 1D free fermion system and observe the emergence of the hyperbolic geometry (AdS3 spatial geometry) as we tune the fermion system towards the gapless critical point (CFT2 point).

  4. Realistic Free-Spins Features Increase Preference for Slot Machines.

    Science.gov (United States)

    Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

    2017-06-01

    Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

  5. A possible extension to the RInChI as a means of providing machine readable process data.

    Science.gov (United States)

    Jacob, Philipp-Maximilian; Lan, Tian; Goodman, Jonathan M; Lapkin, Alexei A

    2017-04-11

    The algorithmic, large-scale use and analysis of reaction databases such as Reaxys is currently hindered by the absence of widely adopted standards for publishing reaction data in machine readable formats. Crucial data such as yields of all products or stoichiometry are frequently not explicitly stated in the published papers and, hence, not reported in the database entry for those reactions, limiting their usefulness for algorithmic analysis. This paper presents a possible extension to the IUPAC RInChI standard via an auxiliary layer, termed ProcAuxInfo, which is a standardised, extensible form in which to report certain key reaction parameters such as declaration of all products and reactants as well as auxiliaries known in the reaction, reaction stoichiometry, amounts of substances used, conversion, yield and operating conditions. The standard is demonstrated via creation of the RInChI including the ProcAuxInfo layer based on three published reactions and demonstrates accurate data recoverability via reverse translation of the created strings. Implementation of this or another method of reporting process data by the publishing community would ensure that databases, such as Reaxys, would be able to abstract crucial data for big data analysis of their contents.

  6. Clozing in on readability : How linguistic features affect and predict text comprehension and on-line processing

    NARCIS (Netherlands)

    Kleijn, S.

    2018-01-01

    Is my text comprehensible for my audience? It is a question publishers, organizations and governments struggle with and it is a question that readability formulae proclaim to solve. With a press of a button the readability of a text is assessed and users know whether texts are suited for their

  7. Fifth Fundamental Catalogue (FK5). Part 1: Basic fundamental stars (Fricke, Schwan, and Lederle 1988): Documentation for the machine-readable version

    Science.gov (United States)

    Warren, Wayne H., Jr.

    1990-01-01

    The machine-readable version of the catalog, as it is currently being distributed from the Astronomical Data Center, is described. The Basic FK5 provides improved mean positions and proper motions for the 1535 classical fundamental stars that had been included in the FK3 and FK4 catalogs. The machine version of the catalog contains the positions and proper motions of the Basic FK5 stars for the epochs and equinoxes J2000.0 and B1950.0, the mean epochs of individual observed right ascensions and declinations used to determine the final positions, and the mean errors of the final positions and proper motions for the reported epochs. The cross identifications to other designations used for the FK5 stars that are given in the published catalog were not included in the original machine versions, but the Durchmusterung numbers have been added at the Astronomical Data Center.

  8. Machine-readable files developed for the High Plains Regional Aquifer-System analysis in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming

    Science.gov (United States)

    Ferrigno, C.F.

    1986-01-01

    Machine-readable files were developed for the High Plains Regional Aquifer-System Analysis project are stored on two magnetic tapes available from the U.S. Geological Survey. The first tape contains computer programs that were used to prepare, store, retrieve, organize, and preserve the areal interpretive data collected by the project staff. The second tape contains 134 data files that can be divided into five general classes: (1) Aquifer geometry data, (2) aquifer and water characteristics , (3) water levels, (4) climatological data, and (5) land use and water use data. (Author 's abstract)

  9. Assessing the Readability of Medical Documents: A Ranking Approach.

    Science.gov (United States)

    Zheng, Jiaping; Yu, Hong

    2018-03-23

    The use of electronic health record (EHR) systems with patient engagement capabilities, including viewing, downloading, and transmitting health information, has recently grown tremendously. However, using these resources to engage patients in managing their own health remains challenging due to the complex and technical nature of the EHR narratives. Our objective was to develop a machine learning-based system to assess readability levels of complex documents such as EHR notes. We collected difficulty ratings of EHR notes and Wikipedia articles using crowdsourcing from 90 readers. We built a supervised model to assess readability based on relative orders of text difficulty using both surface text features and word embeddings. We evaluated system performance using the Kendall coefficient of concordance against human ratings. Our system achieved significantly higher concordance (.734) with human annotators than did a baseline using the Flesch-Kincaid Grade Level, a widely adopted readability formula (.531). The improvement was also consistent across different disease topics. This method's concordance with an individual human user's ratings was also higher than the concordance between different human annotators (.658). We explored methods to automatically assess the readability levels of clinical narratives. Our ranking-based system using simple textual features and easy-to-learn word embeddings outperformed a widely used readability formula. Our ranking-based method can predict relative difficulties of medical documents. It is not constrained to a predefined set of readability levels, a common design in many machine learning-based systems. Furthermore, the feature set does not rely on complex processing of the documents. One potential application of our readability ranking is personalization, allowing patients to better accommodate their own background knowledge. ©Jiaping Zheng, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.03.2018.

  10. Deep Restricted Kernel Machines Using Conjugate Feature Duality.

    Science.gov (United States)

    Suykens, Johan A K

    2017-08-01

    The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

  11. Critical feature analysis of a radiotherapy machine

    International Nuclear Information System (INIS)

    Rae, Andrew; Jackson, Daniel; Ramanan, Prasad; Flanz, Jay; Leyman, Didier

    2005-01-01

    The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An 'assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code

  12. Blue gum gaming machine: an evaluation of responsible gambling features.

    Science.gov (United States)

    Blaszczynski, Alexander; Gainsbury, Sally; Karlov, Lisa

    2014-09-01

    Structural characteristics of gaming machines contribute to persistence in play and excessive losses. The purpose of this study was to evaluate the effectiveness of five proposed responsible gaming features: responsible gaming messages; a bank meter quarantining winnings until termination of play; alarm clock facilitating setting time-reminders; demo mode allowing play without money; and a charity donation feature where residual amounts can be donated rather than played to zero credits. A series of ten modified gaming machines were located in five Australian gambling venues. The sample comprised 300 patrons attending the venue and who played the gaming machines. Participants completed a structured interview eliciting gambling and socio-demographic data and information on their perceptions and experience of play on the index machines. Results showed that one-quarter of participants considered that these features would contribute to preventing recreational gamblers from developing problems. Just under half of the participants rated these effects to be at least moderate or significant. The promising results suggest that further refinements to several of these features could represent a modest but effective approach to minimising excessive gambling on gaming machines.

  13. Improving readability through extractive summarization for learners with reading difficulties

    Directory of Open Access Journals (Sweden)

    K. Nandhini

    2013-11-01

    Full Text Available In this paper, we describe the design and evaluation of extractive summarization approach to assist the learners with reading difficulties. As existing summarization approaches inherently assign more weights to the important sentences, our approach predicts the summary sentences that are important as well as readable to the target audience with good accuracy. We used supervised machine learning technique for summary extraction of science and social subjects in the educational text. Various independent features from the existing literature for predicting important sentences and proposed learner dependent features for predicting readable sentences are extracted from texts and are used for automatic classification. We performed both extrinsic and intrinsic evaluation on this approach and the intrinsic evaluation is carried out using F-measure and readability analysis. The extrinsic evaluation comprises of learner feedback using likert scale and the effect of assistive summary on improving readability for learners’ with reading difficulty using ANOVA. The results show significant improvement in readability for the target audience using assistive summary.

  14. Simplifying the Reuse and Interoperability of Geoscience Data Sets and Models with Semantic Metadata that is Human-Readable and Machine-actionable

    Science.gov (United States)

    Peckham, S. D.

    2017-12-01

    Standardized, deep descriptions of digital resources (e.g. data sets, computational models, software tools and publications) make it possible to develop user-friendly software systems that assist scientists with the discovery and appropriate use of these resources. Semantic metadata makes it possible for machines to take actions on behalf of humans, such as automatically identifying the resources needed to solve a given problem, retrieving them and then automatically connecting them (despite their heterogeneity) into a functioning workflow. Standardized model metadata also helps model users to understand the important details that underpin computational models and to compare the capabilities of different models. These details include simplifying assumptions on the physics, governing equations and the numerical methods used to solve them, discretization of space (the grid) and time (the time-stepping scheme), state variables (input or output), model configuration parameters. This kind of metadata provides a "deep description" of a computational model that goes well beyond other types of metadata (e.g. author, purpose, scientific domain, programming language, digital rights, provenance, execution) and captures the science that underpins a model. A carefully constructed, unambiguous and rules-based schema to address this problem, called the Geoscience Standard Names ontology will be presented that utilizes Semantic Web best practices and technologies. It has also been designed to work across science domains and to be readable by both humans and machines.

  15. Readability versus Leveling.

    Science.gov (United States)

    Fry, Edward

    2002-01-01

    Shows some similarities and differences between readability formulas and leveling procedures and reports some current large-scale uses of readability formulas. Presents a dictionary definition of readability and leveling, and a history and background of readability and leveling. Discusses what goes into determining readability and leveling scores.…

  16. Simultaneous feature selection and classification via Minimax Probability Machine

    Directory of Open Access Journals (Sweden)

    Liming Yang

    2010-12-01

    Full Text Available This paper presents a novel method for simultaneous feature selection and classification by incorporating a robust L1-norm into the objective function of Minimax Probability Machine (MPM. A fractional programming framework is derived by using a bound on the misclassification error involving the mean and covariance of the data. Furthermore, the problems are solved by the Quadratic Interpolation method. Experiments show that our methods can select fewer features to improve the generalization compared to MPM, which illustrates the effectiveness of the proposed algorithms.

  17. Fault diagnosis of rotating machine by isometric feature mapping

    International Nuclear Information System (INIS)

    Zhang, Yun; Li, Benwei; Wang, Lin; Wang, Wen; Wang, Zibin

    2013-01-01

    Principal component analysis (PCA) and linear discriminate analysis (LDA) are well-known linear dimensionality reductions for fault classification. However, since they are linear methods, they perform not well for high-dimensional data that has the nonlinear geometric structure. As kernel extension of PCA, Kernel PCA is used for nonlinear fault classification. However, the performance of Kernel PCA largely depends on its kernel function which can only be empirically selected from finite candidates. Thus, a novel rotating machine fault diagnosis approach based on geometrically motivated nonlinear dimensionality reduction named isometric feature mapping (Isomap) is proposed. The approach can effectively extract the intrinsic nonlinear manifold features embedded in high-dimensional fault data sets. Experimental results with rotor and rolling bearing data show that the proposed approach overcomes the flaw of conventional fault pattern recognition approaches and obviously improves the fault classification performance.

  18. Feature Import Vector Machine: A General Classifier with Flexible Feature Selection.

    Science.gov (United States)

    Ghosh, Samiran; Wang, Yazhen

    2015-02-01

    The support vector machine (SVM) and other reproducing kernel Hilbert space (RKHS) based classifier systems are drawing much attention recently due to its robustness and generalization capability. General theme here is to construct classifiers based on the training data in a high dimensional space by using all available dimensions. The SVM achieves huge data compression by selecting only few observations which lie close to the boundary of the classifier function. However when the number of observations are not very large (small n ) but the number of dimensions/features are large (large p ), then it is not necessary that all available features are of equal importance in the classification context. Possible selection of an useful fraction of the available features may result in huge data compression. In this paper we propose an algorithmic approach by means of which such an optimal set of features could be selected. In short, we reverse the traditional sequential observation selection strategy of SVM to that of sequential feature selection. To achieve this we have modified the solution proposed by Zhu and Hastie (2005) in the context of import vector machine (IVM), to select an optimal sub-dimensional model to build the final classifier with sufficient accuracy.

  19. The Principles of Readability

    Science.gov (United States)

    DuBay, William H.

    2004-01-01

    The principles of readability are in every style manual. Readability formulas are in every writing aid. What is missing is the research and theory on which they stand. This short review of readability research spans 100 years. The first part covers the history of adult literacy studies in the U.S., establishing the stratified nature of the adult…

  20. Novel Automatic Filter-Class Feature Selection for Machine Learning Regression

    DEFF Research Database (Denmark)

    Wollsen, Morten Gill; Hallam, John; Jørgensen, Bo Nørregaard

    2017-01-01

    With the increased focus on application of Big Data in all sectors of society, the performance of machine learning becomes essential. Efficient machine learning depends on efficient feature selection algorithms. Filter feature selection algorithms are model-free and therefore very fast, but require...... model in the feature selection process. PCA is often used in machine learning litterature and can be considered the default feature selection method. RDESF outperformed PCA in both experiments in both prediction error and computational speed. RDESF is a new step into filter-based automatic feature...

  1. Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

    NARCIS (Netherlands)

    Malta, Tathiane M.; Sokolov, Artem; Gentles, Andrew J.; Burzykowski, Tomasz; Poisson, Laila; Weinstein, John N.; Kamińska, Bożena; Huelsken, Joerg; Omberg, Larsson; Gevaert, Olivier; Colaprico, Antonio; Czerwińska, Patrycja; Mazurek, Sylwia; Mishra, Lopa; Heyn, Holger; Krasnitz, Alex; Godwin, Andrew K.; Lazar, Alexander J.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Gonzalez, Ana Maria Angulo; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Stuart, Joshua M.; Hoadley, Katherine A.; Laird, Peter W.; Noushmehr, Houtan; Wiznerowicz, Maciej

    2018-01-01

    Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR)

  2. A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature

    OpenAIRE

    Keong Chen Wong; Yusof Yusri

    2017-01-01

    This paper presents an algorithm for efficiently recognizing and determining the convexity of an edge blend feature. The algorithm first recognizes all of the edge blend features from the Boundary Representation of a part; then a series of convexity test have been run on the recognized edge blend features. The novelty of the presented algorithm lies in, instead of each recognized blend feature is suppressed as most of researchers did, the recognized blend features of this research are gone th...

  3. Accuracy of locating circular features using machine vision

    Science.gov (United States)

    Sklair, Cheryl W.; Hoff, William A.; Gatrell, Lance B.

    1992-03-01

    The ability to automatically locate objects using vision is a key technology for flexible, intelligent robotic operations. The vision task is facilitated by placing optical targets or markings in advance on the objects to be located. A number of researchers have advocated the use of circular target features as the features that can be most accurately located. This paper describes extensive analysis on circle centroid accuracy using both simulations and laboratory measurements. The work was part of an effort to design a video positioning sensor for NASA's Flight Telerobotic Servicer that would meet accuracy requirements. We have analyzed the main contributors to centroid error and have classified them into the following: (1) spatial quantization errors, (2) errors due to signal noise and random timing errors, (3) surface tilt errors, and (4) errors in modeling camera geometry. It is possible to compensate for the errors in (3) given an estimate of the tilt angle, and the errors from (4) by calibrating the intrinsic camera attributes. The errors in (1) and (2) cannot be compensated for, but they can be measured and their effects reduced somewhat. To characterize these error sources, we measured centroid repeatability under various conditions, including synchronization method, signal-to-noise ratio, and frequency attenuation. Although these results are specific to our video system and equipment, they provide a reference point that should be a characteristic of typical CCD cameras and digitization equipment.

  4. Methods to Measure Map Readability

    OpenAIRE

    Harrie, Lars

    2009-01-01

    Creation of maps in real-time web services introduces challenges concerning map readability. Therefore we must introduce analytical measures controlling the readability. The aim of this study is to develop and evaluate analytical readability measures with the help of user tests.

  5. Readability and Reading Ability.

    Science.gov (United States)

    Wright, Benjamin D.; Stenner, A. Jackson

    This document discusses the measurement of reading ability and the readability of books by application of the Lexile framework. It begins by stating the importance of uniform measures. It then discusses the history of reading ability testing, based on the assumption that no researcher has been able to measure more than one kind of reading ability.…

  6. Readability of Wikipedia

    NARCIS (Netherlands)

    Lucassen, T.; Dijkstra, Roald; Schraagen, Johannes Martinus Cornelis

    2012-01-01

    Wikipedia is becoming widely acknowledged as a reliable source of encyclopedic information. However, concerns have been expressed about its readability. Wikipedia articles might be written in a language too difficult to be understood by most of its visitors. In this study, we apply the Flesch

  7. A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

    Science.gov (United States)

    D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

    1993-01-01

    A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

  8. Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Jia Uddin

    2014-01-01

    Full Text Available This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D texture features and a multiclass support vector machine (MCSVM. The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture patterns (or repetitive patterns, and extracts these texture features by generating the dominant neighborhood structure (DNS map. The principal component analysis (PCA is then used for the purpose of dimensionality reduction of the high-dimensional feature vector including the extracted texture features due to the fact that the high-dimensional feature vector can degrade classification performance, and this paper configures an effective feature vector including discriminative fault features for diagnosis. Finally, the proposed approach utilizes the one-against-all (OAA multiclass support vector machines (MCSVMs to identify induction motor failures. In this study, the Gaussian radial basis function kernel cooperates with OAA MCSVMs to deal with nonlinear fault features. Experimental results demonstrate that the proposed approach outperforms three state-of-the-art fault diagnosis algorithms in terms of fault classification accuracy, yielding an average classification accuracy of 100% even in noisy environments.

  9. Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.

    Science.gov (United States)

    Ranjith, G; Parvathy, R; Vikas, V; Chandrasekharan, Kesavadas; Nair, Suresh

    2015-04-01

    With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine learning, a branch of artificial intelligence, is increasingly being used in medical image analysis applications such as image segmentation, registration and computer-aided diagnosis and detection. Histopathological analysis is currently the gold standard for classification of brain tumors. The use of machine learning algorithms along with extraction of relevant features from magnetic resonance imaging (MRI) holds promise of replacing conventional invasive methods of tumor classification. The aim of the study is to classify gliomas into benign and malignant types using MRI data. Retrospective data from 28 patients who were diagnosed with glioma were used for the analysis. WHO Grade II (low-grade astrocytoma) was classified as benign while Grade III (anaplastic astrocytoma) and Grade IV (glioblastoma multiforme) were classified as malignant. Features were extracted from MR spectroscopy. The classification was done using four machine learning algorithms: multilayer perceptrons, support vector machine, random forest and locally weighted learning. Three of the four machine learning algorithms gave an area under ROC curve in excess of 0.80. Random forest gave the best performance in terms of AUC (0.911) while sensitivity was best for locally weighted learning (86.1%). The performance of different machine learning algorithms in the classification of gliomas is promising. An even better performance may be expected by integrating features extracted from other MR sequences. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  10. Time-frequency feature analysis and recognition of fission neutrons signal based on support vector machine

    International Nuclear Information System (INIS)

    Jin Jing; Wei Biao; Feng Peng; Tang Yuelin; Zhou Mi

    2010-01-01

    Based on the interdependent relationship between fission neutrons ( 252 Cf) and fission chain ( 235 U system), the paper presents the time-frequency feature analysis and recognition in fission neutron signal based on support vector machine (SVM) through the analysis on signal characteristics and the measuring principle of the 252 Cf fission neutron signal. The time-frequency characteristics and energy features of the fission neutron signal are extracted by using wavelet decomposition and de-noising wavelet packet decomposition, and then applied to training and classification by means of support vector machine based on statistical learning theory. The results show that, it is effective to obtain features of nuclear signal via wavelet decomposition and de-noising wavelet packet decomposition, and the latter can reflect the internal characteristics of the fission neutron system better. With the training accomplished, the SVM classifier achieves an accuracy rate above 70%, overcoming the lack of training samples, and verifying the effectiveness of the algorithm. (authors)

  11. Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

    Science.gov (United States)

    Choi, Ickwon; Chung, Amy W; Suscovich, Todd J; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J; Francis, Donald; Robb, Merlin L; Michael, Nelson L; Kim, Jerome H; Alter, Galit; Ackerman, Margaret E; Bailey-Kellogg, Chris

    2015-04-01

    The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

  12. Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

    Directory of Open Access Journals (Sweden)

    Ickwon Choi

    2015-04-01

    Full Text Available The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release. We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

  13. Learning features for tissue classification with the classification restricted Boltzmann machine

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2014-01-01

    Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce the convo...... outperform conventional RBM-based feature learning, which is unsupervised and uses only a generative learning objective, as well as often-used filter banks. We show that a mixture of generative and discriminative learning can produce filters that give a higher classification accuracy....

  14. Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

    Science.gov (United States)

    Jegadeeshwaran, R.; Sugumaran, V.

    2015-02-01

    Hydraulic brakes in automobiles are important components for the safety of passengers; therefore, the brakes are a good subject for condition monitoring. The condition of the brake components can be monitored by using the vibration characteristics. On-line condition monitoring by using machine learning approach is proposed in this paper as a possible solution to such problems. The vibration signals for both good as well as faulty conditions of brakes were acquired from a hydraulic brake test setup with the help of a piezoelectric transducer and a data acquisition system. Descriptive statistical features were extracted from the acquired vibration signals and the feature selection was carried out using the C4.5 decision tree algorithm. There is no specific method to find the right number of features required for classification for a given problem. Hence an extensive study is needed to find the optimum number of features. The effect of the number of features was also studied, by using the decision tree as well as Support Vector Machines (SVM). The selected features were classified using the C-SVM and Nu-SVM with different kernel functions. The results are discussed and the conclusion of the study is presented.

  15. Application of higher order spectral features and support vector machines for bearing faults classification.

    Science.gov (United States)

    Saidi, Lotfi; Ben Ali, Jaouher; Fnaiech, Farhat

    2015-01-01

    Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals. Copyright © 2014 ISA

  16. Device-Free Localization via an Extreme Learning Machine with Parameterized Geometrical Feature Extraction

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    2017-04-01

    Full Text Available Device-free localization (DFL is becoming one of the new technologies in wireless localization field, due to its advantage that the target to be localized does not need to be attached to any electronic device. In the radio-frequency (RF DFL system, radio transmitters (RTs and radio receivers (RXs are used to sense the target collaboratively, and the location of the target can be estimated by fusing the changes of the received signal strength (RSS measurements associated with the wireless links. In this paper, we will propose an extreme learning machine (ELM approach for DFL, to improve the efficiency and the accuracy of the localization algorithm. Different from the conventional machine learning approaches for wireless localization, in which the above differential RSS measurements are trivially used as the only input features, we introduce the parameterized geometrical representation for an affected link, which consists of its geometrical intercepts and differential RSS measurement. Parameterized geometrical feature extraction (PGFE is performed for the affected links and the features are used as the inputs of ELM. The proposed PGFE-ELM for DFL is trained in the offline phase and performed for real-time localization in the online phase, where the estimated location of the target is obtained through the created ELM. PGFE-ELM has the advantages that the affected links used by ELM in the online phase can be different from those used for training in the offline phase, and can be more robust to deal with the uncertain combination of the detectable wireless links. Experimental results show that the proposed PGFE-ELM can improve the localization accuracy and learning speed significantly compared with a number of the existing machine learning and DFL approaches, including the weighted K-nearest neighbor (WKNN, support vector machine (SVM, back propagation neural network (BPNN, as well as the well-known radio tomographic imaging (RTI DFL approach.

  17. Identifying predictive features in drug response using machine learning: opportunities and challenges.

    Science.gov (United States)

    Vidyasagar, Mathukumalli

    2015-01-01

    This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

  18. Application of the Disruption Predictor Feature Developer to developing a machine-portable disruption predictor

    Science.gov (United States)

    Parsons, Matthew; Tang, William; Feibush, Eliot

    2016-10-01

    Plasma disruptions pose a major threat to the operation of tokamaks which confine a large amount of stored energy. In order to effectively mitigate this damage it is necessary to predict an oncoming disruption with sufficient warning time to take mitigative action. Machine learning approaches to this problem have shown promise but require further developments to address (1) the need for machine-portable predictors and (2) the availability of multi-dimensional signal inputs. Here we demonstrate progress in these two areas by applying the Disruption Predictor Feature Developer to data from JET and NSTX, and discuss topics of focus for ongoing work in support of ITER. The author is also supported under the Fulbright U.S. Student Program as a graduate student in the department of Nuclear, Plasma and Radiological Engineering at the University of Illinois at Urbana-Champaign.

  19. Pipeline leakage recognition based on the projection singular value features and support vector machine

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Wei; Zhang, Laibin; Mingda, Wang; Jinqiu, Hu [College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing, (China)

    2010-07-01

    The negative wave pressure method is one of the processes used to detect leaks on oil pipelines. The development of new leakage recognition processes is difficult because it is practically impossible to collect leakage pressure samples. The method of leakage feature extraction and the selection of the recognition model are also important in pipeline leakage detection. This study investigated a new feature extraction approach Singular Value Projection (SVP). It projects the singular value to a standard basis. A new pipeline recognition model based on the multi-class Support Vector Machines was also developed. It was found that SVP is a clear and concise recognition feature of the negative pressure wave. Field experiments proved that the model provided a high recognition accuracy rate. This approach to pipeline leakage detection based on the SVP and SVM has a high application value.

  20. Readability Approaches: Implications for Turkey

    Science.gov (United States)

    Ulusoy, Mustafa

    2006-01-01

    Finding the right fit between students' reading ability and textbooks is very important for comprehension. Readability studies aim to analyse texts to find the right fit between students and texts. In this literature review, readability studies are classified under quantitative, qualitative and combined quantitative-qualitative readability…

  1. About machine-readable travel documents

    Energy Technology Data Exchange (ETDEWEB)

    Vaudenay, S; Vuagnoux, M [EPFL, Lausanne (Switzerland)

    2007-07-15

    Passports are documents that help immigration officers to identify people. In order to strongly authenticate their data and to automatically identify people, they are now equipped with RFID chips. These contain private information, biometrics, and a digital signature by issuing authorities. Although they substantially increase security at the border controls, they also come with new security and privacy issues. In this paper, we survey existing protocols and their weaknesses.

  2. About machine-readable travel documents

    International Nuclear Information System (INIS)

    Vaudenay, S; Vuagnoux, M

    2007-01-01

    Passports are documents that help immigration officers to identify people. In order to strongly authenticate their data and to automatically identify people, they are now equipped with RFID chips. These contain private information, biometrics, and a digital signature by issuing authorities. Although they substantially increase security at the border controls, they also come with new security and privacy issues. In this paper, we survey existing protocols and their weaknesses

  3. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

    Science.gov (United States)

    Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

    2018-05-01

    Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

  4. BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

    KAUST Repository

    Kandaswamy, Krishna Kumar

    2011-08-17

    Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.

  5. Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Artificial Fish Swarm Algorithms

    Directory of Open Access Journals (Sweden)

    Kuan-Cheng Lin

    2015-01-01

    Full Text Available Rapid advances in information and communication technology have made ubiquitous computing and the Internet of Things popular and practicable. These applications create enormous volumes of data, which are available for analysis and classification as an aid to decision-making. Among the classification methods used to deal with big data, feature selection has proven particularly effective. One common approach involves searching through a subset of the features that are the most relevant to the topic or represent the most accurate description of the dataset. Unfortunately, searching through this kind of subset is a combinatorial problem that can be very time consuming. Meaheuristic algorithms are commonly used to facilitate the selection of features. The artificial fish swarm algorithm (AFSA employs the intelligence underlying fish swarming behavior as a means to overcome optimization of combinatorial problems. AFSA has proven highly successful in a diversity of applications; however, there remain shortcomings, such as the likelihood of falling into a local optimum and a lack of multiplicity. This study proposes a modified AFSA (MAFSA to improve feature selection and parameter optimization for support vector machine classifiers. Experiment results demonstrate the superiority of MAFSA in classification accuracy using subsets with fewer features for given UCI datasets, compared to the original FASA.

  6. BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

    KAUST Repository

    Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Hazrati, Mehrnaz Khodam; Kalies, Kai-Uwe; Martinetz, Thomas

    2011-01-01

    Background: Bioluminescence is a process in which light is emitted by a living organism. Most creatures that emit light are sea creatures, but some insects, plants, fungi etc, also emit light. The biotechnological application of bioluminescence has become routine and is considered essential for many medical and general technological advances. Identification of bioluminescent proteins is more challenging due to their poor similarity in sequence. So far, no specific method has been reported to identify bioluminescent proteins from primary sequence.Results: In this paper, we propose a novel predictive method that uses a Support Vector Machine (SVM) and physicochemical properties to predict bioluminescent proteins. BLProt was trained using a dataset consisting of 300 bioluminescent proteins and 300 non-bioluminescent proteins, and evaluated by an independent set of 141 bioluminescent proteins and 18202 non-bioluminescent proteins. To identify the most prominent features, we carried out feature selection with three different filter approaches, ReliefF, infogain, and mRMR. We selected five different feature subsets by decreasing the number of features, and the performance of each feature subset was evaluated.Conclusion: BLProt achieves 80% accuracy from training (5 fold cross-validations) and 80.06% accuracy from testing. The performance of BLProt was compared with BLAST and HMM. High prediction accuracy and successful prediction of hypothetical proteins suggests that BLProt can be a useful approach to identify bioluminescent proteins from sequence information, irrespective of their sequence similarity. 2011 Kandaswamy et al; licensee BioMed Central Ltd.

  7. Towards human behavior recognition based on spatio temporal features and support vector machines

    Science.gov (United States)

    Ghabri, Sawsen; Ouarda, Wael; Alimi, Adel M.

    2017-03-01

    Security and surveillance are vital issues in today's world. The recent acts of terrorism have highlighted the urgent need for efficient surveillance. There is indeed a need for an automated system for video surveillance which can detect identity and activity of person. In this article, we propose a new paradigm to recognize an aggressive human behavior such as boxing action. Our proposed system for human activity detection includes the use of a fusion between Spatio Temporal Interest Point (STIP) and Histogram of Oriented Gradient (HoG) features. The novel feature called Spatio Temporal Histogram Oriented Gradient (STHOG). To evaluate the robustness of our proposed paradigm with a local application of HoG technique on STIP points, we made experiments on KTH human action dataset based on Multi Class Support Vector Machines classification. The proposed scheme outperforms basic descriptors like HoG and STIP to achieve 82.26% us an accuracy value of classification rate.

  8. Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.

    Science.gov (United States)

    Hettige, Nuwan C; Nguyen, Thai Binh; Yuan, Chen; Rajakulendran, Thanara; Baddour, Jermeen; Bhagwat, Nikhil; Bani-Fatemi, Ali; Voineskos, Aristotle N; Mallar Chakravarty, M; De Luca, Vincenzo

    2017-07-01

    Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integration of many risk factors in order to build an algorithm that predicts which patients are likely to attempt suicide. Currently it is unclear how to integrate previously identified risk factors into a clinically relevant predictive tool to estimate the probability of a patient with schizophrenia for attempting suicide. We conducted a cross-sectional assessment on a sample of 345 participants diagnosed with schizophrenia spectrum disorders. Suicide attempters and non-attempters were clearly identified using the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Suicide Ideation Scale (BSS). We developed four classification algorithms using a regularized regression, random forest, elastic net and support vector machine models with sociocultural and clinical variables as features to train the models. All classification models performed similarly in identifying suicide attempters and non-attempters. Our regularized logistic regression model demonstrated an accuracy of 67% and an area under the curve (AUC) of 0.71, while the random forest model demonstrated 66% accuracy and an AUC of 0.67. Support vector classifier (SVC) model demonstrated an accuracy of 67% and an AUC of 0.70, and the elastic net model demonstrated and accuracy of 65% and an AUC of 0.71. Machine learning algorithms offer a relatively successful method for incorporating many clinical features to predict individuals at risk for future suicide attempts. Increased performance of these models using clinically relevant variables offers the potential to facilitate early treatment and intervention to prevent future suicide attempts. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Machine Fault Detection Based on Filter Bank Similarity Features Using Acoustic and Vibration Analysis

    Directory of Open Access Journals (Sweden)

    Mauricio Holguín-Londoño

    2016-01-01

    Full Text Available Vibration and acoustic analysis actively support the nondestructive and noninvasive fault diagnostics of rotating machines at early stages. Nonetheless, the acoustic signal is less used because of its vulnerability to external interferences, hindering an efficient and robust analysis for condition monitoring (CM. This paper presents a novel methodology to characterize different failure signatures from rotating machines using either acoustic or vibration signals. Firstly, the signal is decomposed into several narrow-band spectral components applying different filter bank methods such as empirical mode decomposition, wavelet packet transform, and Fourier-based filtering. Secondly, a feature set is built using a proposed similarity measure termed cumulative spectral density index and used to estimate the mutual statistical dependence between each bandwidth-limited component and the raw signal. Finally, a classification scheme is carried out to distinguish the different types of faults. The methodology is tested in two laboratory experiments, including turbine blade degradation and rolling element bearing faults. The robustness of our approach is validated contaminating the signal with several levels of additive white Gaussian noise, obtaining high-performance outcomes that make the usage of vibration, acoustic, and vibroacoustic measurements in different applications comparable. As a result, the proposed fault detection based on filter bank similarity features is a promising methodology to implement in CM of rotating machinery, even using measurements with low signal-to-noise ratio.

  10. Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

    Science.gov (United States)

    Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario

    2016-01-01

    The development of an error compensation model for coordinate measuring machines (CMMs) and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included. PMID:27690052

  11. Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part I—Model Development

    Directory of Open Access Journals (Sweden)

    Roque Calvo

    2016-09-01

    Full Text Available The development of an error compensation model for coordinate measuring machines (CMMs and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included.

  12. Feature recognition and detection for ancient architecture based on machine vision

    Science.gov (United States)

    Zou, Zheng; Wang, Niannian; Zhao, Peng; Zhao, Xuefeng

    2018-03-01

    Ancient architecture has a very high historical and artistic value. The ancient buildings have a wide variety of textures and decorative paintings, which contain a lot of historical meaning. Therefore, the research and statistics work of these different compositional and decorative features play an important role in the subsequent research. However, until recently, the statistics of those components are mainly by artificial method, which consumes a lot of labor and time, inefficiently. At present, as the strong support of big data and GPU accelerated training, machine vision with deep learning as the core has been rapidly developed and widely used in many fields. This paper proposes an idea to recognize and detect the textures, decorations and other features of ancient building based on machine vision. First, classify a large number of surface textures images of ancient building components manually as a set of samples. Then, using the convolution neural network to train the samples in order to get a classification detector. Finally verify its precision.

  13. Geodesic Flow Kernel Support Vector Machine for Hyperspectral Image Classification by Unsupervised Subspace Feature Transfer

    Directory of Open Access Journals (Sweden)

    Alim Samat

    2016-03-01

    Full Text Available In order to deal with scenarios where the training data, used to deduce a model, and the validation data have different statistical distributions, we study the problem of transformed subspace feature transfer for domain adaptation (DA in the context of hyperspectral image classification via a geodesic Gaussian flow kernel based support vector machine (GFKSVM. To show the superior performance of the proposed approach, conventional support vector machines (SVMs and state-of-the-art DA algorithms, including information-theoretical learning of discriminative cluster for domain adaptation (ITLDC, joint distribution adaptation (JDA, and joint transfer matching (JTM, are also considered. Additionally, unsupervised linear and nonlinear subspace feature transfer techniques including principal component analysis (PCA, randomized nonlinear principal component analysis (rPCA, factor analysis (FA and non-negative matrix factorization (NNMF are investigated and compared. Experiments on two real hyperspectral images show the cross-image classification performances of the GFKSVM, confirming its effectiveness and suitability when applied to hyperspectral images.

  14. The Readability of an Unreadable Text.

    Science.gov (United States)

    Gordon, Robert M.

    1980-01-01

    The Dale-Chall Readability Formula and the Fry Readability Graph were used to analyze passages of Plato's "Parmenides," a notoriously difficult literary piece. The readability levels of the text ranged from fourth to eighth grade (Dale-Chall) and from sixth to tenth grade (Fry), indicating the limitations of the readability tests. (DF)

  15. Specific Features of Chip Making and Work-piece Surface Layer Formation in Machining Thermal Coatings

    Directory of Open Access Journals (Sweden)

    V. M. Yaroslavtsev

    2016-01-01

    Full Text Available A wide range of unique engineering structural and performance properties inherent in metallic composites characterizes wear- and erosion-resistant high-temperature coatings made by thermal spraying methods. This allows their use both in manufacturing processes to enhance the wear strength of products, which have to operate under the cyclic loading, high contact pressures, corrosion and high temperatures and in product renewal.Thermal coatings contribute to the qualitative improvement of the technical level of production and product restoration using the ceramic composite materials. However, the possibility to have a significantly increased product performance, reduce their factory labour hours and materials/output ratio in manufacturing and restoration is largely dependent on the degree of the surface layer quality of products at their finishing stage, which is usually provided by different kinds of machining.When machining the plasma-sprayed thermal coatings, a removing process of the cut-off layer material is determined by its distinctive features such as a layered structure, high internal stresses, low ductility material, high tendency to the surface layer strengthening and rehardening, porosity, high abrasive properties, etc. When coatings are machined these coating properties result in specific characteristics of chip formation and conditions for formation of the billet surface layer.The chip formation of plasma-sprayed coatings was studied at micro-velocities using an experimental tool-setting microscope-based setup, created in BMSTU. The setup allowed simultaneous recording both the individual stages (phases of the chip formation process and the operating force factors.It is found that formation of individual chip elements comes with the multiple micro-cracks that cause chipping-off the small particles of material. The emerging main crack in the cut-off layer of material leads to separation of the largest chip element. Then all the stages

  16. Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features.

    Science.gov (United States)

    Szantoi, Zoltan; Escobedo, Francisco J; Abd-Elrahman, Amr; Pearlstine, Leonard; Dewitt, Bon; Smith, Scot

    2015-05-01

    Mapping of wetlands (marsh vs. swamp vs. upland) is a common remote sensing application.Yet, discriminating between similar freshwater communities such as graminoid/sedge fromremotely sensed imagery is more difficult. Most of this activity has been performed using medium to low resolution imagery. There are only a few studies using highspatial resolutionimagery and machine learning image classification algorithms for mapping heterogeneouswetland plantcommunities. This study addresses this void by analyzing whether machine learning classifierssuch as decisiontrees (DT) and artificial neural networks (ANN) can accurately classify graminoid/sedgecommunities usinghigh resolution aerial imagery and image texture data in the Everglades National Park, Florida.In addition tospectral bands, the normalized difference vegetation index, and first- and second-order texturefeatures derivedfrom the near-infrared band were analyzed. Classifier accuracies were assessed using confusiontablesand the calculated kappa coefficients of the resulting maps. The results indicated that an ANN(multilayerperceptron based on backpropagation) algorithm produced a statistically significantly higheraccuracy(82.04%) than the DT (QUEST) algorithm (80.48%) or the maximum likelihood (80.56%)classifier (αtexture features.

  17. Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine.

    Science.gov (United States)

    Yang, Zhangjing; Feng, Piaopiao; Wen, Tian; Wan, Minghua; Hong, Xunning

    2017-01-01

    Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have a similar appearance in MRI images. This similarity may lead to misclassification and could affect the treatment results. In this paper, we propose a semi-automatic method based on multi-sequence MRI to differentiate these two types of brain tumors. Our method consists of three steps: 1) the key slice is selected from 3D MRIs and region of interests (ROIs) are drawn around the tumor region; 2) different features are extracted based on prior clinical knowledge and validated using a t-test; and 3) features that are helpful for classification are used to build an original feature vector and a support vector machine is applied to perform classification. In total, 58 GBM cases and 37 lymphoma cases are used to validate our method. A leave-one-out crossvalidation strategy is adopted in our experiments. The global accuracy of our method was determined as 96.84%, which indicates that our method is effective for the differentiation of GBM and lymphoma and can be applied in clinical diagnosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review

    Science.gov (United States)

    Zhang, Xue; Acencio, Marcio Luis; Lemke, Ney

    2016-01-01

    Essential proteins/genes are indispensable to the survival or reproduction of an organism, and the deletion of such essential proteins will result in lethality or infertility. The identification of essential genes is very important not only for understanding the minimal requirements for survival of an organism, but also for finding human disease genes and new drug targets. Experimental methods for identifying essential genes are costly, time-consuming, and laborious. With the accumulation of sequenced genomes data and high-throughput experimental data, many computational methods for identifying essential proteins are proposed, which are useful complements to experimental methods. In this review, we show the state-of-the-art methods for identifying essential genes and proteins based on machine learning and network topological features, point out the progress and limitations of current methods, and discuss the challenges and directions for further research. PMID:27014079

  19. A Novel Approach for Multi Class Fault Diagnosis in Induction Machine Based on Statistical Time Features and Random Forest Classifier

    Science.gov (United States)

    Sonje, M. Deepak; Kundu, P.; Chowdhury, A.

    2017-08-01

    Fault diagnosis and detection is the important area in health monitoring of electrical machines. This paper proposes the recently developed machine learning classifier for multi class fault diagnosis in induction machine. The classification is based on random forest (RF) algorithm. Initially, stator currents are acquired from the induction machine under various conditions. After preprocessing the currents, fourteen statistical time features are estimated for each phase of the current. These parameters are considered as inputs to the classifier. The main scope of the paper is to evaluate effectiveness of RF classifier for individual and mixed fault diagnosis in induction machine. The stator, rotor and mixed faults (stator and rotor faults) are classified using the proposed classifier. The obtained performance measures are compared with the multilayer perceptron neural network (MLPNN) classifier. The results show the much better performance measures and more accurate than MLPNN classifier. For demonstration of planned fault diagnosis algorithm, experimentally obtained results are considered to build the classifier more practical.

  20. A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

    Science.gov (United States)

    Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

    2017-06-09

    Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Extending the features of RBMK refuelling machine simulator with a training tool based on virtual reality

    International Nuclear Information System (INIS)

    Khoudiakov, M.; Slonimsky, V.; Mitrofanov, S.

    2004-01-01

    include a training methodology, simulation models/ malfunctions and VR-models to support the maintenance personnel. That work is to be based on a design and creation of a multi-machine computer complex, software and information support (Data base) development, and developing anew and/or up-grade the technology system models and training support methodology. The paper gives the background for developing the training system, the features and the structure of the system in addition to the current status in the development process. The final system will be delivered to LNPP in November 2004. (Author)

  2. EEG machine learning with Higuchi fractal dimension and Sample Entropy as features for successful detection of depression

    OpenAIRE

    Cukic, Milena; Pokrajac, David; Stokic, Miodrag; Simic, slobodan; Radivojevic, Vlada; Ljubisavljevic, Milos

    2018-01-01

    Reliable diagnosis of depressive disorder is essential for both optimal treatment and prevention of fatal outcomes. In this study, we aimed to elucidate the effectiveness of two non-linear measures, Higuchi Fractal Dimension (HFD) and Sample Entropy (SampEn), in detecting depressive disorders when applied on EEG. HFD and SampEn of EEG signals were used as features for seven machine learning algorithms including Multilayer Perceptron, Logistic Regression, Support Vector Machines with the linea...

  3. Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning

    Science.gov (United States)

    2013-01-01

    Background Plastids are an important component of plant cells, being the site of manufacture and storage of chemical compounds used by the cell, and contain pigments such as those used in photosynthesis, starch synthesis/storage, cell color etc. They are essential organelles of the plant cell, also present in algae. Recent advances in genomic technology and sequencing efforts is generating a huge amount of DNA sequence data every day. The predicted proteome of these genomes needs annotation at a faster pace. In view of this, one such annotation need is to develop an automated system that can distinguish between plastid and non-plastid proteins accurately, and further classify plastid-types based on their functionality. We compared the amino acid compositions of plastid proteins with those of non-plastid ones and found significant differences, which were used as a basis to develop various feature-based prediction models using similarity-search and machine learning. Results In this study, we developed separate Support Vector Machine (SVM) trained classifiers for characterizing the plastids in two steps: first distinguishing the plastid vs. non-plastid proteins, and then classifying the identified plastids into their various types based on their function (chloroplast, chromoplast, etioplast, and amyloplast). Five diverse protein features: amino acid composition, dipeptide composition, the pseudo amino acid composition, Nterminal-Center-Cterminal composition and the protein physicochemical properties are used to develop SVM models. Overall, the dipeptide composition-based module shows the best performance with an accuracy of 86.80% and Matthews Correlation Coefficient (MCC) of 0.74 in phase-I and 78.60% with a MCC of 0.44 in phase-II. On independent test data, this model also performs better with an overall accuracy of 76.58% and 74.97% in phase-I and phase-II, respectively. The similarity-based PSI-BLAST module shows very low performance with about 50% prediction

  4. Voltammetric electronic tongue and support vector machines for identification of selected features in Mexican coffee.

    Science.gov (United States)

    Domínguez, Rocio Berenice; Moreno-Barón, Laura; Muñoz, Roberto; Gutiérrez, Juan Manuel

    2014-09-24

    This paper describes a new method based on a voltammetric electronic tongue (ET) for the recognition of distinctive features in coffee samples. An ET was directly applied to different samples from the main Mexican coffee regions without any pretreatment before the analysis. The resulting electrochemical information was modeled with two different mathematical tools, namely Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM). Growing conditions (i.e., organic or non-organic practices and altitude of crops) were considered for a first classification. LDA results showed an average discrimination rate of 88% ± 6.53% while SVM successfully accomplished an overall accuracy of 96.4% ± 3.50% for the same task. A second classification based on geographical origin of samples was carried out. Results showed an overall accuracy of 87.5% ± 7.79% for LDA and a superior performance of 97.5% ± 3.22% for SVM. Given the complexity of coffee samples, the high accuracy percentages achieved by ET coupled with SVM in both classification problems suggested a potential applicability of ET in the assessment of selected coffee features with a simpler and faster methodology along with a null sample pretreatment. In addition, the proposed method can be applied to authentication assessment while improving cost, time and accuracy of the general procedure.

  5. Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

    Directory of Open Access Journals (Sweden)

    Yeom, Ha-Neul

    2014-09-01

    Full Text Available In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

  6. Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

    Science.gov (United States)

    Jamal, Salma; Goyal, Sukriti; Shanker, Asheesh; Grover, Abhinav

    2016-10-18

    Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer's is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer's towards development of effective AD therapeutics. In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings. To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.

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

    Science.gov (United States)

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

    2016-04-01

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

  8. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Alessandra Caggiano

    2018-03-01

    Full Text Available Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA is proposed. PCA allowed to identify a smaller number of features (k = 2 features, the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax was achieved, with predicted values very close to the measured tool wear values.

  9. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition.

    Science.gov (United States)

    Caggiano, Alessandra

    2018-03-09

    Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features ( k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear ( VB max ) was achieved, with predicted values very close to the measured tool wear values.

  10. Tool Wear Prediction in Ti-6Al-4V Machining through Multiple Sensor Monitoring and PCA Features Pattern Recognition

    Science.gov (United States)

    2018-01-01

    Machining of titanium alloys is characterised by extremely rapid tool wear due to the high cutting temperature and the strong adhesion at the tool-chip and tool-workpiece interface, caused by the low thermal conductivity and high chemical reactivity of Ti alloys. With the aim to monitor the tool conditions during dry turning of Ti-6Al-4V alloy, a machine learning procedure based on the acquisition and processing of cutting force, acoustic emission and vibration sensor signals during turning is implemented. A number of sensorial features are extracted from the acquired sensor signals in order to feed machine learning paradigms based on artificial neural networks. To reduce the large dimensionality of the sensorial features, an advanced feature extraction methodology based on Principal Component Analysis (PCA) is proposed. PCA allowed to identify a smaller number of features (k = 2 features), the principal component scores, obtained through linear projection of the original d features into a new space with reduced dimensionality k = 2, sufficient to describe the variance of the data. By feeding artificial neural networks with the PCA features, an accurate diagnosis of tool flank wear (VBmax) was achieved, with predicted values very close to the measured tool wear values. PMID:29522443

  11. Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

    2018-03-01

    Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p breast cancer detected in the next subsequent mammography screening.

  12. Text Readability and Intuitive Simplification: A Comparison of Readability Formulas

    Science.gov (United States)

    Crossley, Scott A.; Allen, David B.; McNamara, Danielle S.

    2011-01-01

    Texts are routinely simplified for language learners with authors relying on a variety of approaches and materials to assist them in making the texts more comprehensible. Readability measures are one such tool that authors can use when evaluating text comprehensibility. This study compares the Coh-Metrix Second Language (L2) Reading Index, a…

  13. Visual Thing Recognition with Binary Scale-Invariant Feature Transform and Support Vector Machine Classifiers Using Color Information

    OpenAIRE

    Wei-Jong Yang; Wei-Hau Du; Pau-Choo Chang; Jar-Ferr Yang; Pi-Hsia Hung

    2017-01-01

    The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an importan...

  14. Prognosis Essay Scoring and Article Relevancy Using Multi-Text Features and Machine Learning

    Directory of Open Access Journals (Sweden)

    Arif Mehmood

    2017-01-01

    Full Text Available This study develops a model for essay scoring and article relevancy. Essay scoring is a costly process when we consider the time spent by an evaluator. It may lead to inequalities of the effort by various evaluators to apply the same evaluation criteria. Bibliometric research uses the evaluation criteria to find relevancy of articles instead. Researchers mostly face relevancy issues while searching articles. Therefore, they classify the articles manually. However, manual classification is burdensome due to time needed for evaluation. The proposed model performs automatic essay evaluation using multi-text features and ensemble machine learning. The proposed method is implemented in two data sets: a Kaggle short answer data set for essay scoring that includes four ranges of disciplines (Science, Biology, English, and English language Arts, and a bibliometric data set having IoT (Internet of Things and non-IoT classes. The efficacy of the model is measured against the Tandalla and AutoP approach using Cohen’s kappa. The model achieves kappa values of 0.80 and 0.83 for the first and second data sets, respectively. Kappa values show that the proposed model has better performance than those of earlier approaches.

  15. Emotioncy: A Potential Measure of Readability

    Science.gov (United States)

    Pishghadamn, Reza; Abbasnejad, Hannaheh

    2016-01-01

    Given the deficiencies of readability formulae as reliable tools for measuring text readability in educational settings, this study aims to offer a new measure to improve the current methods of testing the readability levels of texts through the incorporation of the newly-developed concept of emotioncy. To this end, a group of 221 students were…

  16. The Readability of Principles of Macroeconomics Textbooks

    Science.gov (United States)

    Tinkler, Sarah; Woods, James

    2013-01-01

    The authors evaluated principles of macroeconomics textbooks for readability using Coh-Metrix, a computational linguistics tool. Additionally, they conducted an experiment on Amazon's Mechanical Turk Web site in which participants ranked the readability of text samples. There was a wide range of scores on readability indexes both among…

  17. How Readable Are Parenting Books?

    Science.gov (United States)

    Abram, Marie J.; Dowling, William D.

    1979-01-01

    The author's style of writing has implications for the ease with which the written material can be read. Using the Flesch Reading Ease Formula, the mean readability score, the standard deviation, and range are given for 50 parenting books. Discussion suggests how the list might be used by parent educators. (Author)

  18. Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.

    Science.gov (United States)

    Madero Orozco, Hiram; Vergara Villegas, Osslan Osiris; Cruz Sánchez, Vianey Guadalupe; Ochoa Domínguez, Humberto de Jesús; Nandayapa Alfaro, Manuel de Jesús

    2015-02-12

    Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung nodule is a round lesion which can be either non-cancerous or cancerous. In the CT, the lung cancer is observed as round white shadow nodules. The possibility to obtain a manually accurate interpretation from CT scans demands a big effort by the radiologist and might be a fatiguing process. Therefore, the design of a computer-aided diagnosis (CADx) system would be helpful as a second opinion tool. The stages of the proposed CADx are: a supervised extraction of the region of interest to eliminate the shape differences among CT images. The Daubechies db1, db2, and db4 wavelet transforms are computed with one and two levels of decomposition. After that, 19 features are computed from each wavelet sub-band. Then, the sub-band and attribute selection is performed. As a result, 11 features are selected and combined in pairs as inputs to the support vector machine (SVM), which is used to distinguish CT images containing cancerous nodules from those not containing nodules. The clinical data set used for experiments consists of 45 CT scans from ELCAP and LIDC. For the training stage 61 CT images were used (36 with cancerous lung nodules and 25 without lung nodules). The system performance was tested with 45 CT scans (23 CT scans with lung nodules and 22 without nodules), different from that used for training. The results obtained show that the methodology successfully classifies cancerous nodules with a diameter from 2 mm to 30 mm. The total preciseness obtained was 82%; the sensitivity was 90.90%, whereas the specificity was 73.91%. The CADx system presented is competitive with other literature systems in terms of sensitivity. The system reduces the complexity of classification by not performing the typical segmentation stage of most CADx

  19. Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.

    Science.gov (United States)

    Morisi, Rita; Manners, David Neil; Gnecco, Giorgio; Lanconelli, Nico; Testa, Claudia; Evangelisti, Stefania; Talozzi, Lia; Gramegna, Laura Ludovica; Bianchini, Claudio; Calandra-Buonaura, Giovanna; Sambati, Luisa; Giannini, Giulia; Cortelli, Pietro; Tonon, Caterina; Lodi, Raffaele

    2018-02-01

    In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classification), based on a set of binary classifiers that discriminate each disorder from all others. We combine diffusion tensor imaging, proton spectroscopy and morphometric-volumetric data to obtain MR quantitative markers, which are provided to support vector machines with the aim of recognizing the different parkinsonian disorders. Feature selection is used to find the most important features for classification. We also exploit a graph-based technique on the set of quantitative markers to extract additional features from the dataset, and increase classification accuracy. When graph-based features are not used, the MR markers that are most frequently automatically extracted by the feature selection procedure reflect alterations in brain regions that are also usually considered to discriminate parkinsonisms in routine clinical practice. Graph-derived features typically increase the diagnostic accuracy, and reduce the number of features required. The results obtained in the work demonstrate that support vector machines applied to multimodal brain MR imaging and using graph-based features represent a novel and highly accurate approach to discriminate parkinsonisms, and a useful tool to assist the diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Virtual Machine Language

    Science.gov (United States)

    Grasso, Christopher; Page, Dennis; O'Reilly, Taifun; Fteichert, Ralph; Lock, Patricia; Lin, Imin; Naviaux, Keith; Sisino, John

    2005-01-01

    Virtual Machine Language (VML) is a mission-independent, reusable software system for programming for spacecraft operations. Features of VML include a rich set of data types, named functions, parameters, IF and WHILE control structures, polymorphism, and on-the-fly creation of spacecraft commands from calculated values. Spacecraft functions can be abstracted into named blocks that reside in files aboard the spacecraft. These named blocks accept parameters and execute in a repeatable fashion. The sizes of uplink products are minimized by the ability to call blocks that implement most of the command steps. This block approach also enables some autonomous operations aboard the spacecraft, such as aerobraking, telemetry conditional monitoring, and anomaly response, without developing autonomous flight software. Operators on the ground write blocks and command sequences in a concise, high-level, human-readable programming language (also called VML ). A compiler translates the human-readable blocks and command sequences into binary files (the operations products). The flight portion of VML interprets the uplinked binary files. The ground subsystem of VML also includes an interactive sequence- execution tool hosted on workstations, which runs sequences at several thousand times real-time speed, affords debugging, and generates reports. This tool enables iterative development of blocks and sequences within times of the order of seconds.

  1. Features of measurement and processing of vibration signals registered on the moving parts of electrical machines

    OpenAIRE

    Gyzhko, Yuri

    2011-01-01

    Measurement and processing of vibration signals registered on the moving parts of the electrical machines using the diagnostic information-measuring system that uses Bluetooth wireless standard for the transmission of the measured data from moving parts of electrical machine is discussed.

  2. Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.

    Science.gov (United States)

    Hussain, Lal

    2018-06-01

    Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the brain. The research reveals that brain activity is monitored through electroencephalogram (EEG) of patients suffered from seizure to detect the epileptic seizure. The performance of EEG detection based epilepsy require feature extracting strategies. In this research, we have extracted varying features extracting strategies based on time and frequency domain characteristics, nonlinear, wavelet based entropy and few statistical features. A deeper study was undertaken using novel machine learning classifiers by considering multiple factors. The support vector machine kernels are evaluated based on multiclass kernel and box constraint level. Likewise, for K-nearest neighbors (KNN), we computed the different distance metrics, Neighbor weights and Neighbors. Similarly, the decision trees we tuned the paramours based on maximum splits and split criteria and ensemble classifiers are evaluated based on different ensemble methods and learning rate. For training/testing tenfold Cross validation was employed and performance was evaluated in form of TPR, NPR, PPV, accuracy and AUC. In this research, a deeper analysis approach was performed using diverse features extracting strategies using robust machine learning classifiers with more advanced optimal options. Support Vector Machine linear kernel and KNN with City block distance metric give the overall highest accuracy of 99.5% which was higher than using the default parameters for these classifiers. Moreover, highest separation (AUC = 0.9991, 0.9990) were obtained at different kernel scales using SVM. Additionally, the K-nearest neighbors with inverse squared distance weight give higher performance at different Neighbors. Moreover, to distinguish the postictal heart rate oscillations from epileptic ictal subjects, and highest performance of 100% was obtained using different machine learning classifiers.

  3. A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

    Directory of Open Access Journals (Sweden)

    Fabio Boi

    2016-12-01

    Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.

  4. A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

    Science.gov (United States)

    Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

    2016-01-01

    Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

  5. Universally Designed Text on the Web: Towards Readability Criteria Based on Anti-Patterns.

    Science.gov (United States)

    Eika, Evelyn

    2016-01-01

    The readability of web texts affects accessibility. The Web Content Accessibility guidelines (WCAG) state that the recommended reading level should match that of someone who has completed basic schooling. However, WCAG does not give advice on what constitutes an appropriate reading level. Web authors need tools to help composing WCAG compliant texts, and specific criteria are needed. Classic readability metrics are generally based on lengths of words and sentences and have been criticized for being over-simplistic. Automatic measures and classifications of texts' reading levels employing more advanced constructs remain an unresolved problem. If such measures were feasible, what should these be? This work examines three language constructs not captured by current readability indices but believed to significantly affect actual readability, namely, relative clauses, garden path sentences, and left-branching structures. The goal is to see whether quantifications of these stylistic features reflect readability and how they correspond to common readability measures. Manual assessments of a set of authentic web texts for such uses were conducted. The results reveal that texts related to narratives such as children's stories, which are given the highest readability value, do not contain these constructs. The structures in question occur more frequently in expository texts that aim at educating or disseminating information such as strategy and journal articles. The results suggest that language anti-patterns hold potential for establishing a set of deeper readability criteria.

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

    Science.gov (United States)

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

    2017-08-04

    Inertial sensors are one of the most commonly used sources of data for human activity recognition (HAR) and exercise detection (ED) tasks. The time series produced by these sensors are generally analyzed through numerical methods. Machine learning techniques such as random forests or support vector machines are popular in this field for classification efforts, but they need to be supported through the isolation of a potentially large number of additionally crafted features derived from the raw data. This feature preprocessing step can involve nontrivial digital signal processing (DSP) techniques. However, in many cases, the researchers interested in this type of activity recognition problems do not possess the necessary technical background for this feature-set development. The study aimed to present a novel application of established machine vision methods to provide interested researchers with an easier entry path into the HAR and ED fields. This can be achieved by removing the need for deep DSP skills through the use of transfer learning. This can be done by using a pretrained convolutional neural network (CNN) developed for machine vision purposes for exercise classification effort. The new method should simply require researchers to generate plots of the signals that they would like to build classifiers with, store them as images, and then place them in folders according to their training label before retraining the network. We applied a CNN, an established machine vision technique, to the task of ED. Tensorflow, a high-level framework for machine learning, was used to facilitate infrastructure needs. Simple time series plots generated directly from accelerometer and gyroscope signals are used to retrain an openly available neural network (Inception), originally developed for machine vision tasks. Data from 82 healthy volunteers, performing 5 different exercises while wearing a lumbar-worn inertial measurement unit (IMU), was collected. The ability of the

  7. Diagnosis of Alzheimer’s Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features

    Directory of Open Access Journals (Sweden)

    Ramesh Kumar Lama

    2017-01-01

    Full Text Available Alzheimer’s disease (AD is a progressive, neurodegenerative brain disorder that attacks neurotransmitters, brain cells, and nerves, affecting brain functions, memory, and behaviors and then finally causing dementia on elderly people. Despite its significance, there is currently no cure for it. However, there are medicines available on prescription that can help delay the progress of the condition. Thus, early diagnosis of AD is essential for patient care and relevant researches. Major challenges in proper diagnosis of AD using existing classification schemes are the availability of a smaller number of training samples and the larger number of possible feature representations. In this paper, we present and compare AD diagnosis approaches using structural magnetic resonance (sMR images to discriminate AD, mild cognitive impairment (MCI, and healthy control (HC subjects using a support vector machine (SVM, an import vector machine (IVM, and a regularized extreme learning machine (RELM. The greedy score-based feature selection technique is employed to select important feature vectors. In addition, a kernel-based discriminative approach is adopted to deal with complex data distributions. We compare the performance of these classifiers for volumetric sMR image data from Alzheimer’s disease neuroimaging initiative (ADNI datasets. Experiments on the ADNI datasets showed that RELM with the feature selection approach can significantly improve classification accuracy of AD from MCI and HC subjects.

  8. Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.

    Science.gov (United States)

    Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio

    2018-02-01

    Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially important as these systems are pervasively being introduced to critical domains, such as the medical field. Representation Learning techniques are general methods for automatic feature computation. Nevertheless, these techniques are regarded as uninterpretable "black boxes". In this paper, we propose a methodology to enhance the interpretability of automatically extracted machine learning features. The proposed system is composed of a Restricted Boltzmann Machine for unsupervised feature learning, and a Random Forest classifier, which are combined to jointly consider existing correlations between imaging data, features, and target variables. We define two levels of interpretation: global and local. The former is devoted to understanding if the system learned the relevant relations in the data correctly, while the later is focused on predictions performed on a voxel- and patient-level. In addition, we propose a novel feature importance strategy that considers both imaging data and target variables, and we demonstrate the ability of the approach to leverage the interpretability of the obtained representation for the task at hand. We evaluated the proposed methodology in brain tumor segmentation and penumbra estimation in ischemic stroke lesions. We show the ability of the proposed methodology to unveil information regarding relationships between imaging modalities and extracted features and their usefulness for the task at hand. In both clinical scenarios, we demonstrate that the proposed methodology enhances the interpretability of automatically learned features, highlighting specific learning patterns that resemble how an expert extracts relevant data from medical images. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. ClearTK 2.0: Design Patterns for Machine Learning in UIMA.

    Science.gov (United States)

    Bethard, Steven; Ogren, Philip; Becker, Lee

    2014-05-01

    ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework.

  10. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Muhammad Naveed Iqbal Qureshi

    2017-09-01

    Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  11. Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

    Science.gov (United States)

    Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

    2016-05-15

    Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Applying machine learning and image feature extraction techniques to the problem of cerebral aneurysm rupture

    Directory of Open Access Journals (Sweden)

    Steren Chabert

    2017-01-01

    Full Text Available Cerebral aneurysm is a cerebrovascular disorder characterized by a bulging in a weak area in the wall of an artery that supplies blood to the brain. It is relevant to understand the mechanisms leading to the apparition of aneurysms, their growth and, more important, leading to their rupture. The purpose of this study is to study the impact on aneurysm rupture of the combination of different parameters, instead of focusing on only one factor at a time as is frequently found in the literature, using machine learning and feature extraction techniques. This discussion takes relevance in the context of the complex decision that the physicians have to take to decide which therapy to apply, as each intervention bares its own risks, and implies to use a complex ensemble of resources (human resources, OR, etc. in hospitals always under very high work load. This project has been raised in our actual working team, composed of interventional neuroradiologist, radiologic technologist, informatics engineers and biomedical engineers, from Valparaiso public Hospital, Hospital Carlos van Buren, and from Universidad de Valparaíso – Facultad de Ingeniería and Facultad de Medicina. This team has been working together in the last few years, and is now participating in the implementation of an “interdisciplinary platform for innovation in health”, as part of a bigger project leaded by Universidad de Valparaiso (PMI UVA1402. It is relevant to emphasize that this project is made feasible by the existence of this network between physicians and engineers, and by the existence of data already registered in an orderly manner, structured and recorded in digital format. The present proposal arises from the description in nowadays literature that the actual indicators, whether based on morphological description of the aneurysm, or based on characterization of biomechanical factor or others, these indicators were shown not to provide sufficient information in order

  13. Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

    Science.gov (United States)

    2013-01-01

    Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

  14. A Comparison of Supervised Machine Learning Algorithms and Feature Vectors for MS Lesion Segmentation Using Multimodal Structural MRI

    Science.gov (United States)

    Sweeney, Elizabeth M.; Vogelstein, Joshua T.; Cuzzocreo, Jennifer L.; Calabresi, Peter A.; Reich, Daniel S.; Crainiceanu, Ciprian M.; Shinohara, Russell T.

    2014-01-01

    Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance. PMID:24781953

  15. Reading apps for children: Readability from the design perspective

    Science.gov (United States)

    Mohammed, Wasan Abdulwahab; Husni, Husniza

    2017-10-01

    Electronic reading for young children opens new avenues especially with the advance of modern reading devices. The readability of mobile learning applications has received extensive attention by the designers and developers. The reason for such concern is due to its importance in determining usability related issues especially in the design context for children. In many cases, children find it difficult to interact with mobile reading apps. This is because apps for reading and for entertainment require different features. As such, this study sets out three objectives: 1) to evaluate five reading apps for young children from design perspectives; 2) to examine the readability for current existing mobile apps for reading and 3) to propose and evaluate mobile apps UI guideline for readability. Readability indices, observation and interview were conducted on 6 - 8 years old students. The obtained result showed that certain reading apps provide better reading experience for children than others. Some of the reasons are mostly related to the design characteristics embedded within the app. In addition, the use of animation was found to stimulate children reading experience as it is believed to offer the interactivity elements to gain their interest and willingness to read. These findings are believed to provide the recommendations and insights for designers of reading apps for children.

  16. Using machine learning to classify image features from canine pelvic radiographs

    DEFF Research Database (Denmark)

    McEvoy, Fintan; Amigo Rubio, Jose Manuel

    2013-01-01

    As the number of images per study increases in the field of veterinary radiology, there is a growing need for computer-assisted diagnosis techniques. The purpose of this study was to evaluate two machine learning statistical models for automatically identifying image regions that contain the canine...

  17. Multi-script handwritten character recognition : Using feature descriptors and machine learning

    NARCIS (Netherlands)

    Surinta, Olarik

    2016-01-01

    Handwritten character recognition plays an important role in transforming raw visual image data obtained from handwritten documents using for example scanners to a format which is understandable by a computer. It is an important application in the field of pattern recognition, machine learning and

  18. Using readability, comprehensibility and lexical coverage to ...

    African Journals Online (AJOL)

    experience academic difficulty in technical subjects such as Accounting. Davison and ...... The readability of managerial accounting and financial management textbooks. .... Principles and Practice in Second Language Acquisition. Available.

  19. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  20. Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

    Directory of Open Access Journals (Sweden)

    Peek Andrew S

    2007-06-01

    Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

  1. Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

    Science.gov (United States)

    Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

    2017-07-18

    Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

  2. Klasifikasi Topik Keluhan Pelanggan Berdasarkan Tweet dengan Menggunakan Penggabungan Feature Hasil Ekstraksi pada Metode Support Vector Machine (SVM

    Directory of Open Access Journals (Sweden)

    Enda Esyudha Pratama

    2015-12-01

    Full Text Available Pemanfaatan twitter sebagai layanan customer serevice perusahaan sudah mulai banyak digunakan, tak terkecuali Speedy. Mekanisme yang ada saat ini untuk proses klasifikasi bentuk dan jenis keluhan serta informasi tentang jumlah keluhan lewat twitter masih dilakukan secara manual. Belum lagi data twitter yang bersifat tidak terstruktur tentunya akan menyulitkan untuk dilakukan analisa dan penggalian informasi dari data tersebut. Berdasarkan permasalahan tersebut, penelitian ini bertujuan untuk memproses data teks dari tweet pengguna twitteryang masuk ke akun @TelkomSpeedy untuk diolah menjadi informasi. Informasi tersebut nantinya digunakan untuk klasifikasi bentuk dan jenis keluhan. Merujuk pada beberapa penelitian terkait, salah satu metode klasifikasi yang paling baik untuk digunakan adalah metode Support Vector Machine (SVM. Konsep dari SVM dapat dijelaskan secara sederhana sebagai usaha mencari hyperplane yang dapat memisahkan dataset sesuai dengan kelasnya. Kelas yang digunakan dalam penelitian kali ini berdasarkan topik keluhan pelanggan yaitu billing, pemasangan/instalasi, putus (disconnect, dan lambat. Faktor penting lainnya dalam hal klasifikasi adalah penentuan feature atau atribut kata yang akan digunakan. Metode feature selection yang digunakan pada penlitian ini adalah term frequency (TF, document frequency (DF, information gain, dan chi-square. Pada penelitian ini juga dilakukan metode penggabungan feature yang telah dihasilkan dari beberapa metode feature selection sebelumnya. Dari hasil penelitian menunjukan bahwa SVM mampu melakukan klasifikasi keluhan dengan baik, hal ini dibuktikan dengan akurasi 82,50% untuk klasifikasi bentuk keluhan dan 86,67% untuk klasifikasi jenis keluhan. Sedangkan untuk kombinasi penggunaan feature dapat meningkatkan akurasi menjadi 83,33% untuk bentuk keluhan dan 89,17% untuk jenis keluhan.   Kata Kunci—customer service, klasifikasi topik keluhan, penggabungan feature, support vector machine

  3. A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods.

    Science.gov (United States)

    Torija, Antonio J; Ruiz, Diego P

    2015-02-01

    The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.

    Science.gov (United States)

    McAllister, Patrick; Zheng, Huiru; Bond, Raymond; Moorhead, Anne

    2018-04-01

    Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and manage obesity. Computer vision methods have been applied to food logging to automate image classification for monitoring dietary intake. In this work we applied pretrained ResNet-152 and GoogleNet convolutional neural networks (CNNs), initially trained using ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset with MatConvNet package, to extract features from food image datasets; Food 5K, Food-11, RawFooT-DB, and Food-101. Deep features were extracted from CNNs and used to train machine learning classifiers including artificial neural network (ANN), support vector machine (SVM), Random Forest, and Naive Bayes. Results show that using ResNet-152 deep features with SVM with RBF kernel can accurately detect food items with 99.4% accuracy using Food-5K validation food image dataset and 98.8% with Food-5K evaluation dataset using ANN, SVM-RBF, and Random Forest classifiers. Trained with ResNet-152 features, ANN can achieve 91.34%, 99.28% when applied to Food-11 and RawFooT-DB food image datasets respectively and SVM with RBF kernel can achieve 64.98% with Food-101 image dataset. From this research it is clear that using deep CNN features can be used efficiently for diverse food item image classification. The work presented in this research shows that pretrained ResNet-152 features provide sufficient generalisation power when applied to a range of food image classification tasks. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Predicting sumoylation sites using support vector machines based on various sequence features, conformational flexibility and disorder.

    Science.gov (United States)

    Yavuz, Ahmet Sinan; Sezerman, Osman Ugur

    2014-01-01

    Sumoylation, which is a reversible and dynamic post-translational modification, is one of the vital processes in a cell. Before a protein matures to perform its function, sumoylation may alter its localization, interactions, and possibly structural conformation. Abberations in protein sumoylation has been linked with a variety of disorders and developmental anomalies. Experimental approaches to identification of sumoylation sites may not be effective due to the dynamic nature of sumoylation, laborsome experiments and their cost. Therefore, computational approaches may guide experimental identification of sumoylation sites and provide insights for further understanding sumoylation mechanism. In this paper, the effectiveness of using various sequence properties in predicting sumoylation sites was investigated with statistical analyses and machine learning approach employing support vector machines. These sequence properties were derived from windows of size 7 including position-specific amino acid composition, hydrophobicity, estimated sub-window volumes, predicted disorder, and conformational flexibility. 5-fold cross-validation results on experimentally identified sumoylation sites revealed that our method successfully predicts sumoylation sites with a Matthew's correlation coefficient, sensitivity, specificity, and accuracy equal to 0.66, 73%, 98%, and 97%, respectively. Additionally, we have showed that our method compares favorably to the existing prediction methods and basic regular expressions scanner. By using support vector machines, a new, robust method for sumoylation site prediction was introduced. Besides, the possible effects of predicted conformational flexibility and disorder on sumoylation site recognition were explored computationally for the first time to our knowledge as an additional parameter that could aid in sumoylation site prediction.

  6. Brain cells in the avian 'prefrontal cortex' code for features of slot-machine-like gambling.

    Directory of Open Access Journals (Sweden)

    Damian Scarf

    2011-01-01

    Full Text Available Slot machines are the most common and addictive form of gambling. In the current study, we recorded from single neurons in the 'prefrontal cortex' of pigeons while they played a slot-machine-like task. We identified four categories of neurons that coded for different aspects of our slot-machine-like task. Reward-Proximity neurons showed a linear increase in activity as the opportunity for a reward drew near. I-Won neurons fired only when the fourth stimulus of a winning (four-of-a-kind combination was displayed. I-Lost neurons changed their firing rate at the presentation of the first nonidentical stimulus, that is, when it was apparent that no reward was forthcoming. Finally, Near-Miss neurons also changed their activity the moment it was recognized that a reward was no longer available, but more importantly, the activity level was related to whether the trial contained one, two, or three identical stimuli prior to the display of the nonidentical stimulus. These findings not only add to recent neurophysiological research employing simulated gambling paradigms, but also add to research addressing the functional correspondence between the avian NCL and primate PFC.

  7. Integrated Features by Administering the Support Vector Machine (SVM of Translational Initiations Sites in Alternative Polymorphic Contex

    Directory of Open Access Journals (Sweden)

    Nurul Arneida Husin

    2012-04-01

    Full Text Available Many algorithms and methods have been proposed for classification problems in bioinformatics. In this study, the discriminative approach in particular support vector machines (SVM is employed to recognize the studied TIS patterns. The applied discriminative approach is used to learn about some discriminant functions of samples that have been labelled as positive or negative. After learning, the discriminant functions are employed to decide whether a new sample is true or false. In this study, support vector machines (SVM is employed to recognize the patterns for studied translational initiation sites in alternative weak context. The method has been optimized with the best parameters selected; c=100, E=10-6 and ex=2 for non linear kernel function. Results show that with top 5 features and non linear kernel, the best prediction accuracy achieved is 95.8%. J48 algorithm is applied to compare with SVM with top 15 features and the results show a good prediction accuracy of 95.8%. This indicates that the top 5 features selected by the IGR method and that are performed by SVM are sufficient to use in the prediction of TIS in weak contexts.

  8. Readability of Invasive Procedure Consent Forms.

    Science.gov (United States)

    Eltorai, Adam E M; Naqvi, Syed S; Ghanian, Soha; Eberson, Craig P; Weiss, Arnold-Peter C; Born, Christopher T; Daniels, Alan H

    2015-12-01

    Informed consent is a pillar of ethical medicine which requires patients to fully comprehend relevant issues including the risks, benefits, and alternatives of an intervention. Given the average reading skill of US adults is at the 8th grade level, the American Medical Association (AMA) and the National Institutes of Health (NIH) recommend patient information materials should not exceed a 6th grade reading level. We hypothesized that text provided in invasive procedure consent forms would exceed recommended readability guidelines for medical information. To test this hypothesis, we gathered procedure consent forms from all surgical inpatient hospitals in the state of Rhode Island. For each consent form, readability analysis was measured with the following measures: Flesch Reading Ease Formula, Flesch-Kincaid Grade Level, Fog Scale, SMOG Index, Coleman-Liau Index, Automated Readability Index, and Linsear Write Formula. These readability scores were used to calculate a composite Text Readability Consensus Grade Level. Invasive procedure consent forms were found to be written at an average of 15th grade level (i.e., third year of college), which is significantly higher than the average US adult reading level of 8th grade (p readability guidelines for patient materials of 6th grade (p readability levels which makes comprehension difficult or impossible for many patients. Efforts to improve the readability of procedural consent forms should improve patient understanding regarding their healthcare decisions. © 2015 Wiley Periodicals, Inc.

  9. Evaluating four readability formulas for Afrikaans.

    NARCIS (Netherlands)

    Jansen, C. J. M.; Richards, Rose; Van Zyl, Liezl

    2017-01-01

    For almost a hundred years now, readability formulas have been used to measure how difficult it is to comprehend a given text. To date, four readability formulas have been developed for Afrikaans. Two such formulas were published by Van Rooyen (1986), one formula by McDermid Heyns (2007) and one

  10. The Role of Auditory Features Within Slot-Themed Social Casino Games and Online Slot Machine Games.

    Science.gov (United States)

    Bramley, Stephanie; Gainsbury, Sally M

    2015-12-01

    Over the last few years playing social casino games has become a popular entertainment activity. Social casino games are offered via social media platforms and mobile apps and resemble gambling activities. However, social casino games are not classified as gambling as they can be played for free, outcomes may not be determined by chance, and players receive no monetary payouts. Social casino games appear to be somewhat similar to online gambling activities in terms of their visual and auditory features, but to date little research has investigated the cross over between these games. This study examines the auditory features of slot-themed social casino games and online slot machine games using a case study design. An example of each game type was played on three separate occasions during which, the auditory features (i.e., music, speech, sound effects, and the absence of sound) within the games were logged. The online slot-themed game was played in demo mode. This is the first study to provide a qualitative account of the role of auditory features within a slot-themed social casino game and an online slot machine game. Our results found many similarities between how sound is utilised within the two games. Therefore the sounds within these games may serve functions including: setting the scene for gaming, creating an image, demarcating space, interacting with visual features, prompting players to act, communicating achievements to players, providing reinforcement, heightening player emotions and the gaming experience. As a result this may reduce the ability of players to make a clear distinction between these two activities, which may facilitate migration between games.

  11. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Maolong Xi

    2016-01-01

    Full Text Available This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO for cancer feature gene selection, coupling support vector machine (SVM for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV. Finally, the BQPSO coupling SVM (BQPSO/SVM, binary PSO coupling SVM (BPSO/SVM, and genetic algorithm coupling SVM (GA/SVM are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

  12. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Science.gov (United States)

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

  13. Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

    Science.gov (United States)

    Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

    2014-12-01

    Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  14. Nonlinear features of the longitudinal instability for high-current machines

    International Nuclear Information System (INIS)

    Hofmann, I.; Boine-Frankenheim, O.

    1999-01-01

    We present results from experiments at the GSI machines as well as computer simulation for space charge dominated coasting beams (below transition). It is found that for the high-current machines presently under discussion the actual challenge lies in the nonlinear regime. Experiments are in good agreement with theory and simulation in the linear regime; for the nonlinear regime and long-time evolution rsp. saturation our experimental results show good agreement in some aspects, like wave steepening. To analyze the final momentum distribution we still depend on simulation, which shows that the behavior differs substantially, depending on whether the working point in the impedance plane lies close to the real (resistive dominated) or imaginary (space charge dominated) axis, or in between. For the space-charge-dominated regime (Re Z<< Im Z) it is found by computer simulation that for currents far above the Keil-Schnell threshold self-stabilization occurs by formation of a momentum tail, hence linear instability criteria can be practically ignored. It is shown here that the global impedance distribution is of crucial importance

  15. PSB LLRF: new features for machine studies and operation in the PSB 2016 run

    CERN Document Server

    Angoletta, M E

    2017-01-01

    A new digital Low-Level RF (LLRF) system has beensuccessfully deployed on the four PS Booster (PSB) ringsin June 2014, after the Long-Shutdown 1 (LS1). Althoughonly recently deployed, several new features for machinestudies and operation have already been required and im-plemented. This note provides an overview of the main fea-tures deployed for the 2016 PSB run and of their results

  16. In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

    Science.gov (United States)

    Singla, Neeru; Srivastava, Vishal; Singh Mehta, Dalip

    2018-02-01

    We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.

  17. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

    Directory of Open Access Journals (Sweden)

    Mustafa Serter Uzer

    2013-01-01

    Full Text Available This paper offers a hybrid approach that uses the artificial bee colony (ABC algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.

  18. Icing Forecasting of High Voltage Transmission Line Using Weighted Least Square Support Vector Machine with Fireworks Algorithm for Feature Selection

    Directory of Open Access Journals (Sweden)

    Tiannan Ma

    2016-12-01

    Full Text Available Accurate forecasting of icing thickness has great significance for ensuring the security and stability of the power grid. In order to improve the forecasting accuracy, this paper proposes an icing forecasting system based on the fireworks algorithm and weighted least square support vector machine (W-LSSVM. The method of the fireworks algorithm is employed to select the proper input features with the purpose of eliminating redundant influence. In addition, the aim of the W-LSSVM model is to train and test the historical data-set with the selected features. The capability of this proposed icing forecasting model and framework is tested through simulation experiments using real-world icing data from the monitoring center of the key laboratory of anti-ice disaster, Hunan, South China. The results show that the proposed W-LSSVM-FA method has a higher prediction accuracy and it may be a promising alternative for icing thickness forecasting.

  19. Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal.

    Science.gov (United States)

    Hosseinifard, Behshad; Moradi, Mohammad Hassan; Rostami, Reza

    2013-03-01

    Diagnosing depression in the early curable stages is very important and may even save the life of a patient. In this paper, we study nonlinear analysis of EEG signal for discriminating depression patients and normal controls. Forty-five unmedicated depressed patients and 45 normal subjects were participated in this study. Power of four EEG bands and four nonlinear features including detrended fluctuation analysis (DFA), higuchi fractal, correlation dimension and lyapunov exponent were extracted from EEG signal. For discriminating the two groups, k-nearest neighbor, linear discriminant analysis and logistic regression as the classifiers are then used. Highest classification accuracy of 83.3% is obtained by correlation dimension and LR classifier among other nonlinear features. For further improvement, all nonlinear features are combined and applied to classifiers. A classification accuracy of 90% is achieved by all nonlinear features and LR classifier. In all experiments, genetic algorithm is employed to select the most important features. The proposed technique is compared and contrasted with the other reported methods and it is demonstrated that by combining nonlinear features, the performance is enhanced. This study shows that nonlinear analysis of EEG can be a useful method for discriminating depressed patients and normal subjects. It is suggested that this analysis may be a complementary tool to help psychiatrists for diagnosing depressed patients. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  20. Readability assessment of online ophthalmic patient information.

    Science.gov (United States)

    Edmunds, Matthew R; Barry, Robert J; Denniston, Alastair K

    2013-12-01

    Patients increasingly use the Internet to access information related to their disease, but poor health literacy is known to impact negatively on medical outcomes. Multiple agencies have recommended that patient-oriented literature be written at a fourth- to sixth-grade (9-12 years of age) reading level to assist understanding. The readability of online patient-oriented materials related to ophthalmic diagnoses is not yet known. To assess the readability of online literature specifically for a range of ophthalmic conditions. Body text of the top 10 patient-oriented websites for 16 different ophthalmic diagnoses, covering the full range of ophthalmic subspecialties, was analyzed for readability, source (United Kingdom vs non-United Kingdom, not for profit vs commercial), and appropriateness for sight-impaired readers. Four validated readability formulas were used: Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning Fog Index (GFOG). Data were compared with the Mann-Whitney test (for 2 groups) and Kruskal-Wallis test (for more than 2 groups) and correlation was assessed by the Spearman r. None of the 160 webpages had readability scores within published guidelines, with 83% assessed as being of "difficult" readability. Not-for-profit webpages were of significantly greater length than commercial webpages (P = .02) and UK-based webpages had slightly superior readability scores compared with those of non-UK webpages (P = .004 to P readability formula used). Of all webpages evaluated, only 34% included facility to adjust text size to assist visually impaired readers. To our knowledge, this is the first study to assess readability of patient-focused webpages specifically for a range of ophthalmic diagnoses. In keeping with previous studies in other medical conditions, we determined that readability scores were inferior to those recommended, irrespective of the measure used. Although readability is only one

  1. Feature Selection based on Machine Learning in MRIs for Hippocampal Segmentation

    Science.gov (United States)

    Tangaro, Sabina; Amoroso, Nicola; Brescia, Massimo; Cavuoti, Stefano; Chincarini, Andrea; Errico, Rosangela; Paolo, Inglese; Longo, Giuseppe; Maglietta, Rosalia; Tateo, Andrea; Riccio, Giuseppe; Bellotti, Roberto

    2015-01-01

    Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic resonance imaging (MRI) scans can show these variations and therefore can be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust, and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach; for each voxel a number of local features were calculated. In this paper, we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) sequential forward selection and (iii) sequential backward elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 feature for each voxel (sequential backward elimination) we obtained comparable state-of-the-art performances with respect to the standard tool FreeSurfer.

  2. Classification of Alzheimer's disease patients with hippocampal shape wrapper-based feature selection and support vector machine

    Science.gov (United States)

    Young, Jonathan; Ridgway, Gerard; Leung, Kelvin; Ourselin, Sebastien

    2012-02-01

    It is well known that hippocampal atrophy is a marker of the onset of Alzheimer's disease (AD) and as a result hippocampal volumetry has been used in a number of studies to provide early diagnosis of AD and predict conversion of mild cognitive impairment patients to AD. However, rates of atrophy are not uniform across the hippocampus making shape analysis a potentially more accurate biomarker. This study studies the hippocampi from 226 healthy controls, 148 AD patients and 330 MCI patients obtained from T1 weighted structural MRI images from the ADNI database. The hippocampi are anatomically segmented using the MAPS multi-atlas segmentation method, and the resulting binary images are then processed with SPHARM software to decompose their shapes as a weighted sum of spherical harmonic basis functions. The resulting parameterizations are then used as feature vectors in Support Vector Machine (SVM) classification. A wrapper based feature selection method was used as this considers the utility of features in discriminating classes in combination, fully exploiting the multivariate nature of the data and optimizing the selected set of features for the type of classifier that is used. The leave-one-out cross validated accuracy obtained on training data is 88.6% for classifying AD vs controls and 74% for classifying MCI-converters vs MCI-stable with very compact feature sets, showing that this is a highly promising method. There is currently a considerable fall in accuracy on unseen data indicating that the feature selection is sensitive to the data used, however feature ensemble methods may overcome this.

  3. Man-machine interface in a submarine command and weapon control system: features and design experience

    Directory of Open Access Journals (Sweden)

    Johan H. Aas

    1989-01-01

    Full Text Available Important man-machine interface (MMI issues concerning a submarine command and weapon control system (CWCS such as crew organization, automation level and decision support are discussed in this paper. Generic submarine CWCS functions and operating conditions are outlined. Detailed, dynamic and real-time prototypes were used to support the MMI design. The prototypes are described and experience with detailed prototyping is discussed. Some of the main interaction principles are summarized and a restricted example of the resulting design is given. Our design experience and current work have been used to outline future perspectives of MMI design in naval CWCSs. The need for both formal and experimental approaches is emphasized.

  4. Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity.

    Science.gov (United States)

    Webb, Samuel J; Hanser, Thierry; Howlin, Brendan; Krause, Paul; Vessey, Jonathan D

    2014-03-25

    A new algorithm has been developed to enable the interpretation of black box models. The developed algorithm is agnostic to learning algorithm and open to all structural based descriptors such as fragments, keys and hashed fingerprints. The algorithm has provided meaningful interpretation of Ames mutagenicity predictions from both random forest and support vector machine models built on a variety of structural fingerprints.A fragmentation algorithm is utilised to investigate the model's behaviour on specific substructures present in the query. An output is formulated summarising causes of activation and deactivation. The algorithm is able to identify multiple causes of activation or deactivation in addition to identifying localised deactivations where the prediction for the query is active overall. No loss in performance is seen as there is no change in the prediction; the interpretation is produced directly on the model's behaviour for the specific query. Models have been built using multiple learning algorithms including support vector machine and random forest. The models were built on public Ames mutagenicity data and a variety of fingerprint descriptors were used. These models produced a good performance in both internal and external validation with accuracies around 82%. The models were used to evaluate the interpretation algorithm. Interpretation was revealed that links closely with understood mechanisms for Ames mutagenicity. This methodology allows for a greater utilisation of the predictions made by black box models and can expedite further study based on the output for a (quantitative) structure activity model. Additionally the algorithm could be utilised for chemical dataset investigation and knowledge extraction/human SAR development.

  5. Practical data mining and machine learning for optics applications: introduction to the feature issue.

    Science.gov (United States)

    Abdulla, Ghaleb; Awwal, Abdul; Borne, Kirk; Ho, Tin Kam; Vestrand, W Thomas

    2011-08-01

    Data mining algorithms utilize search techniques to explore hidden patterns and correlations in the data, which otherwise require a tremendous amount of human time to explore. This feature issue explores the use of such techniques to help understand the data, build better simulators, explain outlier behavior, and build better predictive models. We hope that this issue will spur discussions and expose a set of tools that can be useful to the optics community.

  6. On feature augmentation for semantic argument classification of the Quran English translation using support vector machine

    Science.gov (United States)

    Khaira Batubara, Dina; Arif Bijaksana, Moch; Adiwijaya

    2018-03-01

    Research on the semantic argument classification requires semantically labeled data in large numbers, called corpus. Because building a corpus is costly and time-consuming, recently many studies have used existing corpus as the training data to conduct semantic argument classification research on new domain. But previous studies have proven that there is a significant decrease in performance when classifying semantic arguments on different domain between the training and the testing data. The main problem is when there is a new argument that found in the testing data but it is not found in the training data. This research carries on semantic argument classification on a new domain that is Quran English Translation by utilizing Propbank corpus as the training data. To recognize the new argument in the training data, this research proposes four new features for extending the argument features in the training data. By using SVM Linear, the experiment has proven that augmenting the proposed features to the baseline system with some combinations option improve the performance of semantic argument classification on Quran data using Propbank Corpus as training data.

  7. Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment.

    Science.gov (United States)

    Torres-Valencia, Cristian A; Álvarez, Mauricio A; Orozco-Gutiérrez, Alvaro A

    2014-01-01

    Human emotion recognition (HER) allows the assessment of an affective state of a subject. Until recently, such emotional states were described in terms of discrete emotions, like happiness or contempt. In order to cover a high range of emotions, researchers in the field have introduced different dimensional spaces for emotion description that allow the characterization of affective states in terms of several variables or dimensions that measure distinct aspects of the emotion. One of the most common of such dimensional spaces is the bidimensional Arousal/Valence space. To the best of our knowledge, all HER systems so far have modelled independently, the dimensions in these dimensional spaces. In this paper, we study the effect of modelling the output dimensions simultaneously and show experimentally the advantages in modeling them in this way. We consider a multimodal approach by including features from the Electroencephalogram and a few physiological signals. For modelling the multiple outputs, we employ a multiple output regressor based on support vector machines. We also include an stage of feature selection that is developed within an embedded approach known as Recursive Feature Elimination (RFE), proposed initially for SVM. The results show that several features can be eliminated using the multiple output support vector regressor with RFE without affecting the performance of the regressor. From the analysis of the features selected in smaller subsets via RFE, it can be observed that the signals that are more informative into the arousal and valence space discrimination are the EEG, Electrooculogram/Electromiogram (EOG/EMG) and the Galvanic Skin Response (GSR).

  8. An analysis of feature relevance in the classification of astronomical transients with machine learning methods

    Science.gov (United States)

    D'Isanto, A.; Cavuoti, S.; Brescia, M.; Donalek, C.; Longo, G.; Riccio, G.; Djorgovski, S. G.

    2016-04-01

    The exploitation of present and future synoptic (multiband and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation. In this work, using data extracted from the Catalina Real Time Transient Survey (CRTS), we investigate the classification performance of some well tested methods: Random Forest, MultiLayer Perceptron with Quasi Newton Algorithm and K-Nearest Neighbours, paying special attention to the feature selection phase. In order to do so, several classification experiments were performed. Namely: identification of cataclysmic variables, separation between galactic and extragalactic objects and identification of supernovae.

  9. Predicting DNA binding proteins using support vector machine with hybrid fractal features.

    Science.gov (United States)

    Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

    2014-02-21

    DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

  10. Readability assessment of online tracheostomy care resources.

    Science.gov (United States)

    Kong, Keonho Albert; Hu, Amanda

    2015-02-01

    To assess the readability of online tracheostomy care resources. Cross-sectional study. Academic center. A Google search was performed for "tracheostomy care" in January 2014. The top 50 results were categorized into major versus minor websites and patient-oriented versus professional-oriented resources. These websites were evaluated with the following readability tools: Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (GFOG). Readability scores for the websites were FRES 57.21 ± 16.71 (possible range = 0-100), FKGL 8.33 ± 2.84 (possible range = 3-12), SMOG 11.25 ± 2.49 (possible range = 3-19), and GFOG 11.43 ± 4.07 (possible range = 3-19). There was no significant difference in all 4 readability scores between major (n = 41) and minor (n = 9) websites. Professional-oriented websites (n = 19) had the following readability scores: FRES 40.77 ± 11.69, FKGL 10.93 ± 2.48, SMOG 13.29 ± 2.32, and GFOG 14.91 ± 3.98. Patient-oriented websites (n = 31) had the following readability scores: FRES 67.29 ± 9.91, FKGL 6.73 ± 1.61, SMOG 10.01 ± 1.64, and GFOG 9.30 ± 2.27. Professional-oriented websites had more difficult readability scores than patient-oriented websites for FRES (P readability between major and minor websites. Professional-oriented websites were more difficult to read than patient-oriented websites. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014.

  11. Machine Learning Algorithms Utilizing Quantitative CT Features May Predict Eventual Onset of Bronchiolitis Obliterans Syndrome After Lung Transplantation.

    Science.gov (United States)

    Barbosa, Eduardo J Mortani; Lanclus, Maarten; Vos, Wim; Van Holsbeke, Cedric; De Backer, William; De Backer, Jan; Lee, James

    2018-02-19

    Long-term survival after lung transplantation (LTx) is limited by bronchiolitis obliterans syndrome (BOS), defined as a sustained decline in forced expiratory volume in the first second (FEV 1 ) not explained by other causes. We assessed whether machine learning (ML) utilizing quantitative computed tomography (qCT) metrics can predict eventual development of BOS. Paired inspiratory-expiratory CT scans of 71 patients who underwent LTx were analyzed retrospectively (BOS [n = 41] versus non-BOS [n = 30]), using at least two different time points. The BOS cohort experienced a reduction in FEV 1 of >10% compared to baseline FEV 1 post LTx. Multifactor analysis correlated declining FEV 1 with qCT features linked to acute inflammation or BOS onset. Student t test and ML were applied on baseline qCT features to identify lung transplant patients at baseline that eventually developed BOS. The FEV 1 decline in the BOS cohort correlated with an increase in the lung volume (P = .027) and in the central airway volume at functional residual capacity (P = .018), not observed in non-BOS patients, whereas the non-BOS cohort experienced a decrease in the central airway volume at total lung capacity with declining FEV 1 (P = .039). Twenty-three baseline qCT parameters could significantly distinguish between non-BOS patients and eventual BOS developers (P machine), we could identify BOS developers at baseline with an accuracy of 85%, using only three qCT parameters. ML utilizing qCT could discern distinct mechanisms driving FEV 1 decline in BOS and non-BOS LTx patients and predict eventual onset of BOS. This approach may become useful to optimize management of LTx patients. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  12. Understanding and Writing G & M Code for CNC Machines

    Science.gov (United States)

    Loveland, Thomas

    2012-01-01

    In modern CAD and CAM manufacturing companies, engineers design parts for machines and consumable goods. Many of these parts are cut on CNC machines. Whether using a CNC lathe, milling machine, or router, the ideas and designs of engineers must be translated into a machine-readable form called G & M Code that can be used to cut parts to precise…

  13. New features of current-driven low-frequency instabilities in a Q-machine plasma

    International Nuclear Information System (INIS)

    Dimitriu, Dan-Gheorghe; Ignatescu, Valerian; Lozneanu, Erzilia; Sanduloviciu, Mircea; Ionita, Codrina; Schrittwieser, Roman Wolfgang

    2001-01-01

    Among the instabilities in a low-density magnetized plasma column, the electrostatic ion-cyclotron instability (EICI) and the potential relaxation instability (PRI) are the best known and most thoroughly investigated. Both instabilities are excited by drawing an electron current parallel to the magnetic field towards a circular collector (CO), which is inserted into the plasma column perpendicular to the axis. For the PRI, the radius of CO must be considerably larger than the ion gyroradius so that the ion trajectories can be approximated as one-dimensional. For the EICI, the radius of CO must be considerably smaller than that of the plasma column, but also larger than one ion gyroradius. A transition from the PRI into the EICI was reported earlier. A certain range of CO radii was found where both instabilities could be excited simultaneously. We report on a strong modulation of the EICI by the PRI, obtained for gradually increasing the CO bias, with the EICI appearing at first, and later the PRI. The EICI frequency was about four times larger than that of the PRI. The modulation not only affects the amplitude but also the frequency of the EICI. This leads to the formation of sidebands in the spectrum around f EICI with a frequency difference equal to ± f PRI . In addition, we find that the EICI frequency depends not only on the magnetic field strength but also on the CO current. Our data also show a strong non-linear dependence of the PRI frequency on the magnetic field strength. To explain these features, we propose a new phenomenological model, which is able to clarify the role of complex space charge configurations for low frequency instabilities in a low-density magnetized plasma column. (authors)

  14. Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait.

    Science.gov (United States)

    Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina

    2014-03-01

    Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  15. Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Lili Chen

    2017-01-01

    Full Text Available Preterm birth (PTB is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT and extreme learning machine (ELM. For each sample, each channel was decomposed into a set of intrinsic mode functions (IMFs using empirical mode decomposition (EMD. Then, the Hilbert transform was applied to IMF to obtain analytic function. The maximum amplitude of analytic function was extracted as feature. The identification model was constructed based on ELM. Experimental results reveal that the best classification performance of the proposed method can reach an accuracy of 88.00%, a sensitivity of 91.30%, and a specificity of 85.19%. The area under receiver operating characteristic (ROC curve is 0.88. Finally, experimental results indicate that the method developed in this work could be effective in the classification of EHG between pregnancy and labour group.

  16. Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.

    Science.gov (United States)

    Chen, Lili; Hao, Yaru

    2017-01-01

    Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT) and extreme learning machine (ELM). For each sample, each channel was decomposed into a set of intrinsic mode functions (IMFs) using empirical mode decomposition (EMD). Then, the Hilbert transform was applied to IMF to obtain analytic function. The maximum amplitude of analytic function was extracted as feature. The identification model was constructed based on ELM. Experimental results reveal that the best classification performance of the proposed method can reach an accuracy of 88.00%, a sensitivity of 91.30%, and a specificity of 85.19%. The area under receiver operating characteristic (ROC) curve is 0.88. Finally, experimental results indicate that the method developed in this work could be effective in the classification of EHG between pregnancy and labour group.

  17. Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

    2017-08-01

    This paper presents a bidirectional brain machine interface (BMI) microsystem designed for closed-loop neuroscience research, especially experiments in freely behaving animals. The system-on-chip (SoC) consists of 16-channel neural recording front-ends, neural feature extraction units, 16-channel programmable neural stimulator back-ends, in-channel programmable closed-loop controllers, global analog-digital converters (ADC), and peripheral circuits. The proposed neural feature extraction units includes 1) an ultra low-power neural energy extraction unit enabling a 64-step natural logarithmic domain frequency tuning, and 2) a current-mode action potential (AP) detection unit with time-amplitude window discriminator. A programmable proportional-integral-derivative (PID) controller has been integrated in each channel enabling a various of closed-loop operations. The implemented ADCs include a 10-bit voltage-mode successive approximation register (SAR) ADC for the digitization of the neural feature outputs and/or local field potential (LFP) outputs, and an 8-bit current-mode SAR ADC for the digitization of the action potential outputs. The multi-mode stimulator can be programmed to perform monopolar or bipolar, symmetrical or asymmetrical charge balanced stimulation with a maximum current of 4 mA in an arbitrary channel configuration. The chip has been fabricated in 0.18 μ m CMOS technology, occupying a silicon area of 3.7 mm 2 . The chip dissipates 56 μW/ch on average. General purpose low-power microcontroller with Bluetooth module are integrated in the system to provide wireless link and SoC configuration. Methods, circuit techniques and system topology proposed in this work can be used in a wide range of relevant neurophysiology research, especially closed-loop BMI experiments.

  18. [Readability of surgical informed consent in Spain].

    Science.gov (United States)

    San Norberto, Enrique María; Gómez-Alonso, Daniel; Trigueros, José M; Quiroga, Jorge; Gualis, Javier; Vaquero, Carlos

    2014-03-01

    To assess the readability of informed consent documents (IC) of the different national surgical societies. During January 2012 we collected 504 IC protocols of different specialties. To calculate readability parameters the following criteria were assessed: number of words, syllables and phrases, syllables/word and word/phrase averages, Word correlation index, Flesch-Szigriszt index, Huerta Fernández index, Inflesz scale degree and the Gunning-Fog index. The mean Flesch-Szigriszt index was 50.65 ± 6,72, so readability is considered normal. There are significant differences between specialties such as Urology (43.00 ± 4.17) and Angiology and Vascular Surgery (63.00 ± 3.26, P<.001). No IC would be appropriate for adult readability according to the Fernández-Huerta index (total mean 55.77 ± 6.57); the IC of Angiology and Vascular Surgery were the closest ones (67.85 ± 3.20). Considering the Inflesz scale degree (total mean of 2.84 ± 3,23), IC can be described as «somewhat difficult». There are significant differences between the IC of Angiology and Vascular Surgery (3.23 ± 0.47) that could be qualified as normal, or Cardiovascular Surgery (2.79 ± 0.43) as «nearly normal readability»; and others such as Urology (1, 70 ± 0.46, P<.001) and Thoracic Surgery (1.90 ± 0.30, P<.001), with a readability between «very» and «somewhat» difficult. The Gunning-Fog indexes are far from the readability for a general audience (total mean of 26.29 ± 10,89). IC developed by scientific societies of different surgical specialties do not have an adequate readability for patients. We recommend the use of readability indexes during the writing of these consent forms. Copyright © 2012 AEC. Published by Elsevier Espana. All rights reserved.

  19. The Evaluation of High School Geography 9 and High School Geography 11 Text Books with Some Formulas of Readability

    Science.gov (United States)

    Gecit, Yilmaz

    2010-01-01

    The purpose of this study is to evaluate readability of 9th and 11th grade geography text-books currently used in schools. As known, one of the most fundamental features in a text-book is the readability of the text by students. In addition, it is also very important that the fluency and suitability of books match age level. In this study, the…

  20. A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification

    Directory of Open Access Journals (Sweden)

    Friehs Karl

    2008-10-01

    Full Text Available Abstract Background Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnological applications. Conventional methods for extracting information about cell viability usually need reagents to be applied on the targeted cells. These reagent-based techniques are reliable and versatile, however, some of them might be invasive and even toxic to the target cells. In support of automated noninvasive assessment of cell viability, a machine vision system has been developed. Results This system is based on supervised learning technique. It learns from images of certain kinds of cell populations and trains some classifiers. These trained classifiers are then employed to evaluate the images of given cell populations obtained via dark field microscopy. Wavelet decomposition is performed on the cell images. Energy and entropy are computed for each wavelet subimage as features. A feature selection algorithm is implemented to achieve better performance. Correlation between the results from the machine vision system and commonly accepted gold standards becomes stronger if wavelet features are utilized. The best performance is achieved with a selected subset of wavelet features. Conclusion The machine vision system based on dark field microscopy in conjugation with supervised machine learning and wavelet feature selection automates the cell viability assessment, and yields comparable results to commonly accepted methods. Wavelet features are found to be suitable to describe the discriminative properties of the live and dead cells in viability classification. According to the analysis, live cells exhibit morphologically more details and are intracellularly more organized than dead ones, which display more homogeneous and diffuse gray values throughout the cells. Feature selection increases the system's performance. The reason lies in the fact that feature

  1. Automatic Sleep Staging using Multi-dimensional Feature Extraction and Multi-kernel Fuzzy Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yanjun Zhang

    2014-01-01

    Full Text Available This paper employed the clinical Polysomnographic (PSG data, mainly including all-night Electroencephalogram (EEG, Electrooculogram (EOG and Electromyogram (EMG signals of subjects, and adopted the American Academy of Sleep Medicine (AASM clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM were learned and the multi-kernel FSVM (MK-FSVM was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

  2. Readability of Online Materials for Rhinoplasty.

    Science.gov (United States)

    Santos, Pauline Joy F; Daar, David A; Paydar, Keyianoosh Z; Wirth, Garrett A

    2018-01-01

    Rhinoplasty is a popular aesthetic and reconstructive surgical procedure. However, little is known about the content and readability of online materials for patient education. The recommended grade level for educational materials is 7th to 8th grade according to the National Institutes of Health (NIH). This study aims to assess the readability of online patient resources for rhinoplasty. The largest public search engine, Google, was queried using the term "rhinoplasty" on February 26, 2016. Location filters were disabled and sponsored results excluded to avoid any inadvertent search bias. The 10 most popular websites were identified and all relevant, patient-directed information within one click from the original site was downloaded and saved as plain text. Readability was analyzed using five established analyses (Readability-score.com, Added Bytes, Ltd., Sussex, UK). Analysis of ten websites demonstrates an average grade level of at least 12 th grade. No material was at the recommended 7 th to 8 th grade reading level (Flesch-Kincaid, 11.1; Gunning-Fog, 14.1; Coleman-Liau, 14.5; SMOG 10.4; Automated Readability, 10.7; Average Grade Level, 12.2). Overall Flesch-Kincaid Reading Ease Index was 43.5, which is rated as "difficult." Online materials available for rhinoplasty exceed NIH-recommended reading levels, which may prevent appropriate decision-making in patients considering these types of surgery. Outcomes of this study identify that Plastic Surgeons should be cognizant of available online patient materials and make efforts to develop and provide more appropriate materials. Readability results can also contribute to marketing strategy and attracting a more widespread interest in the procedure.

  3. The Readability and Complexity of District-Provided School-Choice Information

    Science.gov (United States)

    Stein, Marc L.; Nagro, Sarah

    2015-01-01

    Public school choice has become a common feature in American school districts. Any potential benefits that could be derived from these policies depend heavily on the ability of parents and students to make informed and educated decisions about their school options. We examined the readability and complexity of school-choice guides across a sample…

  4. ENTREVIS - a Spanish machine-readable text corpus

    DEFF Research Database (Denmark)

    Jensen, Kjær

    1991-01-01

    Præsentation af første halvdel et spansk tekskorpus bestående af samtlige interviews med spaniere i de to ugeskrifter Cambio16 og Tiempo i 1990. Dette korpus er siden suppleret med samtlige interviews i de samme tidsskrifter i 1995. Korpus samlede størrelse: over 1.2 million ord...

  5. Hidden Identification on Parts: Magnetic Machine-Readable Matrix Symbols

    Science.gov (United States)

    Schramm, Harry F.; Jones, Clyde S.; Roxby, Donald L.; Teed, James D.; Shih, William C. L.; Fitzpatrick, Gerald L.; Knisely, Craig

    2005-01-01

    All NASA parts have identification, usually expressed in terms of part number, serial number, and the like. In most cases, this identification is permanently marked directly on the part for tracking throughout its life cycle. NASA has developed a method for reading the matrix symbol through up to 15 mils (25 m) of paint (5 or 6 layers). This method of part identification involves coating selected patches on the objects with magnetic materials in matrix symbol patterns and reading the patterns by use of magneto-optical imaging equipment.

  6. A readability assessment of online stroke information.

    Science.gov (United States)

    Sharma, Nikhil; Tridimas, Andreas; Fitzsimmons, Paul R

    2014-07-01

    Patients and carers increasingly access the Internet as a source of health information. Poor health literacy is extremely common and frequently limits patient's comprehension of health care information literature. We aimed to assess the readability of online consumer-orientated stroke information using 2 validated readability measures. The 100 highest Google ranked consumer-oriented stroke Web pages were assessed for reading difficulty using the Flesch-Kincaid and Simple Measure of Gobbledygook (SMOG) formulae. None of the included Web pages complied with the current readability guidelines when readability was measured using the gold standard SMOG formula. Mean Flesch-Kincaid grade level was 10.4 (95% confidence interval [CI] 9.97-10.9) and mean SMOG grade 12.1 (95% CI 11.7-12.4). Over half of the Web pages were produced at graduate reading levels or above. Not-for-profit Web pages were significantly easier to read (P=.0006). The Flesch-Kincaid formula significantly underestimated reading difficulty, with a mean underestimation of 1.65 grades (95% CI 1.49-1.81), Preadability guidelines and to be comprehensible to the average patient. The Flesch-Kincaid formula significantly underestimates reading difficulty, and SMOG should be used as the measure of choice. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  7. Readability Revisited? The Implications of Text Complexity

    Science.gov (United States)

    Wray, David; Janan, Dahlia

    2013-01-01

    The concept of readability has had a variable history, moving from a position where it was considered as a very important topic for those responsible for producing texts and matching those texts to the abilities and needs of learners, to its current declining visibility in the education literature. Some important work has been coming from the USA…

  8. Validation Study of Waray Text Readability Instrument

    Science.gov (United States)

    Oyzon, Voltaire Q.; Corrales, Juven B.; Estardo, Wilfredo M., Jr.

    2015-01-01

    In 2012 the Leyte Normal University developed a computer software--modelled after the Spache Readability Formula (1953) made for English--made to help rank texts that can is used by teachers or research groups on selecting appropriate reading materials to support the DepEd's MTB-MLE program in Region VIII, in the Philippines. However,…

  9. Readability of Early Intervention Program Literature

    Science.gov (United States)

    Pizur-Barnekow, Kris; Patrick, Timothy; Rhyner, Paula M.; Cashin, Susan; Rentmeester, Angela

    2011-01-01

    Accessibility of early intervention program literature was examined through readability analysis of documents given to families who have a child served by the Birth to 3 program. Nine agencies that serve families in Birth to 3 programs located in a county in the Midwest provided the (n = 94) documents. Documents were included in the analysis if…

  10. A Readability Analysis of Selected Introductory Economics.

    Science.gov (United States)

    Gallagher, Daniel J.; Thompson, G. Rodney

    1981-01-01

    To aid secondary school and college level economics teachers as they select textbooks for introductory economics courses, this article recounts how teachers can use the Flesch Reading Ease Test to measure readability. Data are presented on application of the Flesch Reading Ease Test to 15 introductory economics textbooks. (Author/DB)

  11. Measuring the Readability of Children's Trade Books.

    Science.gov (United States)

    Popp, Helen M.; Porter, Douglas

    In order to utilize interesting children's trade books in a systematic reading program, two readability formulas were devised based on a selection of children's trade books. Children's scores on selections from these books and judges' rankings were compared. The judges' decisions were considered to be highly credible and were used as the criterion…

  12. Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

    Science.gov (United States)

    Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

    2015-10-01

    Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley

  13. SU-F-R-17: Advancing Glioblastoma Multiforme (GBM) Recurrence Detection with MRI Image Texture Feature Extraction and Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Yu, V; Ruan, D; Nguyen, D; Kaprealian, T; Chin, R; Sheng, K [UCLA School of Medicine, Los Angeles, CA (United States)

    2016-06-15

    Purpose: To test the potential of early Glioblastoma Multiforme (GBM) recurrence detection utilizing image texture pattern analysis in serial MR images post primary treatment intervention. Methods: MR image-sets of six time points prior to the confirmed recurrence diagnosis of a GBM patient were included in this study, with each time point containing T1 pre-contrast, T1 post-contrast, T2-Flair, and T2-TSE images. Eight Gray-level co-occurrence matrix (GLCM) texture features including Contrast, Correlation, Dissimilarity, Energy, Entropy, Homogeneity, Sum-Average, and Variance were calculated from all images, resulting in a total of 32 features at each time point. A confirmed recurrent volume was contoured, along with an adjacent non-recurrent region-of-interest (ROI) and both volumes were propagated to all prior time points via deformable image registration. A support vector machine (SVM) with radial-basis-function kernels was trained on the latest time point prior to the confirmed recurrence to construct a model for recurrence classification. The SVM model was then applied to all prior time points and the volumes classified as recurrence were obtained. Results: An increase in classified volume was observed over time as expected. The size of classified recurrence maintained at a stable level of approximately 0.1 cm{sup 3} up to 272 days prior to confirmation. Noticeable volume increase to 0.44 cm{sup 3} was demonstrated at 96 days prior, followed by significant increase to 1.57 cm{sup 3} at 42 days prior. Visualization of the classified volume shows the merging of recurrence-susceptible region as the volume change became noticeable. Conclusion: Image texture pattern analysis in serial MR images appears to be sensitive to detecting the recurrent GBM a long time before the recurrence is confirmed by a radiologist. The early detection may improve the efficacy of targeted intervention including radiosurgery. More patient cases will be included to create a generalizable

  14. Analyzing readability of medicines information material in Slovenia

    Science.gov (United States)

    Kasesnik, Karin; Kline, Mihael

    2011-01-01

    Objective: Readability has been claimed to be an important factor for understanding texts describing health symptoms and medications. Such texts may be a factor which indirectly affects the health of the population. Despite the expertise of physicians, the readability of information sources may be important for acquiring essential treatment information. The aim of this study was to measure the readability level of medicines promotion material in Slovenia. Methods: The Flesch readability formula was modified to comply with Slovene texts. On the basis of determining the Slovene readability algorithm, the readability ease related to the readability grade level of different Slovene texts was established. In order to estimate an adjustment of the texts to the recommended readability grade level of the targeted population, readability values of English texts were set. One sample t-test and standard deviations from the arithmetic mean values were used as statistical tests. Results: The results of the research showed low readability scores of the Slovene texts. Difficult readability values were seen in different types of examined texts: in patient information leaflets, in the summaries of product characteristics, in promotional materials, while describing over-the-counter medications and in the materials for creating disease awareness. Especially low readability values were found within the texts belonging to promotional materials intended for the physicians. None of researched items, not even for the general public, were close to primary school grade readability levels and therefore could not be described as easily readable. Conclusion: This study provides an understanding of the level of readability of selected Slovene medicines information material. It was concluded that health-related texts were not compliant with general public or with healthcare professional needs. PMID:23093886

  15. Readability Assessment of Online Patient Abdominoplasty Resources.

    Science.gov (United States)

    Phillips, Nicole A; Vargas, Christina R; Chuang, Danielle J; Lee, Bernard T

    2015-02-01

    Limited functional health literacy is recognized as an important contributor to health disparities in the United States. As internet access becomes more universal, there is increasing concern about whether patients with poor or marginal literacy can access understandable healthcare information. As such, the National Institutes of Health and American Medical Association recommend that patient information be written at a sixth grade level. This study identifies the most popular online resources for patient information about abdominoplasty and evaluates their readability in the context of average American literacy. The two largest internet search engines were queried for "tummy tuck surgery" to simulate a patient search in lay terms. The ten most popular sites common to both search engines were identified, and all relevant articles from the main sites were downloaded. Sponsored results were excluded. Readability analysis of the articles was performed using ten established tests. Online information about abdominoplasty from the ten most popular publically available websites had an overall average readability of 12th grade. Mean reading grade level scores among tests were: Coleman-Liau 11.9, Flesch-Kincaid 11.4, FORCAST 11.1, Fry 13, Gunning Fog 13.5, New Dale-Chall 11.8, New Fog Count 9.9, Raygor Estimate 12, and SMOG 13.4; Flesch Reading Ease index score was 46. Online patient resources about abdominoplasty are uniformly above the recommended target readability level and are likely too difficult for many patients to understand. A range of readability identified among websites could allow surgeons to guide patients to more appropriate resources for their literacy skills.

  16. Principal Components of Superhigh-Dimensional Statistical Features and Support Vector Machine for Improving Identification Accuracies of Different Gear Crack Levels under Different Working Conditions

    Directory of Open Access Journals (Sweden)

    Dong Wang

    2015-01-01

    Full Text Available Gears are widely used in gearbox to transmit power from one shaft to another. Gear crack is one of the most frequent gear fault modes found in industry. Identification of different gear crack levels is beneficial in preventing any unexpected machine breakdown and reducing economic loss because gear crack leads to gear tooth breakage. In this paper, an intelligent fault diagnosis method for identification of different gear crack levels under different working conditions is proposed. First, superhigh-dimensional statistical features are extracted from continuous wavelet transform at different scales. The number of the statistical features extracted by using the proposed method is 920 so that the extracted statistical features are superhigh dimensional. To reduce the dimensionality of the extracted statistical features and generate new significant low-dimensional statistical features, a simple and effective method called principal component analysis is used. To further improve identification accuracies of different gear crack levels under different working conditions, support vector machine is employed. Three experiments are investigated to show the superiority of the proposed method. Comparisons with other existing gear crack level identification methods are conducted. The results show that the proposed method has the highest identification accuracies among all existing methods.

  17. Computer-readable ''Nuclear Data Sheets''

    International Nuclear Information System (INIS)

    Ewbank, W.B.

    1975-01-01

    The evaluated nuclear structure data contained in ''Nuclear Data Sheets'' are available in computer-readable form. Experimentally established properties of nuclear levels are included as well as radiations from nuclear reactions and radioactive decay. Portions of the data can be selected for distribution in several formats on magnetic tape or computer cards. A variety of different listing and drawing formats are also available. 4 figures

  18. The readability of American Academy of Pediatrics patient education brochures.

    Science.gov (United States)

    Freda, Margaret Comerford

    2005-01-01

    The purpose of this study was to evaluate the readability of American Academy of Pediatrics (AAP) patient education brochures. Seventy-four brochures were analyzed using two readability formulas. Mean readability for all 74 brochures was grade 7.94 using the Flesch-Kincaid formula, and grade 10.1 with SMOG formula (P = .001). Using the SMOG formula, no brochures were of acceptably low (education brochures have acceptably low levels of readability, but at least half are written at higher than acceptable readability levels for the general public. This study also demonstrated statistically significant variability between the two different readability formulas; had only the SMOG formula been used, all of the brochures would have had unacceptably high readability levels. Readability is an essential concept for patient education materials. Professional associations that develop and market patient education materials should test for readability and publish those readability levels on each piece of patient education so health care providers will know if the materials are appropriate for their patients.

  19. Consent information leaflets - readable or unreadable?

    Science.gov (United States)

    Graham, Caroline; Reynard, John M; Turney, Benjamin W

    2015-05-01

    The objective of this article is to assess the readability of leaflets about urological procedures provided by the British Association of Urological Surgeons (BAUS) to evaluate their suitability for providing information. Information leaflets were assessed using three measures of readability: Flesch Reading Ease, Flesch-Kincaid and Simple Measure of Gobbledygook (SMOG) grade formulae. The scores were compared with national literacy statistics. Relatively good readability was demonstrated using the Flesch Reading Ease (53.4-60.1) and Flesch-Kincaid Grade Level (6.5-7.6) methods. However, the average SMOG index (14.0-15.0) for each category suggests that the majority of the leaflets are written above the reading level of an 18-year-old. Using national literacy statistics, at least 43% of the population will have significant difficultly understanding the majority of these leaflets. The results suggest that comprehension of the leaflets provided by the BAUS is likely to be poor. These leaflets may be used as an adjunct to discussion but it is essential to ensure that all the information necessary to make an informed decision has been conveyed in a way that can be understood by the patient.

  20. Consent information leaflets – readable or unreadable?

    Science.gov (United States)

    Graham, Caroline; Reynard, John M; Turney, Benjamin W

    2016-01-01

    Objective The objective of this article is to assess the readability of leaflets about urological procedures provided by the British Association of Urological Surgeons (BAUS) to evaluate their suitability for providing information. Methods Information leaflets were assessed using three measures of readability: Flesch Reading Ease, Flesch-Kincaid and Simple Measure of Gobbledygook (SMOG) grade formulae. The scores were compared with national literacy statistics. Results Relatively good readability was demonstrated using the Flesch Reading Ease (53.4–60.1) and Flesch-Kincaid Grade Level (6.5–7.6) methods. However, the average SMOG index (14.0–15.0) for each category suggests that the majority of the leaflets are written above the reading level of an 18-year-old. Using national literacy statistics, at least 43% of the population will have significant difficultly understanding the majority of these leaflets. Conclusions The results suggest that comprehension of the leaflets provided by the BAUS is likely to be poor. These leaflets may be used as an adjunct to discussion but it is essential to ensure that all the information necessary to make an informed decision has been conveyed in a way that can be understood by the patient. PMID:27867520

  1. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  2. Forensic scientists' conclusions: how readable are they for non-scientist report-users?

    Science.gov (United States)

    Howes, Loene M; Kirkbride, K Paul; Kelty, Sally F; Julian, Roberta; Kemp, Nenagh

    2013-09-10

    Scientists have an ethical responsibility to assist non-scientists to understand their findings and expert opinions before they are used as decision-aids within the criminal justice system. The communication of scientific expert opinion to non-scientist audiences (e.g., police, lawyers, and judges) through expert reports is an important but under-researched issue. Readability statistics were used to assess 111 conclusions from a proficiency test in forensic glass analysis. The conclusions were written using an average of 23 words per sentence, and approximately half of the conclusions were expressed using the active voice. At an average Flesch-Kincaid Grade level of university undergraduate (Grade 13), and Flesch Reading Ease score of difficult (42), the conclusions were written at a level suitable for people with some tertiary education in science, suggesting that the intended non-scientist readers would find them difficult to read. To further analyse the readability of conclusions, descriptive features of text were used: text structure; sentence structure; vocabulary; elaboration; and coherence and unity. Descriptive analysis supported the finding that texts were written at a level difficult for non-scientists to read. Specific aspects of conclusions that may pose difficulties for non-scientists were located. Suggestions are included to assist scientists to write conclusions with increased readability for non-scientist readers, while retaining scientific integrity. In the next stage of research, the readability of expert reports in their entirety is to be explored. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  3. SU-F-R-08: Can Normalization of Brain MRI Texture Features Reduce Scanner-Dependent Effects in Unsupervised Machine Learning?

    Energy Technology Data Exchange (ETDEWEB)

    Ogden, K; O’Dwyer, R [SUNY Upstate Medical University, Syracuse, NY (United States); Bradford, T [Syracuse University, Syracuse, NY (United States); Cussen, L [Rochester Institute of Technology, Rochester, NY (United States)

    2016-06-15

    Purpose: To reduce differences in features calculated from MRI brain scans acquired at different field strengths with or without Gadolinium contrast. Methods: Brain scans were processed for 111 epilepsy patients to extract hippocampus and thalamus features. Scans were acquired on 1.5 T scanners with Gadolinium contrast (group A), 1.5T scanners without Gd (group B), and 3.0 T scanners without Gd (group C). A total of 72 features were extracted. Features were extracted from original scans and from scans where the image pixel values were rescaled to the mean of the hippocampi and thalami values. For each data set, cluster analysis was performed on the raw feature set and for feature sets with normalization (conversion to Z scores). Two methods of normalization were used: The first was over all values of a given feature, and the second by normalizing within the patient group membership. The clustering software was configured to produce 3 clusters. Group fractions in each cluster were calculated. Results: For features calculated from both the non-rescaled and rescaled data, cluster membership was identical for both the non-normalized and normalized data sets. Cluster 1 was comprised entirely of Group A data, Cluster 2 contained data from all three groups, and Cluster 3 contained data from only groups 1 and 2. For the categorically normalized data sets there was a more uniform distribution of group data in the three Clusters. A less pronounced effect was seen in the rescaled image data features. Conclusion: Image Rescaling and feature renormalization can have a significant effect on the results of clustering analysis. These effects are also likely to influence the results of supervised machine learning algorithms. It may be possible to partly remove the influence of scanner field strength and the presence of Gadolinium based contrast in feature extraction for radiomics applications.

  4. SU-F-R-08: Can Normalization of Brain MRI Texture Features Reduce Scanner-Dependent Effects in Unsupervised Machine Learning?

    International Nuclear Information System (INIS)

    Ogden, K; O’Dwyer, R; Bradford, T; Cussen, L

    2016-01-01

    Purpose: To reduce differences in features calculated from MRI brain scans acquired at different field strengths with or without Gadolinium contrast. Methods: Brain scans were processed for 111 epilepsy patients to extract hippocampus and thalamus features. Scans were acquired on 1.5 T scanners with Gadolinium contrast (group A), 1.5T scanners without Gd (group B), and 3.0 T scanners without Gd (group C). A total of 72 features were extracted. Features were extracted from original scans and from scans where the image pixel values were rescaled to the mean of the hippocampi and thalami values. For each data set, cluster analysis was performed on the raw feature set and for feature sets with normalization (conversion to Z scores). Two methods of normalization were used: The first was over all values of a given feature, and the second by normalizing within the patient group membership. The clustering software was configured to produce 3 clusters. Group fractions in each cluster were calculated. Results: For features calculated from both the non-rescaled and rescaled data, cluster membership was identical for both the non-normalized and normalized data sets. Cluster 1 was comprised entirely of Group A data, Cluster 2 contained data from all three groups, and Cluster 3 contained data from only groups 1 and 2. For the categorically normalized data sets there was a more uniform distribution of group data in the three Clusters. A less pronounced effect was seen in the rescaled image data features. Conclusion: Image Rescaling and feature renormalization can have a significant effect on the results of clustering analysis. These effects are also likely to influence the results of supervised machine learning algorithms. It may be possible to partly remove the influence of scanner field strength and the presence of Gadolinium based contrast in feature extraction for radiomics applications.

  5. Classification of breast masses in ultrasound images using self-adaptive differential evolution extreme learning machine and rough set feature selection.

    Science.gov (United States)

    Prabusankarlal, Kadayanallur Mahadevan; Thirumoorthy, Palanisamy; Manavalan, Radhakrishnan

    2017-04-01

    A method using rough set feature selection and extreme learning machine (ELM) whose learning strategy and hidden node parameters are optimized by self-adaptive differential evolution (SaDE) algorithm for classification of breast masses is investigated. A pathologically proven database of 140 breast ultrasound images, including 80 benign and 60 malignant, is used for this study. A fast nonlocal means algorithm is applied for speckle noise removal, and multiresolution analysis of undecimated discrete wavelet transform is used for accurate segmentation of breast lesions. A total of 34 features, including 29 textural and five morphological, are applied to a [Formula: see text]-fold cross-validation scheme, in which more relevant features are selected by quick-reduct algorithm, and the breast masses are discriminated into benign or malignant using SaDE-ELM classifier. The diagnosis accuracy of the system is assessed using parameters, such as accuracy (Ac), sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), Matthew's correlation coefficient (MCC), and area ([Formula: see text]) under receiver operating characteristics curve. The performance of the proposed system is also compared with other classifiers, such as support vector machine and ELM. The results indicated that the proposed SaDE algorithm has superior performance with [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] compared to other classifiers.

  6. Low-Resolution Tactile Image Recognition for Automated Robotic Assembly Using Kernel PCA-Based Feature Fusion and Multiple Kernel Learning-Based Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liu

    2014-01-01

    Full Text Available In this paper, we propose a robust tactile sensing image recognition scheme for automatic robotic assembly. First, an image reprocessing procedure is designed to enhance the contrast of the tactile image. In the second layer, geometric features and Fourier descriptors are extracted from the image. Then, kernel principal component analysis (kernel PCA is applied to transform the features into ones with better discriminating ability, which is the kernel PCA-based feature fusion. The transformed features are fed into the third layer for classification. In this paper, we design a classifier by combining the multiple kernel learning (MKL algorithm and support vector machine (SVM. We also design and implement a tactile sensing array consisting of 10-by-10 sensing elements. Experimental results, carried out on real tactile images acquired by the designed tactile sensing array, show that the kernel PCA-based feature fusion can significantly improve the discriminating performance of the geometric features and Fourier descriptors. Also, the designed MKL-SVM outperforms the regular SVM in terms of recognition accuracy. The proposed recognition scheme is able to achieve a high recognition rate of over 85% for the classification of 12 commonly used metal parts in industrial applications.

  7. Readability Levels of Dental Patient Education Brochures.

    Science.gov (United States)

    Boles, Catherine D; Liu, Ying; November-Rider, Debra

    2016-02-01

    The objective of this study was to evaluate dental patient education brochures produced since 2000 to determine if there is any change in the Flesch-Kincaid grade level readability. A convenience sample of 36 brochures was obtained for analysis of the readability of the patient education material on multiple dental topics. Readability was measured using the Flesch-Kincaid Grade Level through Microsoft Word. Pearson's correlation was used to describe the relationship among the factors of interest. Backward model selection of multiple linear regression model was used to investigate the relationship between Flesch-Kincaid Grade level and a set of predictors included in this study. A convenience sample (n=36) of dental education brochures produced from 2000 to 2014 showed a mean Flesch-Kincaid reading grade level of 9.15. Weak to moderate correlations existed between word count and grade level (r=0.40) and characters count and grade level (r=0.46); strong correlations were found between grade level and average words per sentence (r=0.70), average characters per word (r=0.85) and Flesch Reading Ease (r=-0.98). Only 1 brochure out of the sample met the recommended sixth grade reading level (Flesch-Kincaid Grade Level 5.7). Overall, the Flesch-Kincaid Grade Level of all brochures was significantly higher than the recommended sixth grade reading level (preadability of the brochures. However, the majority of the brochures analyzed are still testing above the recommended sixth grade reading level. Copyright © 2016 The American Dental Hygienists’ Association.

  8. Implementation of support vector machine for classification of speech marked hijaiyah letters based on Mel frequency cepstrum coefficient feature extraction

    Science.gov (United States)

    Adhi Pradana, Wisnu; Adiwijaya; Novia Wisesty, Untari

    2018-03-01

    Support Vector Machine or commonly called SVM is one method that can be used to process the classification of a data. SVM classifies data from 2 different classes with hyperplane. In this study, the system was built using SVM to develop Arabic Speech Recognition. In the development of the system, there are 2 kinds of speakers that have been tested that is dependent speakers and independent speakers. The results from this system is an accuracy of 85.32% for speaker dependent and 61.16% for independent speakers.

  9. Grammatical Metaphor, Controlled Languageand Machine Translation

    DEFF Research Database (Denmark)

    Møller, Margrethe

    2003-01-01

    It is a general assumption that 1) the readability and clarity of LSP texts written in a controlled language are better than uncontrolled texts and 2) that controlled languages produce better results with machine translation than uncontrolled languages. Controlled languages impose lexical...

  10. Method of generating a computer readable model

    DEFF Research Database (Denmark)

    2008-01-01

    A method of generating a computer readable model of a geometrical object constructed from a plurality of interconnectable construction elements, wherein each construction element has a number of connection elements for connecting the construction element with another construction element. The met......A method of generating a computer readable model of a geometrical object constructed from a plurality of interconnectable construction elements, wherein each construction element has a number of connection elements for connecting the construction element with another construction element....... The method comprises encoding a first and a second one of the construction elements as corresponding data structures, each representing the connection elements of the corresponding construction element, and each of the connection elements having associated with it a predetermined connection type. The method...... further comprises determining a first connection element of the first construction element and a second connection element of the second construction element located in a predetermined proximity of each other; and retrieving connectivity information of the corresponding connection types of the first...

  11. Readability of patient information pamphlets in urogynecology.

    Science.gov (United States)

    Reagan, Krista M L; O'Sullivan, David M; Harvey, David P; Lasala, Christine A

    2015-01-01

    The purpose of this study was to determine the reading level of frequently used patient information pamphlets and documents in the field of urogynecology. Urogynecology pamphlets were identified from a variety of sources. Readability was determined using 4 different accepted formulas: the Flesch-Kincaid Grade Level, the simple measure of gobbledygook Index, the Coleman-Liau Index, and the Gunning Fog index. The scores were calculated using an online calculator (http://www.readability-score.com). Descriptive statistics were used for analysis. The average of the 4 scores was calculated for each pamphlet. Subsequently, Z-scores were used to standardize the averages between the reading scales. Of the 40 documents reviewed, only a single pamphlet met the National Institutes of Health-recommended reading level. This document was developed by the American Urological Association and was specifically designated as a "Low-Literacy Brochure." The remainder of the patient education pamphlets, from both industry-sponsored and academic-sponsored sources, consistently rated above the recommended reading level for maximum comprehension. The majority of patient education pamphlets, from both industry-sponsored and academic-sponsored sources, are above the reading level recommended by the National Institutes of Health for maximum patient comprehension. Future work should be done to improve the educational resources available to patients by simplifying the verbiage in these documents.

  12. Readability of Malaria Medicine Information Leaflets in Nigeria ...

    African Journals Online (AJOL)

    Purpose: To assess the readability of malaria medicines information leaflets available in Nigeria. Methods: Fourty five leaflets were assessed using the Simplified Measure of Gobbledygook (SMOG) readability test and by examining them for paper type, font size type, use of symbols and pictograms, and bilingual information ...

  13. Readability and Understandability of Online Vocal Cord Paralysis Materials.

    Science.gov (United States)

    Balakrishnan, Vini; Chandy, Zachariah; Hseih, Amy; Bui, Thanh-Lan; Verma, Sunil P

    2016-03-01

    Patients use several online resources to learn about vocal cord paralysis (VCP). The objective of this study was to assess the readability and understandability of online VCP patient education materials (PEMs), with readability assessments and the Patient Education Materials Evaluation Tool (PEMAT), respectively. The relationship between readability and understandability was then analyzed. Descriptive and correlational design. Online PEMs were identified by performing a Google search with the term "vocal cord paralysis." After scientific webpages, news articles, and information for medical professionals were excluded, 29 articles from the first 50 search results were considered. Readability analysis was performed with 6 formulas. Four individuals with different educational backgrounds conducted understandability analysis with the PEMAT. Fleiss's Kappa interrater reliability analysis determined consistency among raters. Correlation between readability and understandability was determined with Pearson's correlation test. The reading level of the reviewed articles ranged from grades 9 to 17. Understandability ranged from 29% to 82%. Correlation analysis demonstrated a strong negative correlation between materials' readability and understandability (r = -0.462, P Online PEMs pertaining to VCP are written above the recommended reading levels. Overall, materials written at lower grade levels are more understandable. However, articles of identical grade levels had varying levels of understandability. The PEMAT may provide a more critical evaluation of the quality of a PEM when compared with readability formulas. Both readability and understandability should be used to evaluate PEMs. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

  14. Readability Levels of the 1975 Third Grade Macmillan Basal Readers.

    Science.gov (United States)

    McKinney, Ernestine Williams

    1983-01-01

    Analysis of third-grade books in the New Macmillan Reading Program reveals that the books exceeded the publisher's designation of readability and did not progress in difficulty from easy to more difficult. Findings suggest the need for more complete and reliable information from publishers concerning textbook readability. (FL)

  15. Measuring the Readability of Elementary Algebra Using the Cloze Technique.

    Science.gov (United States)

    Kulm, Gerald

    The relationship to readability of ten variables characterizing structural properties of mathematical prose was investigated in elementary algebra textbooks. Readability was measured by algebra student's responses to two forms of cloze tests. Linear and currilinear correlations were calculated between each structural variable and the cloze test.…

  16. Readability of Brochures Produced by State of Florida.

    Science.gov (United States)

    Christ, William G.; Pharr, Paula

    1980-01-01

    A study of the readability of governmental pamphlets produced by the State of Florida, based on the use of the Flesch Reading Ease Formula and the Dale-Chall Formula, suggests that if a seventh or eighth grade readability level is considered an appropriate standard for public information brochures, the brochures tested may be too complex…

  17. readability of comprehension passages in junior high school (jhs)

    African Journals Online (AJOL)

    CHARLES

    ... to enhance readability. Key Words: readability formulas, comprehension passages, Junior High School, .... Index has a manual version but in this study the electronic version was used. The ..... probably the majority of the people heard the news by word of mouth. A critical look ..... The Journal of Tourism Studies 9.2: 49-60.

  18. Textbooks in Management, Marketing and Finance: An Analysis of Readability.

    Science.gov (United States)

    Gallagher, Daniel J.; Thompson, G. Rodney

    1982-01-01

    Examines the readability of texts in basic junior level college courses in the fields of management, marketing, and finance. The readability model is described, along with its application and results. Specific texts and how they fared are listed in accompanying tables. (CT)

  19. Readability as a Factor in Magazine Ad Copy Recall.

    Science.gov (United States)

    Wesson, David A.

    1989-01-01

    Examines the relationship between advertising copy readability and advertising effectiveness. Finds that recall is improved when the copy style is either fairly easy or fairly hard to read. Suggests the value of considering copy readability as a potential contributor, though a minor one, to the success of magazine advertising. (RS)

  20. Classification of nervous system withdrawn and approved drugs with ToxPrint features via machine learning strategies.

    Science.gov (United States)

    Onay, Aytun; Onay, Melih; Abul, Osman

    2017-04-01

    Early-phase virtual screening of candidate drug molecules plays a key role in pharmaceutical industry from data mining and machine learning to prevent adverse effects of the drugs. Computational classification methods can distinguish approved drugs from withdrawn ones. We focused on 6 data sets including maximum 110 approved and 110 withdrawn drugs for all and nervous system diseases to distinguish approved drugs from withdrawn ones. In this study, we used support vector machines (SVMs) and ensemble methods (EMs) such as boosted and bagged trees to classify drugs into approved and withdrawn categories. Also, we used CORINA Symphony program to identify Toxprint chemotypes including over 700 predefined chemotypes for determination of risk and safety assesment of candidate drug molecules. In addition, we studied nervous system withdrawn drugs to determine the key fragments with The ParMol package including gSpan algorithm. According to our results, the descriptors named as the number of total chemotypes and bond CN_amine_aliphatic_generic were more significant descriptors. The developed Medium Gaussian SVM model reached 78% prediction accuracy on test set for drug data set including all disease. Here, bagged tree and linear SVM models showed 89% of accuracies for phycholeptics and psychoanaleptics drugs. A set of discriminative fragments in nervous system withdrawn drug (NSWD) data sets was obtained. These fragments responsible for the drugs removed from market were benzene, toluene, N,N-dimethylethylamine, crotylamine, 5-methyl-2,4-heptadiene, octatriene and carbonyl group. This paper covers the development of computational classification methods to distinguish approved drugs from withdrawn ones. In addition, the results of this study indicated the identification of discriminative fragments is of significance to design a new nervous system approved drugs with interpretation of the structures of the NSWDs. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Comparative Performance Analysis of Support Vector Machine, Random Forest, Logistic Regression and k-Nearest Neighbours in Rainbow Trout (Oncorhynchus Mykiss) Classification Using Image-Based Features.

    Science.gov (United States)

    Saberioon, Mohammadmehdi; Císař, Petr; Labbé, Laurent; Souček, Pavel; Pelissier, Pablo; Kerneis, Thierry

    2018-03-29

    The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based features. In total, one-hundred and sixty rainbow trout ( Oncorhynchus mykiss ) were fed either a fish-meal based diet (80 fish) or a 100% plant-based diet (80 fish) and photographed using consumer-grade digital camera. Twenty-three colour features and four texture features were extracted. Four different classification methods were used to evaluate fish diets including Random forest (RF), Support vector machine (SVM), Logistic regression (LR) and k -Nearest neighbours ( k -NN). The SVM with radial based kernel provided the best classifier with correct classification rate (CCR) of 82% and Kappa coefficient of 0.65. Although the both LR and RF methods were less accurate than SVM, they achieved good classification with CCR 75% and 70% respectively. The k -NN was the least accurate (40%) classification model. Overall, it can be concluded that consumer-grade digital cameras could be employed as the fast, accurate and non-invasive sensor for classifying rainbow trout based on their diets. Furthermore, these was a close association between image-based features and fish diet received during cultivation. These procedures can be used as non-invasive, accurate and precise approaches for monitoring fish status during the cultivation by evaluating diet's effects on fish skin.

  2. Comparative Performance Analysis of Support Vector Machine, Random Forest, Logistic Regression and k-Nearest Neighbours in Rainbow Trout (Oncorhynchus Mykiss Classification Using Image-Based Features

    Directory of Open Access Journals (Sweden)

    Mohammadmehdi Saberioon

    2018-03-01

    Full Text Available The main aim of this study was to develop a new objective method for evaluating the impacts of different diets on the live fish skin using image-based features. In total, one-hundred and sixty rainbow trout (Oncorhynchus mykiss were fed either a fish-meal based diet (80 fish or a 100% plant-based diet (80 fish and photographed using consumer-grade digital camera. Twenty-three colour features and four texture features were extracted. Four different classification methods were used to evaluate fish diets including Random forest (RF, Support vector machine (SVM, Logistic regression (LR and k-Nearest neighbours (k-NN. The SVM with radial based kernel provided the best classifier with correct classification rate (CCR of 82% and Kappa coefficient of 0.65. Although the both LR and RF methods were less accurate than SVM, they achieved good classification with CCR 75% and 70% respectively. The k-NN was the least accurate (40% classification model. Overall, it can be concluded that consumer-grade digital cameras could be employed as the fast, accurate and non-invasive sensor for classifying rainbow trout based on their diets. Furthermore, these was a close association between image-based features and fish diet received during cultivation. These procedures can be used as non-invasive, accurate and precise approaches for monitoring fish status during the cultivation by evaluating diet’s effects on fish skin.

  3. SU-D-204-01: A Methodology Based On Machine Learning and Quantum Clustering to Predict Lung SBRT Dosimetric Endpoints From Patient Specific Anatomic Features

    Energy Technology Data Exchange (ETDEWEB)

    Lafata, K; Ren, L; Wu, Q; Kelsey, C; Hong, J; Cai, J; Yin, F [Duke University Medical Center, Durham, NC (United States)

    2016-06-15

    Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space to identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong

  4. The readability of psychosocial wellness patient resources: improving surgical outcomes.

    Science.gov (United States)

    Kugar, Meredith A; Cohen, Adam C; Wooden, William; Tholpady, Sunil S; Chu, Michael W

    2017-10-01

    Patient education is increasingly accessed with online resources and is essential for patient satisfaction and clinical outcomes. The average American adult reads at a seventh grade level, and the National Institute of Health (NIH) and the American Medical Association (AMA) recommend that information be written at a sixth-grade reading level. Health literacy plays an important role in the disease course and outcomes of all patients, including those with depression and likely other psychiatric disorders, although this is an area in need of further study. The purpose of this study was to collect and analyze written, online mental health resources on the Veterans Health Administration (VA) website, and other websites, using readability assessment instruments. An internet search was performed to identify written patient education information regarding mental health from the VA (the VA Mental Health Website) and top-rated psychiatric hospitals. Seven mental health topics were included in the analysis: generalized anxiety disorder, bipolar, major depressive disorder, posttraumatic stress disorder, schizophrenia, substance abuse, and suicide. Readability analyses were performed using the Gunning Fog Index, the Flesch-Kincaid Grade Level, the Coleman-Liau Index, the SMOG Readability Formula, and the Automated Readability Index. These scores were then combined into a Readability Consensus score. A two-tailed t-test was used to compare the mean values, and statistical significance was set at P readability consensus than six of the top psychiatric hospitals (P readability consensus for mental health information on all websites analyzed was 9.52. Online resources for mental health disorders are more complex than recommended by the NIH and AMA. Efforts to improve readability of mental health and psychosocial wellness resources could benefit patient understanding and outcomes, especially in patients with lower literacy. Surgical outcomes are correlated with patient mental

  5. Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening

    Science.gov (United States)

    Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te

    2018-03-01

    Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p  =  0.002 518), sigma (p  =  0.002 781), uniformity (p  =  0.032 41), and entropy (p  =  0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining

  6. Comparison of Different Machine Learning Algorithms for Lithological Mapping Using Remote Sensing Data and Morphological Features: A Case Study in Kurdistan Region, NE Iraq

    Science.gov (United States)

    Othman, Arsalan; Gloaguen, Richard

    2015-04-01

    Topographic effects and complex vegetation cover hinder lithology classification in mountain regions based not only in field, but also in reflectance remote sensing data. The area of interest "Bardi-Zard" is located in the NE of Iraq. It is part of the Zagros orogenic belt, where seven lithological units outcrop and is known for its chromite deposit. The aim of this study is to compare three machine learning algorithms (MLAs): Maximum Likelihood (ML), Support Vector Machines (SVM), and Random Forest (RF) in the context of a supervised lithology classification task using Advanced Space-borne Thermal Emission and Reflection radiometer (ASTER) satellite, its derived, spatial information (spatial coordinates) and geomorphic data. We emphasize the enhancement in remote sensing lithological mapping accuracy that arises from the integration of geomorphic features and spatial information (spatial coordinates) in classifications. This study identifies that RF is better than ML and SVM algorithms in almost the sixteen combination datasets, which were tested. The overall accuracy of the best dataset combination with the RF map for the all seven classes reach ~80% and the producer and user's accuracies are ~73.91% and 76.09% respectively while the kappa coefficient is ~0.76. TPI is more effective with SVM algorithm than an RF algorithm. This paper demonstrates that adding geomorphic indices such as TPI and spatial information in the dataset increases the lithological classification accuracy.

  7. Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

    Science.gov (United States)

    Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

    2018-06-01

    With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

  8. IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform.

    Directory of Open Access Journals (Sweden)

    N Lance Hepler

    2014-09-01

    Full Text Available Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab, determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license, documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

  9. The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection

    Directory of Open Access Journals (Sweden)

    Jin-peng Liu

    2017-07-01

    Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.

  10. Readability Formulas as Applied to College Economics Textbooks.

    Science.gov (United States)

    McConnell, Campbell R.

    1982-01-01

    Determines from empirical information on the application of four readability formulas to a group of widely used college economics textbooks that there is no consistency in the absolute reading levels or the rank orderings of these books. (AEA)

  11. Classification of radiological errors in chest radiographs, using support vector machine on the spatial frequency features of false- negative and false-positive regions

    Science.gov (United States)

    Pietrzyk, Mariusz W.; Donovan, Tim; Brennan, Patrick C.; Dix, Alan; Manning, David J.

    2011-03-01

    Aim: To optimize automated classification of radiological errors during lung nodule detection from chest radiographs (CxR) using a support vector machine (SVM) run on the spatial frequency features extracted from the local background of selected regions. Background: The majority of the unreported pulmonary nodules are visually detected but not recognized; shown by the prolonged dwell time values at false-negative regions. Similarly, overestimated nodule locations are capturing substantial amounts of foveal attention. Spatial frequency properties of selected local backgrounds are correlated with human observer responses either in terms of accuracy in indicating abnormality position or in the precision of visual sampling the medical images. Methods: Seven radiologists participated in the eye tracking experiments conducted under conditions of pulmonary nodule detection from a set of 20 postero-anterior CxR. The most dwelled locations have been identified and subjected to spatial frequency (SF) analysis. The image-based features of selected ROI were extracted with un-decimated Wavelet Packet Transform. An analysis of variance was run to select SF features and a SVM schema was implemented to classify False-Negative and False-Positive from all ROI. Results: A relative high overall accuracy was obtained for each individually developed Wavelet-SVM algorithm, with over 90% average correct ratio for errors recognition from all prolonged dwell locations. Conclusion: The preliminary results show that combined eye-tracking and image-based features can be used for automated detection of radiological error with SVM. The work is still in progress and not all analytical procedures have been completed, which might have an effect on the specificity of the algorithm.

  12. Using a Feature Subset Selection method and Support Vector Machine to address curse of dimensionality and redundancy in Hyperion hyperspectral data classification

    Directory of Open Access Journals (Sweden)

    Amir Salimi

    2018-04-01

    Full Text Available The curse of dimensionality resulted from insufficient training samples and redundancy is considered as an important problem in the supervised classification of hyperspectral data. This problem can be handled by Feature Subset Selection (FSS methods and Support Vector Machine (SVM. The FSS methods can manage the redundancy by removing redundant spectral bands. Moreover, kernel based methods, especially SVM have a high ability to classify limited-sample data sets. This paper mainly aims to assess the capability of a FSS method and the SVM in curse of dimensional circumstances and to compare results with the Artificial Neural Network (ANN, when they are used to classify alteration zones of the Hyperion hyperspectral image acquired from the greatest Iranian porphyry copper complex. The results demonstrated that by decreasing training samples, the accuracy of SVM was just decreased 1.8% while the accuracy of ANN was highly reduced i.e. 14.01%. In addition, a hybrid FSS was applied to reduce the dimension of Hyperion. Accordingly, among the 165 useable spectral bands of Hyperion, 18 bands were only selected as the most important and informative bands. Although this dimensionality reduction could not intensively improve the performance of SVM, ANN revealed a significant improvement in the computational time and a slightly enhancement in the average accuracy. Therefore, SVM as a low-sensitive method respect to the size of training data set and feature space can be applied to classify the curse of dimensional problems. Also, the FSS methods can improve the performance of non-kernel based classifiers by eliminating redundant features. Keywords: Curse of dimensionality, Feature Subset Selection, Hydrothermal alteration, Hyperspectral, SVM

  13. Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping.

    Science.gov (United States)

    Sadeghi-Tehran, Pouria; Virlet, Nicolas; Sabermanesh, Kasra; Hawkesford, Malcolm J

    2017-01-01

    Accurately segmenting vegetation from the background within digital images is both a fundamental and a challenging task in phenotyping. The performance of traditional methods is satisfactory in homogeneous environments, however, performance decreases when applied to images acquired in dynamic field environments. In this paper, a multi-feature learning method is proposed to quantify vegetation growth in outdoor field conditions. The introduced technique is compared with the state-of the-art and other learning methods on digital images. All methods are compared and evaluated with different environmental conditions and the following criteria: (1) comparison with ground-truth images, (2) variation along a day with changes in ambient illumination, (3) comparison with manual measurements and (4) an estimation of performance along the full life cycle of a wheat canopy. The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.

  14. Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping

    Directory of Open Access Journals (Sweden)

    Pouria Sadeghi-Tehran

    2017-11-01

    Full Text Available Abstract Background Accurately segmenting vegetation from the background within digital images is both a fundamental and a challenging task in phenotyping. The performance of traditional methods is satisfactory in homogeneous environments, however, performance decreases when applied to images acquired in dynamic field environments. Results In this paper, a multi-feature learning method is proposed to quantify vegetation growth in outdoor field conditions. The introduced technique is compared with the state-of the-art and other learning methods on digital images. All methods are compared and evaluated with different environmental conditions and the following criteria: (1 comparison with ground-truth images, (2 variation along a day with changes in ambient illumination, (3 comparison with manual measurements and (4 an estimation of performance along the full life cycle of a wheat canopy. Conclusion The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.

  15. Exploration on Automated Software Requirement Document Readability Approaches

    OpenAIRE

    Chen, Mingda; He, Yao

    2017-01-01

    Context. The requirements analysis phase, as the very beginning of software development process, has been identified as a quite important phase in the software development lifecycle. Software Requirement Specification (SRS) is the output of requirements analysis phase, whose quality factors play an important role in the evaluation work. Readability is a quite important SRS quality factor, but there are few available automated approaches for readability measurement, because of the tight depend...

  16. Readability of pediatric health materials for preventive dental care

    Directory of Open Access Journals (Sweden)

    Riedy Christine A

    2006-11-01

    Full Text Available Abstract Background This study examined the content and general readability of pediatric oral health education materials for parents of young children. Methods Twenty-seven pediatric oral health pamphlets or brochures from commercial, government, industry, and private nonprofit sources were analyzed for general readability ("usability" according to several parameters: readability, (Flesch-Kincaid grade level, Flesch Reading Ease, and SMOG grade level; thoroughness, (inclusion of topics important to young childrens' oral health; textual framework (frequency of complex phrases, use of pictures, diagrams, and bulleted text within materials; and terminology (frequency of difficult words and dental jargon. Results Readability of the written texts ranged from 2nd to 9th grade. The average Flesch-Kincaid grade level for government publications was equivalent to a grade 4 reading level (4.73, range, 2.4 – 6.6; F-K grade levels for commercial publications averaged 8.1 (range, 6.9 – 8.9; and industry published materials read at an average Flesch-Kincaid grade level of 7.4 (range, 4.7 – 9.3. SMOG readability analysis, based on a count of polysyllabic words, consistently rated materials 2 to 3 grade levels higher than did the Flesch-Kincaid analysis. Government sources were significantly lower compared to commercial and industry sources for Flesch-Kincaid grade level and SMOG readability analysis. Content analysis found materials from commercial and industry sources more complex than government-sponsored publications, whereas commercial sources were more thorough in coverage of pediatric oral health topics. Different materials frequently contained conflicting information. Conclusion Pediatric oral health care materials are readily available, yet their quality and readability vary widely. In general, government publications are more readable than their commercial and industry counterparts. The criteria for usability and results of the analyses

  17. Readability of websites containing information on dental implants.

    Science.gov (United States)

    Jayaratne, Yasas S N; Anderson, Nina K; Zwahlen, Roger A

    2014-12-01

    It is recommended that health-related materials for patients be written at sixth grade level or below. Many websites oriented toward patient education about dental implants are available, but the readability of these sites has not been evaluated. To assess readability of patient-oriented online information on dental implants. Websites containing patient-oriented information on dental implants were retrieved using the Google search engine. Individual and mean readability/grade levels were calculated using standardized formulas. Readability of each website was classified as easy (≤ 6th-grade level) or difficult (≥ 10th grade level). Thirty nine websites with patient-oriented information on dental implant were found. The average readability grade level of these websites was 11.65 ± 1.36. No website scored at/below the recommended 6th grade level. Thirty four of 39 websites (87.18%) were difficult to read. The number of characters, words, and sentences on these sites varied widely. All patient-oriented websites on dental implants scored above the recommended grade level, and majority of these sites were "difficult" in their readability. There is a dire need to create patient information websites on implants, which the majority can read. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Readability of patient information and consent documents in rheumatological studies.

    Science.gov (United States)

    Hamnes, Bente; van Eijk-Hustings, Yvonne; Primdahl, Jette

    2016-07-16

    Before participation in medical research an informed consent must be obtained. This study investigates whether the readability of patient information and consent documents (PICDs) corresponds to the average educational level of participants in rheumatological studies in the Netherlands, Denmark, and Norway. 24 PICDs from studies were collected and readability was assessed independently using the Gunning's Fog Index (FOG) and Simple Measure of Gobbledygook (SMOG) grading. The mean score for the FOG and SMOG grades were 14.2 (9.0-19.0) and 14.2 (12-17) respectively. The mean FOG and SMOG grades were 12.7 and 13.3 in the Dutch studies, 15.0 and 14.9 in the Danish studies, and 14.6 and 14.3 in the Norwegian studies, respectively. Out of the 2865 participants, more than 57 % had a lower educational level than the highest readability score calculated in the individual study. As the readability level of the PICDs did not match the participants' educational level, consent may not have been valid, as the participants may have had a limited understanding of what they agreed to participate in. There should be more focus on the readability of PICDs. National guidelines for how to write clear and unambiguous PICDs in simple and easily understandable language could increase the focus on the readability of PICD.

  19. Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine

    Directory of Open Access Journals (Sweden)

    Yang Zhang

    2015-11-01

    Full Text Available Prognostics is necessary to ensure the reliability and safety of lithium-ion batteries for hybrid electric vehicles or satellites. This process can be achieved by capacity estimation, which is a direct fading indicator for assessing the state of health of a battery. However, the capacity of a lithium-ion battery onboard is difficult to monitor. This paper presents a data-driven approach for online capacity estimation. First, six novel features are extracted from cyclic charge/discharge cycles and used as indirect health indicators. An adaptive multi-kernel relevance machine (MKRVM based on accelerated particle swarm optimization algorithm is used to determine the optimal parameters of MKRVM and characterize the relationship between extracted features and battery capacity. The overall estimation process comprises offline and online stages. A supervised learning step in the offline stage is established for model verification to ensure the generalizability of MKRVM for online application. Cross-validation is further conducted to validate the performance of the proposed model. Experiment and comparison results show the effectiveness, accuracy, efficiency, and robustness of the proposed approach for online capacity estimation of lithium-ion batteries.

  20. Determining Readability: How to Select and Apply Easy-to-Use Readability Formulas to Assess the Difficulty of Adult Literacy Materials

    Science.gov (United States)

    Burke, Victoria; Greenberg, Daphne

    2010-01-01

    There are many readability tools that instructors can use to help adult learners select reading materials. We describe and compare different types of readability tools: formulas calculated by hand, tools found on the Web, tools embedded in a word processing program, and readability tools found in a commercial software program. Practitioners do not…

  1. HyFlex EDM: superficial features, metallurgical analysis and fatigue resistance of innovative electro discharge machined NiTi rotary instruments.

    Science.gov (United States)

    Pirani, C; Iacono, F; Generali, L; Sassatelli, P; Nucci, C; Lusvarghi, L; Gandolfi, M G; Prati, C

    2016-05-01

    To evaluate the surface and microstructural alterations of new and used HyFlex EDM prototypes and to test their fatigue resistance. Fifteen HyFlex EDM prototypes were used for in vitro instrumentation of severely curved root canals. Surface and microstructural characteristics of new and used files were compared by ESEM analysis equipped with energy dispersive X-ray spectrophotometry (EDS) and optical metallographic imaging. Usage-induced degradation was assessed. Thirty additional HyFlex EDM prototypes and 20 standard manufactured HyFlex CM files were subjected to cyclic fatigue tests. Time to fracture was recorded, and results were validated using the Kruskal-Wallis test (α-level 0.05). Fatigued files were analysed by ESEM for fractographic evaluation. Surface and microstructural characterization of EDM prototypes revealed the typical spark-machined surface of a NiTi EDM alloy. No fractures were registered during root canal instrumentation. No evident surface alterations and minor degradation were observed between new and used instruments. The metallographic analysis of new and used files disclosed a homogeneous structure, mostly composed of lenticular martensite grains, and some residual austenite. The cyclic fatigue test showed an increase of fatigue resistance up to 700% on the EDM compared to CM files. Spark-machined peculiar surface is the main feature of HyFlex EDM. Low degradation was observed after multiple canal instrumentations. Prototypes exhibited surprising high values of cyclic fatigue resistance and a safe in vitro use in severely curved canals. © 2015 International Endodontic Journal. Published by John Wiley & Sons Ltd.

  2. Assessing Online Patient Education Readability for Spine Surgery Procedures.

    Science.gov (United States)

    Long, William W; Modi, Krishna D; Haws, Brittany E; Khechen, Benjamin; Massel, Dustin H; Mayo, Benjamin C; Singh, Kern

    2018-03-01

    Increased patient reliance on Internet-based health information has amplified the need for comprehensible online patient education articles. As suggested by the American Medical Association and National Institute of Health, spine fusion articles should be written for a 4th-6th-grade reading level to increase patient comprehension, which may improve postoperative outcomes. The purpose of this study is to determine the readability of online health care education information relating to anterior cervical discectomy and fusion (ACDF) and lumbar fusion procedures. Online health-education resource qualitative analysis. Three search engines were utilized to access patient education articles for common cervical and lumbar spine procedures. Relevant articles were analyzed for readability using Readability Studio Professional Edition software (Oleander Software Ltd). Articles were stratified by organization type as follows: General Medical Websites (GMW), Healthcare Network/Academic Institutions (HNAI), and Private Practices (PP). Thirteen common readability tests were performed with the mean readability of each compared between subgroups using analysis of variance. ACDF and lumbar fusion articles were determined to have a mean readability of 10.7±1.5 and 11.3±1.6, respectively. GMW, HNAI, and PP subgroups had a mean readability of 10.9±2.9, 10.7±2.8, and 10.7±2.5 for ACDF and 10.9±3.0, 10.8±2.9, and 11.6±2.7 for lumbar fusion articles. Of 310 total articles, only 6 (3 ACDF and 3 lumbar fusion) were written for comprehension below a 7th-grade reading level. Current online literature from medical websites containing information regarding ACDF and lumbar fusion procedures are written at a grade level higher than the suggested guidelines. Therefore, current patient education articles should be revised to accommodate the average reading level in the United States and may result in improved patient comprehension and postoperative outcomes.

  3. Readability of medicinal package leaflets: a systematic review.

    Science.gov (United States)

    Pires, Carla; Vigário, Marina; Cavaco, Afonso

    2015-01-01

    OBJECTIVE To review studies on the readability of package leaflets of medicinal products for human use. METHODS We conducted a systematic literature review between 2008 and 2013 using the keywords "Readability and Package Leaflet" and "Readability and Package Insert" in the academic search engine Biblioteca do Conhecimento Online, comprising different bibliographic resources/databases. The preferred reporting items for systematic reviews and meta-analyses criteria were applied to prepare the draft of the report. Quantitative and qualitative original studies were included. Opinion or review studies not written in English, Portuguese, Italian, French, or Spanish were excluded. RESULTS We identified 202 studies, of which 180 were excluded and 22 were enrolled [two enrolling healthcare professionals, 10 enrolling other type of participants (including patients), three focused on adverse reactions, and 7 descriptive studies]. The package leaflets presented various readability problems, such as complex and difficult to understand texts, small font size, or few illustrations. The main methods to assess the readability of the package leaflet were usability tests or legibility formulae. Limitations with these methods included reduced number of participants; lack of readability formulas specifically validated for specific languages (e.g., Portuguese); and absence of an assessment on patients literacy, health knowledge, cognitive skills, levels of satisfaction, and opinions. CONCLUSIONS Overall, the package leaflets presented various readability problems. In this review, some methodological limitations were identified, including the participation of a limited number of patients and healthcare professionals, the absence of prior assessments of participant literacy, humor or sense of satisfaction, or the predominance of studies not based on role-plays about the use of medicines. These limitations should be avoided in future studies and be considered when interpreting the results.

  4. PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

    Science.gov (United States)

    Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

    2018-04-14

    Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations

  5. Identification of Migratory Insects from their Physical Features using a Decision-Tree Support Vector Machine and its Application to Radar Entomology.

    Science.gov (United States)

    Hu, Cheng; Kong, Shaoyang; Wang, Rui; Long, Teng; Fu, Xiaowei

    2018-04-03

    Migration is a key process in the population dynamics of numerous insect species, including many that are pests or vectors of disease. Identification of insect migrants is critically important to studies of insect migration. Radar is an effective means of monitoring nocturnal insect migrants. However, species identification of migrating insects is often unachievable with current radar technology. Special-purpose entomological radar can measure radar cross-sections (RCSs) from which the insect mass, wingbeat frequency and body length-to-width ratio (a measure of morphological form) can be estimated. These features may be valuable for species identification. This paper explores the identification of insect migrants based on the mass, wingbeat frequency and length-to-width ratio, and body length is also introduced to assess the benefit of adding another variable. A total of 23 species of migratory insects captured by a searchlight trap are used to develop a classification model based on decision-tree support vector machine method. The results reveal that the identification accuracy exceeds 80% for all species if the mass, wingbeat frequency and length-to-width ratio are utilized, and the addition of body length is shown to further increase accuracy. It is also shown that improving the precision of the measurements leads to increased identification accuracy.

  6. A new model of flavonoids affinity towards P-glycoprotein: genetic algorithm-support vector machine with features selected by a modified particle swarm optimization algorithm.

    Science.gov (United States)

    Cui, Ying; Chen, Qinggang; Li, Yaxiao; Tang, Ling

    2017-02-01

    Flavonoids exhibit a high affinity for the purified cytosolic NBD (C-terminal nucleotide-binding domain) of P-glycoprotein (P-gp). To explore the affinity of flavonoids for P-gp, quantitative structure-activity relationship (QSAR) models were developed using support vector machines (SVMs). A novel method coupling a modified particle swarm optimization algorithm with random mutation strategy and a genetic algorithm coupled with SVM was proposed to simultaneously optimize the kernel parameters of SVM and determine the subset of optimized features for the first time. Using DRAGON descriptors to represent compounds for QSAR, three subsets (training, prediction and external validation set) derived from the dataset were employed to investigate QSAR. With excluding of the outlier, the correlation coefficient (R 2 ) of the whole training set (training and prediction) was 0.924, and the R 2 of the external validation set was 0.941. The root-mean-square error (RMSE) of the whole training set was 0.0588; the RMSE of the cross-validation of the external validation set was 0.0443. The mean Q 2 value of leave-many-out cross-validation was 0.824. With more informations from results of randomization analysis and applicability domain, the proposed model is of good predictive ability, stability.

  7. Assessing readability of patient education materials: current role in orthopaedics.

    Science.gov (United States)

    Badarudeen, Sameer; Sabharwal, Sanjeev

    2010-10-01

    Health literacy is the single best predictor of an individual's health status. It is important to customize health-related education material to the individual patient's level of reading skills. Readability of a given text is the objective measurement of the reading skills one should possess to understand the written material. In this article, some of the commonly used readability assessment tools are discussed and guidelines to improve the comprehension of patient education handouts are provided. Where are we now? Several healthcare organizations have recommended the readability of patient education materials be no higher than sixth- to eighth-grade level. However, most of the patient education materials currently available on major orthopaedic Web sites are written at a reading level that may be too advanced for comprehension by a substantial proportion of the population. WHERE DO WE NEED TO GO?: There are several readily available and validated tools for assessing the readability of written materials. While use of audiovisual aids such as video clips, line drawings, models, and charts can enhance the comprehension of a health-related topic, standard readability tools cannot construe such enhancements. HOW DO WE GET THERE?: Given the variability in the capacity to comprehend health-related materials among individuals seeking orthopaedic care, stratifying the contents of patient education materials at different levels of complexity will likely improve health literacy and enhance patient-centered communication.

  8. Readability of Orthopedic Trauma Patient Education Materials on the Internet.

    Science.gov (United States)

    Mohan, Rohith; Yi, Paul H; Morshed, Saam

    In this study, we used the Flesch-Kincaid Readability Scale to determine the readability levels of orthopedic trauma patient education materials on the American Academy of Orthopaedic Surgeons (AAOS) website and to examine how subspecialty coauthorship affects readability level. Included articles from the AAOS online patient education library and the AAOS OrthoPortal website were categorized as trauma or broken bones and injuries on the AAOS online library or were screened by study authors for relevance to orthopedic trauma. Subsequently, the Flesch-Kincaid scale was used to determine each article's readability level, which was reported as a grade level. Subspecialty coauthorship was noted for each article. A total of 115 articles from the AAOS website were included in the study and reviewed. Mean reading level was grade 9.1 for all articles reviewed. Nineteen articles (16.5%) were found to be at or below the eighth-grade level, and only 1 article was at or below the sixth-grade level. In addition, there was no statistically significant difference between articles coauthored by the various orthopedic subspecialties and those authored exclusively by AAOS. Orthopedic trauma readability materials on the AAOS website appear to be written at a reading comprehension level too high for the average patient to understand.

  9. Optical security features for plastic card documents

    Science.gov (United States)

    Hossick Schott, Joachim

    1998-04-01

    Print-on-demand is currently a major trend in the production of paper based documents. This fully digital production philosophy will likely have ramifications also for the secure identification document market. Here, plastic cards increasingly replace traditionally paper based security sensitive documents such as drivers licenses and passports. The information content of plastic cards can be made highly secure by using chip cards. However, printed and other optical security features will continue to play an important role, both for machine readable and visual inspection. Therefore, on-demand high resolution print technologies, laser engraving, luminescent pigments and laminated features such as holograms, kinegrams or phase gratings will have to be considered for the production of secure identification documents. Very important are also basic optical, surface and material durability properties of the laminates as well as the strength and nature of the adhesion between the layers. This presentation will address some of the specific problems encountered when optical security features such as high resolution printing and laser engraving are to be integrated in the on-demand production of secure plastic card identification documents.

  10. Machine medical ethics

    CERN Document Server

    Pontier, Matthijs

    2015-01-01

    The essays in this book, written by researchers from both humanities and sciences, describe various theoretical and experimental approaches to adding medical ethics to a machine in medical settings. Medical machines are in close proximity with human beings, and getting closer: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old, and with medical professionals. In such contexts, machines are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity, and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for e...

  11. Readability of Online Sources Regarding Meniscal Tears.

    Science.gov (United States)

    Hodax, Jonathan D; Baird, Grayson L; McBride, Trevor; Owens, Brett D

    2017-09-01

    Meniscal injuries are extremely common, with an incidence of 8.3 per 1,000 person/years in young, active individuals. Patients often turn to the internet to glean information about their injuries, and even to guide decision making about treatment. Much research has been done demonstrating that a reading level of eighth grade or lower is appropriate for accurately communicating written information to patients, yet medical practitioners often fail to meet this requirement. To better examine the information patients receive about meniscal injuries, we set out to evaluate the reading level and content of three commonly used search terms on the three search engines with the largest market share. The authors examined the keywords "meniscus tear," "meniscus tear treatment," and "knee pain meniscus" on the three highest market share search engines. The top 10 results from each search were included, and redundancies identified. Unique Web sites were evaluated for source, word count, reading level, and content including advertisements, diagrams, photographs, nonoperative and operative options, and accurate medical information. A total of 23 unique Web sites were identified in our search, including 13 public education sources, 6 academic institutions, and 4 private physicians/groups. Average grade levels of articles ranged from 9.4 to 14.2 (mean, 11.14; standard deviation [SD] 1.46), and Flesch-Kincaid reading ease scores ranged from 23.9 to 68.7 (mean, 55.31; SD, 10.11). Pages from public sources required the highest level of readability (11.6, 95% confidence interval [CI]: 9.8-13.2), which was significantly higher than private (11.0, 95% CI: 9.3, 12.7]) and academic (10.9, 95% CI: 8.9-12.9), p  = 0.007 and p  = 0.002, respectively. Further efforts to make appropriate health information available to patients are needed. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  12. The readability and suitability of sexual health promotion leaflets.

    Science.gov (United States)

    Corcoran, Nova; Ahmad, Fatuma

    2016-02-01

    To investigate the readability and suitability of sexual health promotion leaflets. Application of SMOG, FRY and SAM tests to assess the readability and suitability of a selection of sexual health leaflets. SMOG and FRY scores illustrate an average reading level of grade 9. SAM scores indicate that 59% of leaflets are superior in design and 41% are average in design. Leaflets generally perform well in the categories of content, literacy demand, typography and layout. They perform poorly in use of graphics, learning stimulation/motivation and cultural appropriateness. Sexual health leaflets have a reading level that is too high. Leaflets perform well on the suitability scores indicating they are reasonably suitable. There are a number of areas where sexual health leaflets could improve their design. Numerous practical techniques are suggested for improving the readability and suitability of sexual health leaflets. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  13. Readability of patient information and consent documents in rheumatological studies

    DEFF Research Database (Denmark)

    Hamnes, Bente; van Eijk-Hustings, Yvonne; Primdahl, Jette

    2016-01-01

    BACKGROUND: Before participation in medical research an informed consent must be obtained. This study investigates whether the readability of patient information and consent documents (PICDs) corresponds to the average educational level of participants in rheumatological studies in the Netherlands......, Denmark, and Norway. METHODS: 24 PICDs from studies were collected and readability was assessed independently using the Gunning's Fog Index (FOG) and Simple Measure of Gobbledygook (SMOG) grading. RESULTS: The mean score for the FOG and SMOG grades were 14.2 (9.0-19.0) and 14.2 (12-17) respectively....... The mean FOG and SMOG grades were 12.7 and 13.3 in the Dutch studies, 15.0 and 14.9 in the Danish studies, and 14.6 and 14.3 in the Norwegian studies, respectively. Out of the 2865 participants, more than 57 % had a lower educational level than the highest readability score calculated in the individual...

  14. Initial Readability Assessment of Clinical Trial Eligibility Criteria

    Science.gov (United States)

    Kang, Tian; Elhadad, Noémie; Weng, Chunhua

    2015-01-01

    Various search engines are available to clinical trial seekers. However, it remains unknown how comprehensible clinical trial eligibility criteria used for recruitment are to a lay audience. This study initially investigated this problem. Readability of eligibility criteria was assessed according to (i) shallow and lexical characteristics through the use of an established, generic readability metric; (ii) syntactic characteristics through natural language processing techniques; and (iii) health terminological characteristics through an automated comparison to technical and lay health texts. We further stratified clinical trials according to various study characteristics (e.g., source country or study type) to understand potential factors influencing readability. Mainly caused by frequent use of technical jargons, a college reading level was found to be necessary to understand eligibility criteria text, a level much higher than the average literacy level of the general American population. The use of technical jargons should be minimized to simplify eligibility criteria text. PMID:26958204

  15. Readability Assessment of Patient Information about Lymphedema and Its Treatment.

    Science.gov (United States)

    Seth, Akhil K; Vargas, Christina R; Chuang, Danielle J; Lee, Bernard T

    2016-02-01

    Patient use of online resources for health information is increasing, and access to appropriately written information has been associated with improved patient satisfaction and overall outcomes. The American Medical Association and the National Institutes of Health recommend that patient materials be written at a sixth-grade reading level. In this study, the authors simulated a patient search of online educational content for lymphedema and evaluated readability. An online search for the term "lymphedema" was performed, and the first 12 hits were identified. User and location filters were disabled and sponsored results were excluded. Patient information from each site was downloaded and formatted into plain text. Readability was assessed using established tests: Coleman-Liau, Flesch-Kincaid, Flesch Reading Ease Index, FORCAST Readability Formula, Fry Graph, Gunning Fog Index, New Dale-Chall Formula, New Fog Count, Raygor Readability Estimate, and Simple Measure of Gobbledygook Readability Formula. There were 152 patient articles downloaded; the overall mean reading level was 12.6. Individual website reading levels ranged from 9.4 (cancer.org) to 16.7 (wikipedia.org). There were 36 articles dedicated to conservative treatments for lymphedema; surgical treatment was mentioned in nine articles across four sites. The average reading level for conservative management was 12.7, compared with 15.6 for surgery (p readability, and surgeons should direct patients to sites appropriate for their level. There is limited information about surgical treatment available on the most popular sites; this information is significantly harder to read than sections on conservative measures.

  16. Readability assessment of internet-based consumer health information.

    Science.gov (United States)

    Walsh, Tiffany M; Volsko, Teresa A

    2008-10-01

    A substantial amount of consumer health-related information is available on the Internet. Studies suggest that consumer comprehension may be compromised if content exceeds a 7th-grade reading level, which is the average American reading level identified by the United States Department of Health and Human Services (USDHHS). To determine the readability of Internet-based consumer health information offered by organizations that represent the top 5 medical-related causes of death in America. We hypothesized that the average readability (reading grade level) of Internet-based consumer health information on heart disease, cancer, stroke, chronic obstructive pulmonary disease, and diabetes would exceed the USDHHS recommended reading level. From the Web sites of the American Heart Association, American Cancer Society, American Lung Association, American Diabetes Association, and American Stroke Association we randomly gathered 100 consumer-health-information articles. We assessed each article with 3 readability-assessment tools: SMOG (Simple Measure of Gobbledygook), Gunning FOG (Frequency of Gobbledygook), and Flesch-Kincaid Grade Level. We also categorized the articles per the USDHHS readability categories: easy to read (below 6th-grade level), average difficulty (7th to 9th grade level), and difficult (above 9th-grade level). Most of the articles exceeded the 7th-grade reading level and were in the USDHHS "difficult" category. The mean +/- SD readability score ranges were: SMOG 11.80 +/- 2.44 to 14.40 +/- 1.47, Flesch-Kincaid 9.85 +/- 2.25 to 11.55 +/- 0.76, and Gunning FOG 13.10 +/- 3.42 to 16.05 +/- 2.31. The articles from the American Lung Association had the lowest reading-level scores with each of the readability-assessment tools. Our findings support that Web-based medical information intended for consumer use is written above USDHHS recommended reading levels. Compliance with these recommendations may increase the likelihood of consumer comprehension.

  17. The readability of scientific texts is decreasing over time

    Science.gov (United States)

    2017-01-01

    Clarity and accuracy of reporting are fundamental to the scientific process. Readability formulas can estimate how difficult a text is to read. Here, in a corpus consisting of 709,577 abstracts published between 1881 and 2015 from 123 scientific journals, we show that the readability of science is steadily decreasing. Our analyses show that this trend is indicative of a growing use of general scientific jargon. These results are concerning for scientists and for the wider public, as they impact both the reproducibility and accessibility of research findings. PMID:28873054

  18. A readability comparison of anti- versus pro-influenza vaccination online messages in Japan

    Directory of Open Access Journals (Sweden)

    Tsuyoshi Okuhara

    2017-06-01

    When health professionals prepare pro-influenza vaccination materials for publication online, we recommend they check for readability using readability assessment tools and improve the text for easy reading if necessary.

  19. Gaze strategies can reveal the impact of source code features on the cognitive load of novice programmers

    DEFF Research Database (Denmark)

    Wulff-Jensen, Andreas; Ruder, Kevin Vignola; Triantafyllou, Evangelia

    2018-01-01

    As shown by several studies, programmers’ readability of source code is influenced by its structural and the textual features. In order to assess the importance of these features, we conducted an eye-tracking experiment with programming students. To assess the readability and comprehensibility of...

  20. Readability, content, and quality of online patient education materials on preeclampsia.

    Science.gov (United States)

    Lange, Elizabeth M S; Shah, Anuj M; Braithwaite, Brian A; You, Whitney B; Wong, Cynthia A; Grobman, William A; Toledo, Paloma

    2015-01-01

    The objective of this study was to evaluate the readability, content, and quality of patient education materials addressing preeclampsia. Websites of U.S. obstetrics and gynecology residency programs were searched for patient education materials. Readability, content, and quality were assessed. A one-sample t-test was used to evaluate mean readability level compared with the recommended 6th grade reading level. Mean readability levels were higher using all indices (p education materials should be improved.

  1. [Application of support vector machine-recursive feature elimination algorithm in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases].

    Science.gov (United States)

    Zhang, Haipeng; Fu, Tong; Zhang, Zhiru; Fan, Zhimin; Zheng, Chao; Han, Bing

    2014-08-01

    To explore the value of application of support vector machine-recursive feature elimination (SVM-RFE) method in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases. Fresh breast tissue samples of 168 patients (all female; ages 22-75) were obtained by routine surgical resection from May 2011 to May 2012 at the Department of Breast Surgery, the First Hospital of Jilin University. Among them, there were 51 normal tissues, 66 benign and 51 malignant breast lesions. All the specimens were assessed by Raman spectroscopy, and the SVM-RFE algorithm was used to process the data and build the mathematical model. Mahalanobis distance and spectral residuals were used as discriminating criteria to evaluate this data-processing method. 1 800 Raman spectra were acquired from the fresh samples of human breast tissues. Based on spectral profiles, the presence of 1 078, 1 267, 1 301, 1 437, 1 653, and 1 743 cm(-1) peaks were identified in the normal tissues; and 1 281, 1 341, 1 381, 1 417, 1 465, 1 530, and 1 637 cm(-1) peaks were found in the benign and malignant tissues. The main characteristic peaks differentiating benign and malignant lesions were 1 340 and 1 480 cm(-1). The accuracy of SVM-RFE in discriminating normal and malignant lesions was 100.0%, while that in the assessment of benign lesions was 93.0%. There are distinct differences among the Raman spectra of normal, benign and malignant breast tissues, and SVM-RFE method can be used to build differentiation model of breast lesions.

  2. Using Readability Tests to Improve the Accuracy of Evaluation Documents Intended for Low-Literate Participants

    Science.gov (United States)

    Kouame, Julien B.

    2010-01-01

    Background: Readability tests are indicators that measure how easy a document can be read and understood. Simple, but very often ignored, readability statistics cannot only provide information about the level of difficulty of the readability of particular documents but also can increase an evaluator's credibility. Purpose: The purpose of this…

  3. Contents and readability of currently used surgical/ procedure ...

    African Journals Online (AJOL)

    Conclusion: The content of majority of the informed consent forms used in Nigerian tertiary health institutions are poor and their readability scores are not better than those used in developed parts of the world. Health Institutions in Nigeria should revise their informed consent forms to improve their contents and do a usability ...

  4. Readability of Healthcare Literature for Hepatitis B and C.

    Science.gov (United States)

    Meillier, Andrew; Patel, Shyam; Al-Osaimi, Abdullah M S

    2015-12-01

    Patients increasingly use the Internet for educational material concerning health and diseases. This information can be utilized to teach the population of hepatitis B and C if properly written at the necessary grade level of the intended patient population. We explored the readability of online resources concerning hepatitis B and C. Google searches were performed for "Hepatitis B" and "Hepatitis C." The Internet resources that were intended for patient education were used with specific exclusions. Articles were taken from 19 and 23 different websites focusing on the symptoms, diagnosis, and treatment of hepatitis B and C, respectively. The articles were analyzed using Readability Studio Professional Edition (Oleander Solutions, Vandalia, OH) using 10 different readability scales. The results were compared and averaged to identify the anticipated academic grade level required to understand the information. The average readability scores of the 10 scales had ranges of 9.7-16.4 for hepatitis B and 9.2-16.4 for hepatitis C. The average academic reading grade level for hepatitis B was 12.6 ± 2.1 and for hepatitis C was 12.7 ± 2.1. There was no significant discrepancy between the hepatitis B and C Internet resource averaged grade levels. The resources accessed by patients are higher than the previously determined necessary grade level for patients to properly understand the intended information. The American Medical Association recommends material should be simplified to grade levels below the sixth grade level to benefit the ideal proportion of the patient population.

  5. Readability of Internet Information on Hearing: Systematic Literature Review.

    Science.gov (United States)

    Laplante-Lévesque, Ariane; Thorén, Elisabet Sundewall

    2015-09-01

    This systematic literature review asks the following question: “ What is the readability of Internet information on hearing that people with hearing impairment and their significant others can access in the context of their hearing care?” Searches were completed in three databases: CINAHL, PubMed, and Scopus. Seventy-eight records were identified and systematically screened for eligibility: 8 records were included that contained data on the readability of Internet information on hearing that people with hear ing impairment and their significant others can access in the context of their hearing care. Records reported mean readability levels from 9 to over 14. In other words, people with hearing impairment and their significant others need 9 to 14 years of education to read and understand Internet information on hearing that they access in the context of their hearing care. The poor readability of Internet information on hearing has been well documented; it is time to focus on valid and sustainable initiatives that address this problem.

  6. Sense and readability: participant information sheets for research studies.

    Science.gov (United States)

    Ennis, Liam; Wykes, Til

    2016-02-01

    Informed consent in research is partly achieved through the use of information sheets. There is a perception however that these information sheets are long and complex. The recommended reading level for patient information is grade 6, or 11-12 years old. To investigate whether the readability of participant information sheets has changed over time, whether particular study characteristics are related to poorer readability and whether readability and other study characteristics are related to successful study recruitment. Method: We obtained 522 information sheets from the UK National Institute for Health Research Clinical Research Network: Mental Health portfolio database and study principal investigators. Readability was assessed with the Flesch reading index and the Grade level test. Information sheets increased in length over the study period. The mean grade level across all information sheets was 9.8, or 15-16 years old. A high level of patient involvement was associated with more recruitment success and studies involving pharmaceutical or device interventions were the least successful. The complexity of information sheets had little bearing on successful recruitment. Information sheets are far more complex than the recommended reading level of grade 6 for patient information. The disparity may be exacerbated by an increasing focus on legal content. Researchers would benefit from clear guidance from ethics committees on writing succinctly and accessibly and how to balance the competing legal issues with the ability of participants to understand what a study entails. © The Royal College of Psychiatrists 2016.

  7. Tools for Assessing Readability of Statistics Teaching Materials

    Science.gov (United States)

    Lesser, Lawrence; Wagler, Amy

    2016-01-01

    This article provides tools and rationale for instructors in math and science to make their assessment and curriculum materials (more) readable for students. The tools discussed (MSWord, LexTutor, Coh-Metrix TEA) are readily available linguistic analysis applications that are grounded in current linguistic theory, but present output that can…

  8. Reassessing the Accuracy and Use of Readability Formulae

    Science.gov (United States)

    Janan, Dahlia; Wray, David

    2014-01-01

    Purpose: The purpose of the study is to review readability formulae and offer a critique, based on a comparison of the grading of a variety of texts given by six well-known formulae. Methodology: A total of 64 texts in English were selected either by or for native English speaking children aged between six and 11 years. Each text was assessed…

  9. Readability of Informed Consent Documents at University Counseling Centers

    Science.gov (United States)

    Lustgarten, Samuel D.; Elchert, Daniel M.; Cederberg, Charles; Garrison, Yunkyoung L.; Ho, Y. C. S.

    2017-01-01

    The extent to which clients understand the nature and anticipated course of therapy is referred to as informed consent. Counseling psychologists often provide informed consent documents to enhance the education of services and for liability purposes. Professionals in numerous health care settings have evaluated the readability of their informed…

  10. Readability of Malaria Medicine Information Leaflets in Nigeria

    African Journals Online (AJOL)

    Erah

    2010-12-18

    Dec 18, 2010 ... for malaria medicines information leaflets available in Nigeria was 13.69 ± 1.70. This value is equivalent ... Health promotion and behaviour change communication ... their rational use at the community level. Readability is the ...

  11. The Readability of Malaysian English Children Books: A Multilevel Analysis

    Directory of Open Access Journals (Sweden)

    Adlina Ismail

    2016-11-01

    Full Text Available These days, there are more English books for children published by local publishers in Malaysia. It is a positive development because the books will be more accessible to the children. However, the books have never been studied and evaluated in depth yet. One important factor in assessing reading materials is readability. Readability determines whether a text is easy or difficult to understand and a balanced mix of both can promote learning and language development. Various researchers mentioned a multilevel framework of discourse that any language assessment on a text should take into account. The levels that were proposed were word, syntax, textbase, situation model and genre and rhetorical structures. Traditional readability measures such as Flesh Reading Ease Formula, Gunning Readability Index, Fog Count, and Fry Grade Level are not able to address the multilevel because they are based on shallow variables. In contrast, Coh-metrix TERA provided five indices that are correlated to grade level and aligned to the multilevel framework. This study analyzed ten Malaysian English chapter books for children using this Coh-metrix TERA. The result revealed that the Malaysian English children books were easy in shallow level but there was a possible difficulty in textbase and situation model level because of the lack of cohesion. In conclusion, more attention should be given on deeper level of text rather than just word and syntax level.

  12. An Analysis of the Readability of Financial Accounting Textbooks.

    Science.gov (United States)

    Smith, Gerald; And Others

    1981-01-01

    The Flesch formula was used to calculate the readability of 15 financial accounting textbooks. The 15 textbooks represented introductory, intermediate, and advanced levels and also were classified by five different publishers. Two-way analysis of variance and Tukey's post hoc analysis revealed some significant differences. (Author/CT)

  13. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  14. The readability of expert reports for non-scientist report-users: reports of forensic comparison of glass.

    Science.gov (United States)

    Howes, Loene M; Kirkbride, K Paul; Kelty, Sally F; Julian, Roberta; Kemp, Nenagh

    2014-03-01

    Scientific language contains features that may impede understanding for non-scientists. Forensic scientists' written reports are read by police, lawyers, and judges, and thus assessment of readability is warranted. Past studies of readability differed in background theory and approach, but analysed one or more of: content and sequence; language; and format. Using a holistic approach, we assessed the readability of expert reports (n=78) of forensic glass comparison from 7 Australian jurisdictions. Two main audiences for reports were relevant: police and the courts. Reports for police were presented either as a completed form or as a brief legal-style report. Reports for court were less brief and used either legal or scientific styles, with content and formatting features supporting these distinctions. Some jurisdictions prepared a single report to satisfy both the courts and police. In general, item list, analytical techniques, results, notes on interpretation, and conclusions were included in reports of all types. However, some reports omitted analytical techniques, and results and conclusions were sometimes combined. According to Flesch Reading Ease, language was difficult, with a Flesch-Kincaid grade level of university undergraduate. Sentences were long and contained undefined specialist terms. Information content per clause (lexical density), was typically high, as for other scientific texts. Uncertainty was expressed differently by jurisdiction. Reports from most jurisdictions were cluttered in appearance, with single-line spacing, narrow margins, and gridlines in tables. Simple suggestions, based on theory and past research, are provided to assist scientists to enhance the readability of expert reports for non-scientists. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. Readability of Online Patient Education Materials Related to IR.

    Science.gov (United States)

    McEnteggart, Gregory E; Naeem, Muhammad; Skierkowski, Dorothy; Baird, Grayson L; Ahn, Sun H; Soares, Gregory

    2015-08-01

    To assess the readability of online patient education materials (OPEM) related to common diseases treated by and procedures performed by interventional radiology (IR). The following websites were chosen based on their average Google search return for each IR OPEM content area examined in this study: Society of Interventional Radiology (SIR), Cardiovascular and Interventional Radiological Society of Europe (CIRSE), National Library of Medicine, RadiologyInfo, Mayo Clinic, WebMD, and Wikipedia. IR OPEM content area was assessed for the following: peripheral arterial disease, central venous catheter, varicocele, uterine artery embolization, vertebroplasty, transjugular intrahepatic portosystemic shunt, and deep vein thrombosis. The following algorithms were used to estimate and compare readability levels: Flesch-Kincaid Grade Formula, Flesch Reading Ease Score, Gunning Frequency of Gobbledygook, Simple Measure of Gobbledygook, and Coleman-Liau Index. Data were analyzed using general mixed modeling. On average, online sources that required beyond high school grade-level readability were Wikipedia (15.0), SIR (14.2), and RadiologyInfo (12.4); sources that required high school grade-level readability were CIRSE (11.3), Mayo Clinic (11.0), WebMD (10.6), and National Library of Medicine (9.0). On average, OPEM on uterine artery embolization, vertebroplasty, varicocele, and peripheral arterial disease required the highest level of readability (12.5, 12.3, 12.3, and 12.2, respectively). The IR OPEM assessed in this study were written above the recommended sixth-grade reading level and the health literacy level of the average American adult. Many patients in the general public may not have the ability to read and understand health information in IR OPEM. Copyright © 2015 SIR. Published by Elsevier Inc. All rights reserved.

  16. Readability analysis of online resources related to lung cancer.

    Science.gov (United States)

    Weiss, Kathleen D; Vargas, Christina R; Ho, Olivia A; Chuang, Danielle J; Weiss, Jonathan; Lee, Bernard T

    2016-11-01

    Patients seeking health information commonly use the Internet as the first source for material. Studies show that well-informed patients have increased involvement, satisfaction, and healthcare outcomes. As one-third of Americans have only basic or below basic health literacy, the National Institutes of Health and American Medical Association recommend patient-directed health resources be written at a sixth-grade reading level. This study evaluates the readability of commonly accessed online resources on lung cancer. A search for "lung cancer" was performed using Google and Bing, and the top 10 websites were identified. Location services were disabled, and sponsored sites were excluded. Relevant articles (n = 109) with patient-directed content available directly from the main sites were downloaded. Readability was assessed using 10 established methods and analyzed with articles grouped by parent website. The average reading grade level across all sites was 11.2, with a range from 8.8 (New Fog Count) to 12.2 (Simple Measure of Gobbledygook). The average Flesch Reading Ease score was 52, corresponding with fairly difficult to read text. The readability varied when compared by individual website, ranging in grade level from 9.2 to 15.2. Only 10 articles (9%) were written below a sixth-grade level and these tended to discuss simpler topics. Patient-directed online information about lung cancer exceeds the recommended sixth-grade reading level. Readability varies between individual websites, allowing physicians to direct patients according to level of health literacy. Modifications to existing materials can significantly improve readability while maintaining content for patients with low health literacy. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. The Readability of Online Resources for Mastopexy Surgery.

    Science.gov (United States)

    Vargas, Christina R; Chuang, Danielle J; Lee, Bernard T

    2016-01-01

    As more patients use Internet resources for health information, there is increasing interest in evaluating the readability of available online materials. The National Institutes of Health and American Medical Association recommend that patient educational content be written at a sixth-grade reading level. This study evaluates the most popular online resources for information about mastopexy relative to average adult literacy in the United States. The 12 most popular sites returned by the largest Internet search engine were identified using the search term "breast lift surgery." Relevant articles from the main sites were downloaded and formatted into text documents. Pictures, captions, links, and references were excluded. The readability of these 100 articles was analyzed overall and subsequently by site using 10 established readability tests. Subgroup analysis was performed for articles discussing the benefits of surgery and those focusing on risks. The overall average readability of online patient information was 13.3 (range, 11.1-15). There was a range of average readability scores overall across the 12 sites from 8.9 to 16.1, suggesting that some may be more appropriate than others for patient demographics with different health literacy levels. Subgroup analysis revealed that articles discussing the risks of mastopexy were significantly harder to read (mean, 14.1) than articles about benefits (11.6). Patient-directed articles from the most popular online resources for mastopexy information are uniformly above the recommended reading level and likely too difficult to be understood by a large number of patients in the United States.

  18. Evaluating the Readability of Radio Frequency Identification for Construction Materials

    Directory of Open Access Journals (Sweden)

    Younghan Jung

    2017-01-01

    Full Text Available Radio Frequency Identification (RFID, which was originally introduced to improve material handling and speed production as part of supply chain management, has become a globally accepted technology that is now applied on many construction sites to facilitate real-time information visibility and traceability. This paper describes a senior undergraduate project for a Construction Management (CM program that was specifically designed to give the students a greater insight into technical research in the CM area. The students were asked to determine whether it would be possible to utilize an RFID system capable of tracking tagged equipment, personnel and materials across an entire construction site. This project required them to set up an experimental program, execute a series of experiments, analyze the results and summarize them in a report. The readability test was performed using an active Ultra-High frequency (UHF, 433.92 MHz RFID system with various construction materials, including metal, concrete, wood, plastic, and aluminum. The readability distance distances are measured for each of the six scenarios. The distance at which a tag was readable with no obstructions was found to be an average of 133.9m based on three measurements, with a standard deviation of 3.9m. This result confirms the manufacturer’s claimed distance of 137.2m. The RFID tag embedded under 50.8mm of concrete was readable for an average distance of only 12.2m, the shortest readable distance of any of the scenarios tested. At the end of the semester, faculty advisors held an open discussion session to gather feedback and elicit the students’ reflections on their research experiences, revealing that the students’ overall impressions of their undergraduate research had positively affected their postgraduate education plans.

  19. Readability and quality of wikipedia pages on neurosurgical topics.

    Science.gov (United States)

    Modiri, Omeed; Guha, Daipayan; Alotaibi, Naif M; Ibrahim, George M; Lipsman, Nir; Fallah, Aria

    2018-03-01

    Wikipedia is the largest online encyclopedia with over 40 million articles, and generating 500 million visits per month. The aim of this study is to assess the readability and quality of Wikipedia pages on neurosurgical related topics. We selected the neurosurgical related Wikipedia pages based on the series of online patient information articles that are published by the American Association of Neurological Surgeons (AANS). We assessed readability of Wikipedia pages using five different readability scales (Flesch Reading Ease, Flesch Kincaid Grade Level, Gunning Fog Index, SMOG) Grade level, and Coleman-Liau Index). We used the Center for Disease Control (CDC) Clear Communication Index as well as the DISCERN Instrument to evaluate the quality of each Wikipedia article. We identified a total of fifty-five Wikipedia articles that corresponded with patient information articles published by the AANS. This constitutes 77.46% of the AANS topics. The mean Flesch Kincaid reading ease score for all of the Wikipedia articles we analyzed is 31.10, which indicates that a college-level education is necessary to understand them. In comparison to the readability analysis for the AANS articles, the Wikipedia articles were more difficult to read across every scale. None of the Wikipedia articles meet the CDC criterion for clear communications. Our analyses demonstrated that Wikipedia articles related to neurosurgical topics are associated with higher grade levels for reading and also below the expected levels of clear communications for patients. Collaborative efforts from the neurosurgical community are needed to enhance the readability and quality of Wikipedia pages related to neurosurgery. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. An asymptotical machine

    Science.gov (United States)

    Cristallini, Achille

    2016-07-01

    A new and intriguing machine may be obtained replacing the moving pulley of a gun tackle with a fixed point in the rope. Its most important feature is the asymptotic efficiency. Here we obtain a satisfactory description of this machine by means of vector calculus and elementary trigonometry. The mathematical model has been compared with experimental data and briefly discussed.

  1. Improving readability of informed consents for research at an academic medical institution.

    Science.gov (United States)

    Hadden, Kristie B; Prince, Latrina Y; Moore, Tina D; James, Laura P; Holland, Jennifer R; Trudeau, Christopher R

    2017-12-01

    The final rule for the protection of human subjects requires that informed consent be "in language understandable to the subject" and mandates that "the informed consent must be organized in such a way that facilitates comprehension." This study assessed the readability of Institutional Review Board-approved informed consent forms at our institution, implemented an intervention to improve the readability of consent forms, and measured the first year impact of the intervention. Readability assessment was conducted on a sample of 217 Institutional Review Board-approved informed consents from 2013 to 2015. A plain language informed consent template was developed and implemented and readability was assessed again after 1 year. The mean readability of the baseline sample was 10th grade. The mean readability of the post-intervention sample (n=82) was seventh grade. Providing investigators with a plain language informed consent template and training can promote improved readability of informed consents for research.

  2. Readability of Online Health Information: A Meta-Narrative Systematic Review.

    Science.gov (United States)

    Daraz, Lubna; Morrow, Allison S; Ponce, Oscar J; Farah, Wigdan; Katabi, Abdulrahman; Majzoub, Abdul; Seisa, Mohamed O; Benkhadra, Raed; Alsawas, Mouaz; Larry, Prokop; Murad, M Hassan

    2018-01-01

    Online health information should meet the reading level for the general public (set at sixth-grade level). Readability is a key requirement for information to be helpful and improve quality of care. The authors conducted a systematic review to evaluate the readability of online health information in the United States and Canada. Out of 3743 references, the authors included 157 cross-sectional studies evaluating 7891 websites using 13 readability scales. The mean readability grade level across websites ranged from grade 10 to 15 based on the different scales. Stratification by specialty, health condition, and type of organization producing information revealed the same findings. In conclusion, online health information in the United States and Canada has a readability level that is inappropriate for general public use. Poor readability can lead to misinformation and may have a detrimental effect on health. Efforts are needed to improve readability and the content of online health information.

  3. Electrical machines & drives

    CERN Document Server

    Hammond, P

    1985-01-01

    Containing approximately 200 problems (100 worked), the text covers a wide range of topics concerning electrical machines, placing particular emphasis upon electrical-machine drive applications. The theory is concisely reviewed and focuses on features common to all machine types. The problems are arranged in order of increasing levels of complexity and discussions of the solutions are included where appropriate to illustrate the engineering implications. This second edition includes an important new chapter on mathematical and computer simulation of machine systems and revised discussions o

  4. Machine Shop Grinding Machines.

    Science.gov (United States)

    Dunn, James

    This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

  5. The quality and readability of internet information regarding clavicle fractures.

    Science.gov (United States)

    Zhang, Dafang; Schumacher, Charles; Harris, Mitchel Byron

    2016-03-01

    The internet has become a major source of health information for patients. However, there has been little scrutiny of health information available on the internet to the public. Our objectives were to evaluate the quality and readability of information available on the internet regarding clavicle fractures and whether they changed with academic affiliation of the website or with complexity of the search term. Through a prospective evaluation of 3 search engines using 3 different search terms of varying complexity ("broken collarbone," "collarbone fracture," and "clavicle fracture"), we evaluated 91 website hits for quality and readability. Websites were specifically analyzed by search term and by website type. Information quality was evaluated on a four-point scale, and information readability was assessed using the Flesch-Kincaid score for reading grade level. The average quality score for our website hits was low, and the average reading grade level was far above the recommended level. Academic websites offered significantly higher quality information, whereas commercial websites offered significantly lower quality information. The use of more complex search terms yielded information of higher reading grade level but not higher quality. Current internet information regarding clavicle fractures is of low quality and low readability. Higher quality information utilizing more accessible language on clavicle fractures is needed on the internet. It is important to be aware of the information accessible to patients prior to their presentation to our clinics. Patients should be advised to visit websites with academic affiliations and to avoid commercial websites. Copyright © 2015 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

  6. Assessing the readability of ClinicalTrials.gov.

    Science.gov (United States)

    Wu, Danny T Y; Hanauer, David A; Mei, Qiaozhu; Clark, Patricia M; An, Lawrence C; Proulx, Joshua; Zeng, Qing T; Vydiswaran, V G Vinod; Collins-Thompson, Kevyn; Zheng, Kai

    2016-03-01

    ClinicalTrials.gov serves critical functions of disseminating trial information to the public and helping the trials recruit participants. This study assessed the readability of trial descriptions at ClinicalTrials.gov using multiple quantitative measures. The analysis included all 165,988 trials registered at ClinicalTrials.gov as of April 30, 2014. To obtain benchmarks, the authors also analyzed 2 other medical corpora: (1) all 955 Health Topics articles from MedlinePlus and (2) a random sample of 100,000 clinician notes retrieved from an electronic health records system intended for conveying internal communication among medical professionals. The authors characterized each of the corpora using 4 surface metrics, and then applied 5 different scoring algorithms to assess their readability. The authors hypothesized that clinician notes would be most difficult to read, followed by trial descriptions and MedlinePlus Health Topics articles. Trial descriptions have the longest average sentence length (26.1 words) across all corpora; 65% of their words used are not covered by a basic medical English dictionary. In comparison, average sentence length of MedlinePlus Health Topics articles is 61% shorter, vocabulary size is 95% smaller, and dictionary coverage is 46% higher. All 5 scoring algorithms consistently rated CliniclTrials.gov trial descriptions the most difficult corpus to read, even harder than clinician notes. On average, it requires 18 years of education to properly understand these trial descriptions according to the results generated by the readability assessment algorithms. Trial descriptions at CliniclTrials.gov are extremely difficult to read. Significant work is warranted to improve their readability in order to achieve CliniclTrials.gov's goal of facilitating information dissemination and subject recruitment. Published by Oxford University Press on behalf of the American Medical Informatics Association 2015. This work is written by US Government

  7. Online Patient Resources for Liposuction: A Comparative Analysis of Readability.

    Science.gov (United States)

    Vargas, Christina R; Ricci, Joseph A; Chuang, Danielle J; Lee, Bernard T

    2016-03-01

    As patients strive to become informed about health care, inadequate functional health literacy is a significant barrier. Nearly half of American adults have poor or marginal health literacy skills and the National Institutes of Health and American Medical Association have recommended that patient information should be written at a sixth grade level. The aim of this study is to identify the most commonly used online patient information about liposuction and to evaluate its readability relative to average American literacy. An internet search of "liposuction" was performed and the 10 most popular websites identified. User and location data were disabled and sponsored results excluded. All relevant, patient-directed articles were downloaded and formatted into plain text. Articles were then analyzed using 10 established readability tests. A comparison group was constructed to identify the most popular online consumer information about tattooing. Mean readability scores and specific article characteristics were compared. A total of 80 articles were collected from websites about liposuction. Readability analysis revealed an overall 13.6 grade reading level (range, 10-16 grade); all articles exceeded the target sixth grade level. Consumer websites about tattooing were significantly easier to read, with a mean 7.8 grade level. These sites contained significantly fewer characters per word and words per sentence, as well as a smaller proportion of complex, long, and unfamiliar words. Online patient resources about liposuction are potentially too difficult for a large number of Americans to understand. Liposuction websites are significantly harder to read than consumer websites about tattooing. Aesthetic surgeons are advised to discuss with patients resources they use and guide patients to appropriate information for their skill level.

  8. Reliability, Readability and Quality of Online Information about Femoracetabular Impingement

    Directory of Open Access Journals (Sweden)

    Fatih Küçükdurmaz

    2015-07-01

    Conclusion: According to our results, the websites intended to attract patients searching for information regarding femoroacetabular impingement are providing a highly accessible, readable information source, but do not appear to apply a comparable amount of rigor to scientific literature or healthcare practitioner websites in regard to matters such as citing sources for information, supplying methodology and including a publication date. This indicates that while these resources are easily accessed by patients, there is potential for them to be a source of misinformation.

  9. Development of Correlations for Windage Power Losses Modeling in an Axial Flux Permanent Magnet Synchronous Machine with Geometrical Features of the Magnets

    Directory of Open Access Journals (Sweden)

    Alireza Rasekh

    2016-11-01

    Full Text Available In this paper, a set of correlations for the windage power losses in a 4 kW axial flux permanent magnet synchronous machine (AFPMSM is presented. In order to have an efficient machine, it is necessary to optimize the total electromagnetic and mechanical losses. Therefore, fast equations are needed to estimate the windage power losses of the machine. The geometry consists of an open rotor–stator with sixteen magnets at the periphery of the rotor with an annular opening in the entire disk. Air can flow in a channel being formed between the magnets and in a small gap region between the magnets and the stator surface. To construct the correlations, computational fluid dynamics (CFD simulations through the frozen rotor (FR method are performed at the practical ranges of the geometrical parameters, namely the gap size distance, the rotational speed of the rotor, the magnet thickness and the magnet angle. Thereafter, two categories of formulations are defined to make the windage losses dimensionless based on whether the losses are mainly due to the viscous forces or the pressure forces. At the end, the correlations can be achieved via curve fittings from the numerical data. The results reveal that the pressure forces are responsible for the windage losses for the side surfaces in the air-channel, whereas for the surfaces facing the stator surface in the gap, the viscous forces mainly contribute to the windage losses. Additionally, the results of the parametric study demonstrate that the overall windage losses in the machine escalate with an increase in either the rotational Reynolds number or the magnet thickness ratio. By contrast, the windage losses decrease once the magnet angle ratio enlarges. Moreover, it can be concluded that the proposed correlations are very useful tools in the design and optimizations of this type of electrical machine.

  10. Readability assessment of online thyroid surgery patient education materials.

    Science.gov (United States)

    Patel, Chirag R; Cherla, Deepa V; Sanghvi, Saurin; Baredes, Soly; Eloy, Jean Anderson

    2013-10-01

    Published guidelines recommend written health information be written at or below the sixth-grade level. We evaluate the readability of online materials related to thyroid surgery. Thyroid surgery materials were evaluated using Flesch Reading Ease Score (FRES), Flesch Kincaid Grade Level (FKGL), Gunning Frequency of Gobbledygook (GFOG), and Simple Measure of Gobbledygook (SMOG). Thirty-one documents were evaluated. FRES scores ranged from 29.3 to 67.8 (possible range = 0 to 100), and averaged 50.5. FKGL ranged from 6.9 to 14.9 (possible range = 3 to 12), and averaged 10.4. SMOG scores ranged from 11.8 to 14.5 (possible range = 3 to 19), and averaged 13.0. GFOG scores ranged from 10.6 to 18.0 (possible range = 3 to 19), and averaged 13.5. Readability scores for online thyroid surgery materials are higher (i.e., more difficult) than the recommended levels. However, readability is only one aspect of comprehension. Written information should be designed with that fact in mind. Copyright © 2013 Wiley Periodicals, Inc.

  11. Readability of informed consent forms in vascular and interventional radiology

    International Nuclear Information System (INIS)

    Pinto, I.; Vigil, D.

    1998-01-01

    To evaluate the readability of the informed consent forms prepared for vascular and interventional radiology. The 18 informed consent forms were analyzed using the Gramatica tool employed in Microsoft Word 97 For Windows which combines the statistics on legibility in terms of three sections: scores, averages and legibility (Flech index, passive voice, sentence complexity and vocabulary complexity). For each, the integrated readability index was also manually calculated. All the documents present a Flesch index of over 10; the sentence complexity indexes are less than or equal to 20, demonstrating that the sentences are not long or complicated in structure. Finally, the integrated readability index of all of them is well over 70. The forms posses acceptable legibility indexes, but their evaluation should be completed by an opinion poll of the patients for whom they are written. Moreover, it must be kept in mind that these documents, like the procedures performed, are changing continually. Thus, it is necessary to update and modify the information to be provided to the patients. (Author) 11 refs

  12. Quality and readability of online information resources on insomnia

    Institute of Scientific and Technical Information of China (English)

    Yan Ma; Albert C.Yang; Ying Duan; Ming Dong; Albert S.Yeung

    2017-01-01

    The internet is a major source for health information.An increasing number of people,including patients with insomnia,search for remedies online;however,little is known about the quality of such information.This study aimed to evaluate the quality and readability of insomnia-related online information.Google was used as the search engine,and the top websites on insomnia that met the inclusion criteria were evaluated for quality and readability.The analyzed websites belonged to nonprofit,commercial,or academic organizations and institutions such as hospitais and universities.Insomnia-related websites typically included definitions (85%),causes and risk factors (100%),symptoms (95%),and treatment options (90%).Cognitive behavioral therapy for insomnia (CBT-Ⅰ) was the most commonly recommended approach for insomnia treatment,and sleep drugs are frequently mentioned.The overall quality of the websites on insomnia is moderate,but all the content exceeded the recommended reading ease levels.Concerns that must be addressed to increase the quality and trustworthiness of online health information include sharing metadata,such as authorship,time of creation and last update,and conflicts of interest;providing evidence for reliability;and increasing the readability for a layman audience.

  13. Readability assessment of online urology patient education materials.

    Science.gov (United States)

    Colaco, Marc; Svider, Peter F; Agarwal, Nitin; Eloy, Jean Anderson; Jackson, Imani M

    2013-03-01

    The National Institutes of Health, American Medical Association, and United States Department of Health and Human Services recommend that patient education materials be written at a fourth to sixth grade reading level to facilitate comprehension. We examined and compared the readability and difficulty of online patient education materials from the American Urological Association and academic urology departments in the Northeastern United States. We assessed the online patient education materials for difficulty level with 10 commonly used readability assessment tools, including the Flesch Reading Ease Score, Flesch-Kincaid Grade Level, Simple Measure of Gobbledygook, Gunning Frequency of Gobbledygook, New Dale-Chall Test, Coleman-Liau index, New Fog Count, Raygor Readability Estimate, FORCAST test and Fry score. Most patient education materials on the websites of these programs were written at or above the eleventh grade reading level. Urological online patient education materials are written above the recommended reading level. They may need to be simplified to facilitate better patient understanding of urological topics. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  14. A level set methodology for predicting the effect of mask wear on surface evolution of features in abrasive jet micro-machining

    International Nuclear Information System (INIS)

    Burzynski, T; Papini, M

    2012-01-01

    A previous implementation of narrow-band level set methodology developed by the authors was extended to allow for the modelling of mask erosive wear in abrasive jet micro-machining (AJM). The model permits the prediction of the surface evolution of both the mask and the target simultaneously, by representing them as a hybrid and continuous mask–target surface. The model also accounts for the change in abrasive mass flux incident to both the target surface and, for the first time, the eroding mask edge, that is brought about by the presence of the mask edge itself. The predictions of the channel surface and eroded mask profiles were compared with measurements on channels machined in both glass and poly-methyl-methacrylate (PMMA) targets at both normal and oblique incidence, using tempered steel and elastomeric masks. A much better agreement between the predicted and measured profiles was found when mask wear was taken into account. Mask wear generally resulted in wider and deeper glass target profiles and wider PMMA target profiles, respectively, when compared to cases where no mask wear was present. This work has important implications for the AJM of complex MEMS and microfluidic devices that require longer machining times. (paper)

  15. Readability in reading materials selection and coursebook design for college English in China

    OpenAIRE

    Lu, Zhongshe

    2002-01-01

    This thesis studies the application of readability in reading materials selection and coursebook design for college English in an EFL context in China. Its aim is to develop rationales which coursebook writers can utilise in selecting materials as texts and as a basis for designing tasks. This study, through a combination of quantitative and qualitative research methods, argues that readability is applicable in the EFL Chinese context, and readability plays a important role in determining...

  16. Pylinguistics: an open source library for readability assessment of texts written in Portuguese

    Directory of Open Access Journals (Sweden)

    Castilhos, S.

    2016-12-01

    Full Text Available Readability assessment is an important task in automatic text simplification that aims identify the text complexity by computing a set of metrics. In this paper, we present the development and assessment of an open source library called Pylinguistics to readability assessment of texts written in Portuguese. Additionally, to illustrate the possibilities of our tool, this work also presents an empirical analysis of readability of Brazilian scientific news dissemination.

  17. Calisthenics with words: The effect of readability and investor sophistication on investors' performance judgment

    OpenAIRE

    Cui, Xiao Carol

    2016-01-01

    Since the 1990s, the SEC has advocated for financial disclosures to be in “plain English” so that they would be more readable and informative. Past research has shown that high readability is related to more extreme investor judgments of firm performance. Processing fluency is the prevalent theory to explain this: higher readability increases the investor’s subconscious reliance on the disclosure, so positive (negative) news leads to more positive (negative) judgments. The relationship may no...

  18. Readability of the written study information in pediatric research in France.

    Directory of Open Access Journals (Sweden)

    Véronique Ménoni

    Full Text Available BACKGROUND: The aim was to evaluate the readability of research information leaflets (RIL for minors asked to participate in biomedical research studies and to assess the factors influencing this readability. METHODS AND FINDINGS: All the pediatric protocols from three French pediatric clinical research units were included (N = 104. Three criteria were used to evaluate readability: length of the text, Flesch's readability score and presence of illustrations. We compared the readability of RIL to texts specifically written for children (school textbooks, school exams or extracts from literary works. We assessed the effect of protocol characteristics on readability. The RIL had a median length of 608 words [350 words, 25(th percentile; 1005 words, 75(th percentile], corresponding to two pages. The readability of the RIL, with a median Flesch score of 40 [30; 47], was much poorer than that of pediatric reference texts, with a Flesch score of 67 [60; 73]. A small proportion of RIL (13/91; 14% were illustrated. The RIL were longer (p<0.001, more readable (p<0.001 and more likely to be illustrated (p<0.009 for industrial than for institutional sponsors. CONCLUSION: Researchers should routinely compute the reading ease of study information sheets and make greater efforts to improve the readability of written documents for potential participants.

  19. Introduction to machine learning.

    Science.gov (United States)

    Baştanlar, Yalin; Ozuysal, Mustafa

    2014-01-01

    The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity and processing power of computers. Together with many other disciplines, machine learning methods have been widely employed in bioinformatics. The difficulties and cost of biological analyses have led to the development of sophisticated machine learning approaches for this application area. In this chapter, we first review the fundamental concepts of machine learning such as feature assessment, unsupervised versus supervised learning and types of classification. Then, we point out the main issues of designing machine learning experiments and their performance evaluation. Finally, we introduce some supervised learning methods.

  20. Superconducting machines. Chapter 4

    International Nuclear Information System (INIS)

    Appleton, A.D.

    1977-01-01

    A brief account is given of the principles of superconductivity and superconductors. The properties of Nb-Ti superconductors and the method of flux stabilization are described. The basic features of superconducting d.c. machines are illustrated by the use of these machines for ship propulsion, steel-mill drives, industrial drives, aluminium production, and other d.c. power supplies. Superconducting a.c. generators and their design parameters are discussed. (U.K.)

  1. Readability of Written Materials for CKD Patients: A Systematic Review.

    Science.gov (United States)

    Morony, Suzanne; Flynn, Michaela; McCaffery, Kirsten J; Jansen, Jesse; Webster, Angela C

    2015-06-01

    The "average" patient has a literacy level of US grade 8 (age 13-14 years), but this may be lower for people with chronic kidney disease (CKD). Current guidelines suggest that patient education materials should be pitched at a literacy level of around 5th grade (age 10-11 years). This study aims to evaluate the readability of written materials targeted at patients with CKD. Systematic review. Patient information materials aimed at adults with CKD and written in English. Patient education materials designed to be printed and read, sourced from practices in Australia and online at all known websites run by relevant international CKD organizations during March 2014. Quantitative analysis of readability using Lexile Analyzer and Flesch-Kincaid tools. We analyzed 80 materials. Both Lexile Analyzer and Flesch-Kincaid analyses suggested that most materials required a minimum of grade 9 (age 14-15 years) schooling to read them. Only 5% of materials were pitched at the recommended level (grade 5). Readability formulas have inherent limitations and do not account for visual information. We did not consider other media through which patients with CKD may access information. Although the study covered materials from the United States, United Kingdom, and Australia, all non-Internet materials were sourced locally, and it is possible that some international paper-based materials were missed. Generalizability may be limited due to exclusion of non-English materials. These findings suggest that patient information materials aimed at patients with CKD are pitched above the average patient's literacy level. This issue is compounded by cognitive decline in patients with CKD, who may have lower literacy than the average patient. It suggests that information providers need to consider their audience more carefully when preparing patient information materials, including user testing with a low-literacy patient population. Copyright © 2015 National Kidney Foundation, Inc. Published by

  2. Readability of online patient education materials for velopharyngeal insufficiency.

    Science.gov (United States)

    Xie, Deborah X; Wang, Ray Y; Chinnadurai, Sivakumar

    2018-01-01

    Evaluate the readability of online and mobile application health information about velopharyngeal insufficiency (VPI). Top website and mobile application results for search terms "velopharyngeal insufficiency", "velopharyngeal dysfunction", "VPI", and "VPD" were analyzed. Readability was determined using 10 algorithms with Readability Studio Professional Edition (Oleander Software Ltd; Vandalia, OH). Subgroup analysis was performed based on search term and article source - academic hospital, general online resource, peer-reviewed journal, or professional organization. 18 unique articles were identified. Overall mean reading grade level was a 12.89 ± 2.9. The highest reading level among these articles was 15.47-approximately the level of a college senior. Articles from "velopharyngeal dysfunction" had the highest mean reading level (13.73 ± 2.11), above "velopharyngeal insufficiency" (12.30 ± 1.56) and "VPI" (11.66 ± 1.70). Articles from peer-reviewed journals had the highest mean reading level (15.35 ± 2.79), while articles from academic hospitals had the lowest (12.81 ± 1.66). There were statistically significant differences in reading levels between the different search terms (P reading level guidelines, online patient education materials for VPI are disseminated with language too complex for most readers. There is also a lack of VPI-related mobile application data available for patients. Patients will benefit if future updates to websites and disseminated patient information are undertaken with health literacy in mind. Future studies will investigate patient comprehension of these materials. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Readability, complexity, and suitability analysis of online lymphedema resources.

    Science.gov (United States)

    Tran, Bao Ngoc N; Singh, Mansher; Lee, Bernard T; Rudd, Rima; Singhal, Dhruv

    2017-06-01

    Over 72% of Americans use online health information to assist in health care decision-making. Previous studies of lymphedema literature have focused only on reading level of patient-oriented materials online. Findings indicate they are too advanced for most patients to comprehend. This, more comprehensive study, expands the previous analysis to include critical elements of health materials beyond readability using assessment tools to report on the complexity and density of data as well as text design, vocabulary, and organization. The top 10 highest ranked websites on lymphedema were identified using the most popular search engine (Google). Website content was analyzed for readability, complexity, and suitability using Simple Measure of Gobbledygook, PMOSE/iKIRSCH, and Suitability Assessment of Materials (SAM), respectively. PMOSE/iKIRSCH and SAM were performed by two independent raters. Fleiss' kappa score was calculated to ensure inter-rater reliability. Online lymphedema literature had a reading grade level of 14.0 (SMOG). Overall complexity score was 6.7 (PMOSE/iKIRSCH) corresponding to "low" complexity and requiring a 8th-12th grade education. Fleiss' kappa score was 80% (P = 0.04, "substantial" agreement). Overall suitability score was 45% (SAM) correlating to the lowest level of "adequate" suitability. Fleiss' kappa score was 76% (P = 0.06, "substantial" agreement). Online resources for lymphedema are above the recommended levels for readability and complexity. The suitability level is barely adequate for the intended audience. Overall, these materials are too sophisticated for the average American adult, whose literacy skills are well documented. Further efforts to revise these materials are needed to improve patient comprehension and understanding. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Assessing the Accuracy and Readability of Online Health Information for Patients With Pancreatic Cancer.

    Science.gov (United States)

    Storino, Alessandra; Castillo-Angeles, Manuel; Watkins, Ammara A; Vargas, Christina; Mancias, Joseph D; Bullock, Andrea; Demirjian, Aram; Moser, A James; Kent, Tara S

    2016-09-01

    The degree to which patients are empowered by written educational materials depends on the text's readability level and the accuracy of the information provided. The association of a website's affiliation or focus on treatment modality with its readability and accuracy has yet to be thoroughly elucidated. To compare the readability and accuracy of patient-oriented online resources for pancreatic cancer by treatment modality and website affiliation. An online search of 50 websites discussing 5 pancreatic cancer treatment modalities (alternative therapy, chemotherapy, clinical trials, radiation therapy, and surgery) was conducted. The website's affiliation was identified. Readability was measured by 9 standardized tests, and accuracy was assessed by an expert panel. Nine standardized tests were used to compute the median readability level of each website. The median readability scores were compared among treatment modality and affiliation categories. Accuracy was determined by an expert panel consisting of 2 medical specialists and 2 surgical specialists. The 4 raters independently evaluated all websites belonging to the 5 treatment modalities (a score of 1 indicates that readability and accuracy based on the focus of the treatment modality and the website's affiliation. Websites discussing surgery (with a median readability level of 13.7 and an interquartile range [IQR] of 11.9-15.6) were easier to read than those discussing radiotherapy (median readability level, 15.2 [IQR, 13.0-17.0]) (P = .003) and clinical trials (median readability level, 15.2 [IQR, 12.8-17.0]) (P = .002). Websites of nonprofit organizations (median readability level, 12.9 [IQR, 11.2-15.0]) were easier to read than media (median readability level, 16.0 [IQR, 13.4-17.0]) (P readability level, 14.8 [IQR, 12.9-17.0]) (P readability level, 14.0 [IQR, 12.1-16.1]) were easier to read than media websites (P = .001). Among treatment modalities, alternative therapy websites exhibited the

  5. Sustainable machining

    CERN Document Server

    2017-01-01

    This book provides an overview on current sustainable machining. Its chapters cover the concept in economic, social and environmental dimensions. It provides the reader with proper ways to handle several pollutants produced during the machining process. The book is useful on both undergraduate and postgraduate levels and it is of interest to all those working with manufacturing and machining technology.

  6. Formalizing the Safety of Java, the Java Virtual Machine and Java Card

    NARCIS (Netherlands)

    Hartel, Pieter H.; Moreau, Luc

    2001-01-01

    We review the existing literature on Java safety, emphasizing formal approaches, and the impact of Java safety on small footprint devices such as smart cards. The conclusion is that while a lot of good work has been done, a more concerted effort is needed to build a coherent set of machine readable

  7. Novel feature selection method based on Stochastic Methods Coupled to Support Vector Machines using H- NMR data (data of olive and hazelnut oils

    Directory of Open Access Journals (Sweden)

    Oscar Eduardo Gualdron

    2014-12-01

    Full Text Available One of the principal inconveniences that analysis and information processing presents is that of the representation of dataset. Normally, one encounters a high number of samples, each one with thousands of variables, and in many cases with irrelevant information and noise. Therefore, in order to represent findings in a clearer way, it is necessary to reduce the amount of variables. In this paper, a novel variable selection technique for multivariable data analysis, inspired on stochastic methods and designed to work with support vector machines (SVM, is described. The approach is demonstrated in a food application involving the detection of adulteration of olive oil (more expensive with hazelnut oil (cheaper. Fingerprinting by H NMR spectroscopy was used to analyze the different samples. Results show that it is possible to reduce the number of variables without affecting classification results.

  8. Readability Assessment of Online Uveitis Patient Education Materials.

    Science.gov (United States)

    Ayoub, Samantha; Tsui, Edmund; Mohammed, Taariq; Tseng, Joseph

    2017-12-29

    To evaluate the readability of online uveitis patient education materials. A Google search in November 2016 was completed using search term "uveitis" and "uveitis inflammation." The top 50 websites with patient-centered information were selected and analyzed for readability using the Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES), Gunning FOG Index (GFI), and Simple Measure of Gobbledygook (SMOG). Statistical analysis was performed with two-tailed t-tests. The mean word count of the top 50 websites was 1162.7 words, and averaged 16.2 words per sentence. For these websites, the mean FRES was 38.0 (range 4-66, SD = 12.0), mean FKGL was 12.3 (range 6.8-19, SD = 2.4), mean SMOG score was 14.4 (range 9.8-19, SD = 1.8), and the mean Gunning FOG index was 14.0 (range 8.6-19, SD = 2.0). The majority of online patient directed uveitis materials are at a higher reading level than that of the average American adult.

  9. Informed consent and the readability of the written consent form.

    Science.gov (United States)

    Sivanadarajah, N; El-Daly, I; Mamarelis, G; Sohail, M Z; Bates, P

    2017-11-01

    Introduction The aim of this study was to objectively ascertain the level of readability of standardised consent forms for orthopaedic procedures. Methods Standardised consent forms (both in summary and detailed formats) endorsed by the British Orthopaedic Association (BOA) were retrieved from orthoconsent.com and assessed for readability. This involved using an online tool to calculate the validated Flesch reading ease score (FRES). This was compared with the FRES for the National Health Service (NHS) Consent Form 1. Data were analysed and interpreted according to the FRES grading table. Results The FRES for Consent Form 1 was 55.6, relating to the literacy expected of an A level student. The mean FRES for the BOA summary consent forms (n=27) was 63.6 (95% confidence interval [CI]: 61.2-66.0) while for the detailed consent forms (n=32), it was 68.9 (95% CI: 67.7-70.0). All BOA detailed forms scored >60, correlating to the literacy expected of a 13-15-year-old. The detailed forms had a higher FRES than the summary forms (p<0.001). Conclusions This study demonstrates that the BOA endorsed standardised consent forms are much easier to read and understand than the NHS Consent Form 1, with the detailed BOA forms being the easiest to read. Despite this, owing to varying literacy levels, a significant proportion of patients may struggle to give informed consent based on the written information provided to them.

  10. MONTO: A Machine-Readable Ontology for Teaching Word Problems in Mathematics

    Science.gov (United States)

    Lalingkar, Aparna; Ramnathan, Chandrashekar; Ramani, Srinivasan

    2015-01-01

    The Indian National Curriculum Framework has as one of its objectives the development of mathematical thinking and problem solving ability. However, recent studies conducted in Indian metros have expressed concern about students' mathematics learning. Except in some private coaching academies, regular classroom teaching does not include problem…

  11. Toolsets for Airborne Data (TAD): Improving Machine Readability for ICARTT Data Files

    Science.gov (United States)

    Early, Amanda Benson; Beach, Aubrey; Northup, Emily; Wang, Dali; Kusterer, John; Quam, Brandi; Chen, Gao

    2015-01-01

    The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. The ASDC specializes in atmospheric data that is important to understanding the causes and processes of global climate change and the consequences of human activities on the climate. The ASDC currently supports more than 44 projects and has over 1,700 archived data sets, which increase daily. ASDC customers include scientists, researchers, federal, state, and local governments, academia, industry, and application users, the remote sensing community, and the general public.

  12. 78 FR 28111 - Making Open and Machine Readable the New Default for Government Information

    Science.gov (United States)

    2013-05-14

    ... entrepreneurs and innovators have utilized these resources to create navigation systems, weather newscasts and... . Entrepreneurs and innovators have continued to develop a vast range of useful new products and businesses using... Directive), the Office of Science and Technology Policy Memorandum of February 22, 2013 (Increasing Access...

  13. Available Methods in Farsi-English Cross Language Information Retrieval Using Machine-readable, Bilingual Glossary

    Directory of Open Access Journals (Sweden)

    Hamid Alizadeh

    2009-12-01

    Full Text Available In this paper the impact scope of Natural Language Processing (NLP on translating search statements was determined by testing out research hypotheses. The NLP techniques employed for search statement processing included text parsing, linguistic forms identification, stopword removal, morphological analysis, and tokenization. Examination of the hypotheses indicated that using the method of translating the first equivalent term selected versus the method of selecting all equivalent terms, would contribute to increased efficiency of the review that while morphological analysis of the terms not translated by the glossary, would increase the retrieval precision cutoff, there would be no significant difference established by the lack of such analysis thereof that sentence translation as opposed to term by term translation, would increase the efficiency of Farsi-English proofreading. Other findings are also represented.

  14. The Effect of Technology-Based Altered Readability Levels on Struggling Readers' Science Comprehension

    Science.gov (United States)

    Marino, Matthew T.; Coyne, Michael; Dunn, Michael

    2010-01-01

    This article reports findings from a study examining how altered readability levels affected struggling readers' (N = 288) comprehension of scientific concepts and vocabulary. Specifically, the researchers were interested in learning what effect altered readability levels have when low ability readers participate in a technology-based science…

  15. Readability of Questionnaires Assessing Listening Difficulties Associated with (Central) Auditory Processing Disorders

    Science.gov (United States)

    Atcherson, Samuel R.; Richburg, Cynthia M.; Zraick, Richard I.; George, Cassandra M.

    2013-01-01

    Purpose: Eight English-language, student- or parent proxy-administered questionnaires for (central) auditory processing disorders, or (C)APD, were analyzed for readability. For student questionnaires, readability levels were checked against the approximate reading grade levels by intended administration age per the questionnaires' developers. For…

  16. Can Readability Formulas Be Used to Successfully Gauge Difficulty of Reading Materials?

    Science.gov (United States)

    Begeny, John C.; Greene, Diana J.

    2014-01-01

    A grade level of reading material is commonly estimated using one or more readability formulas, which purport to measure text difficulty based on specified text characteristics. However, there is limited direction for teachers and publishers regarding which readability formulas (if any) are appropriate indicators of actual text difficulty. Because…

  17. A Software Application for Assessing Readability in the Japanese EFL Context

    Science.gov (United States)

    Ozasa, Toshiaki; Weir, George R. S.; Fukui, Masayasu

    2010-01-01

    We have been engaged in developing a readability index and its application software attuned for Japanese EFL learners. The index program, Ozasa-Fukui Year Level Program, Ver. 1.0, was used in developing the readability metric Ozasa-Fukui Year Level Index but tended to assume a high level of computer knowledge in its users. As a result, the…

  18. Readability Level of Spanish-Language Patient-Reported Outcome Measures in Audiology and Otolaryngology

    Science.gov (United States)

    Coco, Laura; Colina, Sonia; Atcherson, Samuel R.

    2017-01-01

    Purpose The purpose of this study was to examine the readability level of the Spanish versions of several audiology- and otolaryngology-related patient-reported outcome measures (PROMs) and include a readability analysis of 2 translation approaches when available—the published version and a “functionalist” version—using a team-based collaborative approach including community members. Method Readability levels were calculated using the Fry Graph adapted for Spanish, as well as the Fernandez-Huerta and the Spaulding formulae for several commonly used audiology- and otolaryngology-related PROMs. Results Readability calculations agreed with previous studies analyzing audiology-related PROMs in English and demonstrated many Spanish-language PROMs were beyond the 5th grade reading level suggested for health-related materials written for the average population. In addition, the functionalist versions of the PROMs yielded lower grade-level (improved) readability levels than the published versions. Conclusion Our results suggest many of the Spanish-language PROMs evaluated here are beyond the recommended readability levels and may be influenced by the approach to translation. Moreover, improved readability may be possible using a functionalist approach to translation. Future analysis of the suitability of outcome measures and the quality of their translations should move beyond readability and include an evaluation of the individual's comprehension of the written text. PMID:28892821

  19. Varying Readability of Science-Based Text in Elementary Readers: Challenges for Teachers

    Science.gov (United States)

    Gallagher, Tiffany L.; Fazio, Xavier; Gunning, Thomas G.

    2012-01-01

    This investigation compared readability formulae to publishers' identified reading levels in science-based elementary readers. Nine well-established readability indices were calculated and comparisons were made with the publishers' identified grade designations and between different genres of text. Results revealed considerable variance among the…

  20. A Comparison of Readability in Science-Based Texts: Implications for Elementary Teachers

    Science.gov (United States)

    Gallagher, Tiffany; Fazio, Xavier; Ciampa, Katia

    2017-01-01

    Science curriculum standards were mapped onto various texts (literacy readers, trade books, online articles). Statistical analyses highlighted the inconsistencies among readability formulae for Grades 2-6 levels of the standards. There was a lack of correlation among the readability measures, and also when comparing different text sources. Online…

  1. Measuring the readability of sustainability reports: : A corpus-based analysis through standard formulae and NLP

    NARCIS (Netherlands)

    Smeuninx, N.; De Clerck, B.; Aerts, Walter

    2016-01-01

    This study characterises and problematises the language of corporate reporting along region, industry, genre, and content lines by applying readability formulae and more advanced natural language processing (NLP)–based analysis to a manually assembled 2.75-million-word corpus. Readability formulae

  2. Readability of "Dear Patient" device advisory notification letters created by a device manufacturer.

    Science.gov (United States)

    Mueller, Luke A; Sharma, Arjun; Ottenberg, Abigale L; Mueller, Paul S

    2013-04-01

    In 2006, the Heart Rhythm Society (HRS) recommended that cardiovascular implantable electronic device (CIED) manufacturers use advisory notification letters to communicate with affected patients. To evaluate the readability of the HRS sample "patient device advisory notification" letter and those created by 1 CIED manufacturer. The HRS sample letter and 25 Boston Scientific Corporation letters dated from 2005 through 2011 were evaluated by using 6 readability tests. Readability (Flesch-Kincaid score) of the HRS sample letter was grade level 12.5, and median readability of the device manufacturer letters was grade level 12.8 (range 10.8-18.9). Similar results were obtained by using other readability scales. No letters had readability scores at the National Work Group on Literacy and Health's recommended reading level-fifth grade; the letters' readability exceeded this recommended level by an average of 7.7 grades (95% confidence interval 6.9-8.5; Preadability scores at the average reading level of US adults-eighth grade; the letters' readability exceeded this level by an average of 4.7 grades (95% confidence interval 3.9-5.5; Preadability of the HRS sample letter and those created by a CIED manufacturer significantly exceeded the recommended and average US adults' reading skill levels. Such letters are unlikely to be informative to many patients. CIED manufacturers should ensure that advisory letters are comprehensible to most affected patients. Copyright © 2013 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

  3. Computational Text Analysis: A More Comprehensive Approach to Determine Readability of Reading Materials

    Science.gov (United States)

    Aziz, Anealka; Fook, Chan Yuen; Alsree, Zubaida

    2010-01-01

    Reading materials are considered having high readability if readers are interested to read the materials, understand the content of the materials and able to read the materials fluently. In contrast, reading materials with low readability discourage readers from reading the materials, create difficulties for readers to understand the content of…

  4. Readability of Air Force Publications: A Criterion Referenced Evaluation. Final Report.

    Science.gov (United States)

    Hooke, Lydia R.; And Others

    In a study of the readability of Air Force regulations, the writer-estimated reading grade level (RGL) for each regulation was rechecked by using the FORCAST readability formula. In four of the seven cases, the regulation writers underestimated the RGL of their regulation by more than one grade level. None of the writers produced a document with…

  5. Readability of the web: a study on 1 billion web pages

    NARCIS (Netherlands)

    de Heus, Marije; Hiemstra, Djoerd

    We have performed a readability study on more than 1 billion web pages. The Automated Readability Index was used to determine the average grade level required to easily comprehend a website. Some of the results are that a 16-year-old can easily understand 50% of the web and an 18-year old can easily

  6. Quality and readability of English-language internet information for aphasia.

    Science.gov (United States)

    Azios, Jamie H; Bellon-Harn, Monica; Dockens, Ashley L; Manchaiah, Vinaya

    2017-08-14

    Little is known about the quality and readability of treatment information in specific neurogenic disorders, such as aphasia. The purpose of this study was to assess quality and readability of English-language Internet information available for aphasia treatment. Forty-three aphasia treatment websites were aggregated using five different country-specific search engines. Websites were then analysed using quality and readability assessments. Statistical calculations were employed to examine website ratings, differences between website origin and quality and readability scores, and correlations between readability instruments. Websites exhibited low quality with few websites obtaining Health On the Net (HON) certification or clear, thorough information as measured by the DISCERN. Regardless of website origin, readability scores were also poor. Approximate educational levels required to comprehend information on aphasia treatment websites ranged from 13 to 16 years of education. Significant differences were found between website origin and readability measures with higher levels of education required to understand information on websites of non-profit organisations. Current aphasia treatment websites were found to exhibit low levels of quality and readability, creating potential accessibility problems for people with aphasia and significant others. Websites including treatment information for aphasia must be improved in order to increase greater information accessibility.

  7. The Readability of Information Literacy Content on Academic Library Web Sites

    Science.gov (United States)

    Lim, Adriene

    2010-01-01

    This article reports on a study addressing the readability of content on academic libraries' Web sites, specifically content intended to improve users' information literacy skills. Results call for recognition of readability as an evaluative component of text in order to better meet the needs of diverse user populations. (Contains 8 tables.)

  8. Analysis of Readability and Interest of Marketing Education Textbooks: Implications for Special Needs Learners.

    Science.gov (United States)

    Jones, Karen H.; And Others

    1993-01-01

    The readability, reading ease, interest level, and writing style of 20 current textbooks in secondary marketing education were evaluated. Readability formulas consistently identified lower reading levels for special needs education, human interest scores were not very reliable information sources, and writing style was also a weak variable. (JOW)

  9. Assessing readability formula differences with written health information materials: application, results, and recommendations.

    Science.gov (United States)

    Wang, Lih-Wern; Miller, Michael J; Schmitt, Michael R; Wen, Frances K

    2013-01-01

    Readability formulas are often used to guide the development and evaluation of literacy-sensitive written health information. However, readability formula results may vary considerably as a result of differences in software processing algorithms and how each formula is applied. These variations complicate interpretations of reading grade level estimates, particularly without a uniform guideline for applying and interpreting readability formulas. This research sought to (1) identify commonly used readability formulas reported in the health care literature, (2) demonstrate the use of the most commonly used readability formulas on written health information, (3) compare and contrast the differences when applying common readability formulas to identical selections of written health information, and (4) provide recommendations for choosing an appropriate readability formula for written health-related materials to optimize their use. A literature search was conducted to identify the most commonly used readability formulas in health care literature. Each of the identified formulas was subsequently applied to word samples from 15 unique examples of written health information about the topic of depression and its treatment. Readability estimates from common readability formulas were compared based on text sample size, selection, formatting, software type, and/or hand calculations. Recommendations for their use were provided. The Flesch-Kincaid formula was most commonly used (57.42%). Readability formulas demonstrated variability up to 5 reading grade levels on the same text. The Simple Measure of Gobbledygook (SMOG) readability formula performed most consistently. Depending on the text sample size, selection, formatting, software, and/or hand calculations, the individual readability formula estimated up to 6 reading grade levels of variability. The SMOG formula appears best suited for health care applications because of its consistency of results, higher level of expected

  10. Power Electronics and Electric Machines Facilities | Transportation

    Science.gov (United States)

    Research | NREL Facilities Power Electronics and Electric Machines Facilities NREL's power electronics and electric machines thermal management experimentation facilities feature a wide range of four researchers in discussion around a piece of laboratory equipment. Power electronics researchers

  11. Readability of online patient education materials on adult reconstruction Web sites.

    Science.gov (United States)

    Polishchuk, Daniil L; Hashem, Jenifer; Sabharwal, Sanjeev

    2012-05-01

    Recommended readability of patient education materials is sixth-grade level or lower. Readability of 212 patient education materials pertaining to adult reconstruction topics available from the American Academy of Orthopaedic Surgeons, American Association of Hip and Knee Surgeons, and 3 other specialty and private practitioner Web sites was assessed using the Flesch-Kincaid grade formula. The mean Flesch-Kincaid score was 11.1 (range, 3-26.5). Only 5 (2%) articles had a readability level of sixth grade or lower. Readability of most of the articles for patient education on adult reconstruction Web sites evaluated may be too advanced for a substantial portion of patients. Further studies are needed to assess the optimal readability level of health information on the Internet. Copyright © 2012 Elsevier Inc. All rights reserved.

  12. Insights into Protein Sequence and Structure-Derived Features Mediating 3D Domain Swapping Mechanism using Support Vector Machine Based Approach

    Directory of Open Access Journals (Sweden)

    Khader Shameer

    2010-06-01

    Full Text Available 3-dimensional domain swapping is a mechanism where two or more protein molecules form higher order oligomers by exchanging identical or similar subunits. Recently, this phenomenon has received much attention in the context of prions and neuro-degenerative diseases, due to its role in the functional regulation, formation of higher oligomers, protein misfolding, aggregation etc. While 3-dimensional domain swap mechanism can be detected from three-dimensional structures, it remains a formidable challenge to derive common sequence or structural patterns from proteins involved in swapping. We have developed a SVM-based classifier to predict domain swapping events using a set of features derived from sequence and structural data. The SVM classifier was trained on features derived from 150 proteins reported to be involved in 3D domain swapping and 150 proteins not known to be involved in swapped conformation or related to proteins involved in swapping phenomenon. The testing was performed using 63 proteins from the positive dataset and 63 proteins from the negative dataset. We obtained 76.33% accuracy from training and 73.81% accuracy from testing. Due to high diversity in the sequence, structure and functions of proteins involved in domain swapping, availability of such an algorithm to predict swapping events from sequence and structure-derived features will be an initial step towards identification of more putative proteins that may be involved in swapping or proteins involved in deposition disease. Further, the top features emerging in our feature selection method may be analysed further to understand their roles in the mechanism of domain swapping.

  13. Readability of patient education materials on the American Orthopaedic Society for Sports Medicine website.

    Science.gov (United States)

    Eltorai, Adam E M; Han, Alex; Truntzer, Jeremy; Daniels, Alan H

    2014-11-01

    The recommended readability of patient education materials by the American Medical Association (AMA) and National Institutes of Health (NIH) should be no greater than a sixth-grade reading level. However, online resources may be too complex for some patients to understand, and poor health literacy predicts inferior health-related quality of life outcomes. This study evaluated whether the American Orthopaedic Society for Sports Medicine (AOSSM) website's patient education materials meet recommended readability guidelines for medical information. We hypothesized that the readability of these online materials would have a Flesch-Kincaid formula grade above the sixth grade. All 65 patient education entries of the AOSSM website were analyzed for grade level readability using the Flesch-Kincaid formula, a widely used and validated tool to evaluate the text reading level. The average (standard deviation) readability of all 65 articles was grade level 10.03 (1.44); 64 articles had a readability score above the sixth-grade level, which is the maximum level recommended by the AMA and NIH. Mean readability of the articles exceeded this level by 4.03 grade levels (95% CI, 3.7-4.4; P reading level of US adults. Mean readability of the articles exceeded this level by 2.03 grade levels (95% CI, 1.7-2.4; P online AOSSM patient education materials exceeds the readability level recommended by the AMA and NIH, and is above the average reading level of the majority of US adults. This online information may be of limited utility to most patients due to a lack of comprehension. Our study provides a clear example of the need to improve the readability of specific education material in order to maximize the efficacy of multimedia sources.

  14. [Systematic analysis of the readability of patient information on the websites of clinics for plastic surgery].

    Science.gov (United States)

    Esfahani, B Janghorban; Faron, A; Roth, K S; Schaller, H-E; Medved, F; Lüers, J-C

    2014-12-01

    The Internet is becoming increasing-ly important as a source of information for patients in medical issues. However, many patients have problems to adequately understand texts, especially with medical content. A basic requirement to understand a written text is the read-ability of a text. The aim of the present study was to examine texts on the websites of German -plastic-surgical hospitals with patient information regarding their readability. In this study, the read-ability of texts of 27 major departments of plastic and Hand surgery in Germany was systematically analysed using 5 recognised readability indices. First, texts were searched based on 20 representative key words and themes. Thereafter, texts were assigned to one of 3 major themes in order to enable statistical analysis. In addition to the 5 readability indices, further objective text parameters were also recorded. Overall, 288 texts were found for analyzation. Most articles were found on the topic of "handsurgery" (n=124), less were found for "facial plastic surgery" (n=80) and "flaps, breast and reconstructive surgery" (n=84). Consistently, all readability indices showed a poor readability for the vast majority of analysed texts with the text appearing readable only for readers with a higher educational level. No significant differences in readability were found between the 3 major themes. Especially in the communication of medical information, it is important to consider the knowledge and education of the addressee. The texts studied consistently showed a readability that is understandable only for academics. Thus, a large part of the intended target group is probably not reached. In order to adequately deliver online information material, a revision of the analysed internet texts appears to be recommendable. © Georg Thieme Verlag KG Stuttgart · New York.

  15. Clearly written, easily comprehended? The readability of websites providing information on epilepsy.

    Science.gov (United States)

    Brigo, Francesco; Otte, Willem M; Igwe, Stanley C; Tezzon, Frediano; Nardone, Raffaele

    2015-03-01

    There is a general need for high-quality, easily accessible, and comprehensive health-care information on epilepsy to better inform the general population about this highly stigmatized neurological disorder. The aim of this study was to evaluate the health literacy level of eight popular English-written websites that provide information on epilepsy in quantitative terms of readability. Educational epilepsy material on these websites, including 41 Wikipedia articles, were analyzed for their overall level of readability and the corresponding academic grade level needed to comprehend the published texts on the first reading. The Flesch Reading Ease (FRE) was used to assess ease of comprehension while the Gunning Fog Index, Coleman-Liau Index, Flesch-Kincaid Grade Level, Automated Readability Index, and Simple Measure of Gobbledygook scales estimated the corresponding academic grade level needed for comprehension. The average readability of websites yielded results indicative of a difficult-to-fairly-difficult readability level (FRE results: 44.0±8.2), with text readability corresponding to an 11th academic grade level (11.3±1.9). The average FRE score of the Wikipedia articles was indicative of a difficult readability level (25.6±9.5), with the other readability scales yielding results corresponding to a 14th grade level (14.3±1.7). Popular websites providing information on epilepsy, including Wikipedia, often demonstrate a low level of readability. This can be ameliorated by increasing access to clear and concise online information on epilepsy and health in general. Short "basic" summaries targeted to patients and nonmedical users should be added to articles published in specialist websites and Wikipedia to ease readability. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Combination of support vector machine, artificial neural network and random forest for improving the classification of convective and stratiform rain using spectral features of SEVIRI data

    Science.gov (United States)

    Lazri, Mourad; Ameur, Soltane

    2018-05-01

    A model combining three classifiers, namely Support vector machine, Artificial neural network and Random forest (SAR) is designed for improving the classification of convective and stratiform rain. This model (SAR model) has been trained and then tested on a datasets derived from MSG-SEVIRI (Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager). Well-classified, mid-classified and misclassified pixels are determined from the combination of three classifiers. Mid-classified and misclassified pixels that are considered unreliable pixels are reclassified by using a novel training of the developed scheme. In this novel training, only the input data corresponding to the pixels in question to are used. This whole process is repeated a second time and applied to mid-classified and misclassified pixels separately. Learning and validation of the developed scheme are realized against co-located data observed by ground radar. The developed scheme outperformed different classifiers used separately and reached 97.40% of overall accuracy of classification.

  17. Mechanical design of machine components

    CERN Document Server

    Ugural, Ansel C

    2015-01-01

    Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...

  18. Simple machines

    CERN Document Server

    Graybill, George

    2007-01-01

    Just how simple are simple machines? With our ready-to-use resource, they are simple to teach and easy to learn! Chocked full of information and activities, we begin with a look at force, motion and work, and examples of simple machines in daily life are given. With this background, we move on to different kinds of simple machines including: Levers, Inclined Planes, Wedges, Screws, Pulleys, and Wheels and Axles. An exploration of some compound machines follows, such as the can opener. Our resource is a real time-saver as all the reading passages, student activities are provided. Presented in s

  19. Laser readable thermoluminescent radiation dosimeters and methods for producing thereof

    International Nuclear Information System (INIS)

    Braunlich, P.F.; Tetzlaff, W.

    1989-01-01

    Thin layer thermoluminescent radiation dosimeters for use in laser readable dosimetry systems, and methods of fabricating such thin layer dosimeters are disclosed. The thin layer thermoluminescent radiation dosimeters include a thin substrate made from glass or other inorganic materials capable of withstanding high temperatures and high heating rates. A thin layer of a thermoluminescent phosphor material is heat bonded to the substrate using an inorganic binder such as glass. The dosimeters can be mounted in frames and cases for ease in handling. Methods of the invention include mixing a suitable phosphor composition and binder, both being in particulate or granular form. The mixture is then deposited onto a substrate such as by using mask printing techniques. The dosimeters are thereafter heated to fuse and bond the binder and phosphor to the substrate. 34 figs

  20. DNA-based machines.

    Science.gov (United States)

    Wang, Fuan; Willner, Bilha; Willner, Itamar

    2014-01-01

    The base sequence in nucleic acids encodes substantial structural and functional information into the biopolymer. This encoded information provides the basis for the tailoring and assembly of DNA machines. A DNA machine is defined as a molecular device that exhibits the following fundamental features. (1) It performs a fuel-driven mechanical process that mimics macroscopic machines. (2) The mechanical process requires an energy input, "fuel." (3) The mechanical operation is accompanied by an energy consumption process that leads to "waste products." (4) The cyclic operation of the DNA devices, involves the use of "fuel" and "anti-fuel" ingredients. A variety of DNA-based machines are described, including the construction of "tweezers," "walkers," "robots," "cranes," "transporters," "springs," "gears," and interlocked cyclic DNA structures acting as reconfigurable catenanes, rotaxanes, and rotors. Different "fuels", such as nucleic acid strands, pH (H⁺/OH⁻), metal ions, and light, are used to trigger the mechanical functions of the DNA devices. The operation of the devices in solution and on surfaces is described, and a variety of optical, electrical, and photoelectrochemical methods to follow the operations of the DNA machines are presented. We further address the possible applications of DNA machines and the future perspectives of molecular DNA devices. These include the application of DNA machines as functional structures for the construction of logic gates and computing, for the programmed organization of metallic nanoparticle structures and the control of plasmonic properties, and for controlling chemical transformations by DNA machines. We further discuss the future applications of DNA machines for intracellular sensing, controlling intracellular metabolic pathways, and the use of the functional nanostructures for drug delivery and medical applications.

  1. Readability of Trauma-Related Patient Education Materials From the American Academy of Orthopaedic Surgeons.

    Science.gov (United States)

    Eltorai, Adam E M; P Thomas, Nathan; Yang, Heejae; Daniels, Alan H; Born, Christopher T

    2016-02-01

    According to the american medical association (AMA) and the national institutes of health (NIH), the recommended readability of patient education materials should be no greater than a sixth-grade reading level. The online patient education information produced by the american academy of orthopaedic surgeons (AAOS) may be too complicated for some patients to understand. This study evaluated whether the AAOS's online trauma-related patient education materials meet recommended readability guidelines for medical information. Ninety-nine articles from the "Broken Bones and Injuries" section of the AAOS-produced patient education website, orthoinfo.org, were analyzed for grade level readability using the Flesch-Kincaid formula, a widely-used and validated tool to evaluate the text reading level. Results for each webpage were compared to the AMA/NIH recommended sixth-grade reading level and the average reading level of U.S. adults (eighth-grade). The mean (SD) grade level readability for all patient education articles was 8.8 (1.1). All but three of the articles had a readability score above the sixth-grade level. The readability of the articles exceeded this level by an average of 2.8 grade levels (95% confidence interval, 2.6 - 3.0; P reading skill level of U.S. adults (eighth grade) by nearly an entire grade level (95% confidence interval, 0.6-1.0; P education website have readability levels that may make comprehension difficult for a substantial portion of the patient population.

  2. Readability of Online Patient Education Materials From the AAOS Web Site

    Science.gov (United States)

    Badarudeen, Sameer; Unes Kunju, Shebna

    2008-01-01

    One of the goals of the American Academy of Orthopaedic Surgeons (AAOS) is to disseminate patient education materials that suit the readability skills of the patient population. According to standard guidelines from healthcare organizations, the readability of patient education materials should be no higher than the sixth-grade level. We hypothesized the readability level of patient education materials available on the AAOS Web site would be higher than the recommended grade level, regardless when the material was available online. Readability scores of all articles from the AAOS Internet-based patient information Web site, “Your Orthopaedic Connection,” were determined using the Flesch-Kincaid grade formula. The mean Flesch-Kincaid grade level of the 426 unique articles was 10.43. Only 10 (2%) of the articles had the recommended readability level of sixth grade or lower. The readability of the articles did not change with time. Our findings suggest the majority of the patient education materials available on the AAOS Web site had readability scores that may be too difficult for comprehension by a substantial portion of the patient population. PMID:18324452

  3. Evaluation of the Readability of Dermatological Postoperative Patient Information Leaflets Across England.

    Science.gov (United States)

    Hunt, William T N; McGrath, Emily J

    2016-06-01

    Postoperative patient information leaflets (PILs) provide important guidance to patients after skin surgery. Readability is a method of evaluating information for text comprehension. The recommended level for PIL readability is US grade ≤6. To evaluate the readability of public English dermatological postoperative PILs. All dermatology departments in England were requested to provide their postoperative PILs. Patient information leaflets were evaluated using Readability Studio (Oleander Software, Vandalia, OH). Two preselected parameters were also noted: whether the PIL was doctor or nurse-written, and whether the PIL was Information Standard hallmarked. Eighty-five of one hundred thirty (65.4%) of PILs were evaluated. Only 29.4% of the PILs were grade level ≤6 with Flesch-Kincaid. The mean readability levels were 7.8 for Flesch-Kincaid, 67 for Flesch reading ease, 10.5 for Simple Measure of Gobbledygook (SMOG), 9.4 for Gunning-Fog, 8 for Fry, and 9.8 for FORCAST. No instruments demonstrated a significant difference between doctor (6) and nurse-written (7) PILs. Two instruments found that the 3 Information Standard hallmarked PILs had a higher (harder) readability than ordinary PILs (n = 82) (Gunning-Fog, p = .029*; SMOG p = .049*). Most English postoperative dermatological PILs' readability levels exceed recommendations (US grade ≤6). Departmental PILs should be reviewed to ensure that they are comprehensible to their patients.

  4. Quality and Readability of English-Language Internet Information for Voice Disorders.

    Science.gov (United States)

    Dueppen, Abigail J; Bellon-Harn, Monica L; Radhakrishnan, Nandhakumar; Manchaiah, Vinaya

    2017-12-15

    The purpose of this study is to evaluate the readability and quality of English-language Internet information related to vocal hygiene, vocal health, and prevention of voice disorders. This study extends recent work because it evaluates readability, content quality, and website origin across broader search criteria than previous studies evaluating online voice material. Eighty-five websites were aggregated using five different country-specific search engines. Websites were then analyzed using quality and readability assessments. The entire web page was evaluated; however, no information or links beyond the first page was reviewed. Statistical calculations were employed to examine website ratings, differences between website origin and quality and readability scores, and correlations between readability instruments. Websites exhibited acceptable quality as measured by the DISCERN. However, only one website obtained the Health On the Net certification. Significant differences in quality were found among website origin, with government websites receiving higher quality ratings. Approximate educational levels required to comprehend information on the websites ranged from 8 to 9 years of education. Significant differences were found between website origin and readability measures with higher levels of education required to understand information on websites of nonprofit organizations. Current vocal hygiene, vocal health, and prevention of voice disorders websites were found to exhibit acceptable levels of quality and readability. However, highly rated Internet information related to voice care should be made more accessible to voice clients through Health On the Net certification. Published by Elsevier Inc.

  5. Readability evaluation of Internet-based patient education materials related to the anesthesiology field.

    Science.gov (United States)

    De Oliveira, Gildasio S; Jung, Michael; Mccaffery, Kirsten J; McCarthy, Robert J; Wolf, Michael S

    2015-08-01

    The main objective of the current investigation was to assess the readability of Internet-based patient education materials related to the field of anesthesiology. We hypothesized that the majority of patient education materials would not be written according to current recommended readability grade level. Online patient education materials describing procedures, risks, and management of anesthesia-related topics were identified using the search engine Google (available at www.google.com) using the terms anesthesia, anesthesiology, anesthesia risks, and anesthesia care. Cross-sectional evaluation. None. Assessments of content readability were performed using validated instruments (Flesch-Kincaid Grade Formulae, the Gunning Frequency of Gobbledygook, the New Dale-Chall Test, the Fry graph, and the Flesch Reading Ease score). Ninety-six Web sites containing Internet patient education materials (IPEMs) were evaluated. The median (interquartile range) readability grade level for all evaluated IPEMs was 13.5 (12.0-14.6). All the evaluated documents were classified at a greater readability level than the current recommended readability grade, P Internet-based patient education materials related to the field of anesthesiology are currently written far above the recommended readability grade level. High complexity of written education materials likely limits access of information to millions of American patients. Redesign of online content of Web sites that provide patient education material regarding anesthesia could be an important step in improving access to information for patients with poor health literacy. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Improving the readability of online foot and ankle patient education materials.

    Science.gov (United States)

    Sheppard, Evan D; Hyde, Zane; Florence, Mason N; McGwin, Gerald; Kirchner, John S; Ponce, Brent A

    2014-12-01

    Previous studies have shown the need for improving the readability of many patient education materials to increase patient comprehension. This study's purpose was to determine the readability of foot and ankle patient education materials and to determine the extent readability can be improved. We hypothesized that the reading levels would be above the recommended guidelines and that decreasing the sentence length would also decrease the reading level of these patient educational materials. Patient education materials from online public sources were collected. The readability of these articles was assessed by a readability software program. The detailed instructions provided by the National Institutes of Health (NIH) were then used as a guideline for performing edits to help improve the readability of selected articles. The most quantitative guideline, lowering all sentences to less than 15 words, was chosen to show the effect of following the NIH recommendations. The reading levels of the sampled articles were above the sixth to seventh grade recommendations of the NIH. The MedlinePlus website, which is a part of the NIH website, had the lowest reading level (8.1). The articles edited had an average reduction of 1.41 grade levels, with the lowest reduction in the Medline articles of 0.65. Providing detailed instructions to the authors writing these patient education articles and implementing editing techniques based on previous recommendations could lead to an improvement in the readability of patient education materials. This study provides authors of patient education materials with simple editing techniques that will allow for the improvement in the readability of online patient educational materials. The improvement in readability will provide patients with more comprehendible education materials that can strengthen patient awareness of medical problems and treatments. © The Author(s) 2014.

  7. Readability assessment of package inserts of biological medicinal products from the European medicines agency website.

    Science.gov (United States)

    Piñero-López, Ma Ángeles; Modamio, Pilar; Lastra, Cecilia F; Mariño, Eduardo L

    2014-07-01

    Package inserts that accompany medicines are a common source of information aimed at patients and should match patient abilities in terms of readability. Our objective was to determine the degree of readability of the package inserts for biological medicinal products commercially available in 2007 and compare them with the readability of the same package inserts in 2010. A total of 33 package inserts were selected and classified into five groups according to the type of medicine: monoclonal antibody-based products, cytokines, therapeutic enzymes, recombinant blood factors and other blood-related products, and recombinant hormones. The package inserts were downloaded from the European Medicines Agency website in 2007 and 2010. Readability was evaluated for the entire text of five of the six sections of the package inserts and for the 'Annex' when there was one. Three readability formulas were used: SMOG (Simple Measure of Gobbledygook) grade, Flesh-Kincaid grade level, and Szigriszt's perspicuity index. No significant differences were found between the readability results for the 2007 package inserts and those from 2010 according to any of the three readability indices studied (p>0.05). However, there were significant differences (preadability scores of the sections of the package inserts in both 2007 and 2010. The readability of the package inserts was above the recommended sixth grade reading level (ages 11-12) and may lead to difficulties of understanding for people with limited literacy. All the sections should be easy to read and, therefore, the readability of the medicine package inserts studied should be improved.

  8. Readability of patient education materials in ophthalmology: a single-institution study and systematic review.

    Science.gov (United States)

    Williams, Andrew M; Muir, Kelly W; Rosdahl, Jullia A

    2016-08-03

    Patient education materials should be written at a level that is understandable for patients with low health literacy. The aims of this study are (1) to review the literature on readability of ophthalmic patient education materials and (2) to evaluate and revise our institution's patient education materials about glaucoma using evidence-based guidelines on writing for patients with low health literacy. A systematic search was conducted on the PubMed/MEDLINE database for studies that have evaluated readability level of ophthalmic patient education materials, and the reported readability scores were assessed. Additionally, we collected evidence-based guidelines for writing easy-to-read patient education materials, and these recommendations were applied to revise 12 patient education handouts on various glaucoma topics at our institution. Readability measures, including Flesch-Kincaid Grade Level (FKGL), and word count were calculated for the original and revised documents. The original and revised versions of the handouts were then scored in random order by two glaucoma specialists using the Suitability Assessment of Materials (SAM) instrument, a grading scale used to evaluate suitability of health information materials for patients. Paired t test was used to analyze changes in readability measures, word count, and SAM score between original and revised handouts. Finally, five glaucoma patients were interviewed to discuss the revised materials, and patient feedback was analyzed qualitatively. Our literature search included 13 studies that evaluated a total of 950 educational materials. Among the mean FKGL readability scores reported in these studies, the median was 11 (representing an eleventh-grade reading level). At our institution, handouts' readability averaged a tenth-grade reading level (FKGL = 10.0 ± 1.6), but revising the handouts improved their readability to a sixth-grade reading level (FKGL = 6.4 ± 1.2) (p readability and suitability of

  9. Face machines

    Energy Technology Data Exchange (ETDEWEB)

    Hindle, D.

    1999-06-01

    The article surveys latest equipment available from the world`s manufacturers of a range of machines for tunnelling. These are grouped under headings: excavators; impact hammers; road headers; and shields and tunnel boring machines. Products of thirty manufacturers are referred to. Addresses and fax numbers of companies are supplied. 5 tabs., 13 photos.

  10. Electric machine

    Science.gov (United States)

    El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  11. Machine Learning.

    Science.gov (United States)

    Kirrane, Diane E.

    1990-01-01

    As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

  12. Nonplanar machines

    International Nuclear Information System (INIS)

    Ritson, D.

    1989-05-01

    This talk examines methods available to minimize, but never entirely eliminate, degradation of machine performance caused by terrain following. Breaking of planar machine symmetry for engineering convenience and/or monetary savings must be balanced against small performance degradation, and can only be decided on a case-by-case basis. 5 refs

  13. A Study of the Subject Categorization of the MIS-related Journals in the ISI Databases Using Topical Features in the Text Content and Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Sung-Chien Lin

    2015-07-01

    Full Text Available In this study we analyzed and discussed that the MIS-related journals under the ISI subject category of IS&LS are simultaneously given with subject category Management, using methods of topic modeling, journal clustering and subject category prediction. In the experiment of journal clustering, all journals under subject category Management and other journals also having similar topical features can be gathered into a cluster, and “management” is their common and the most distinct topic. Because the journals belonged to this cluster are almost same to those in the MIS clusters generated by the previous studies, we considered it as the MIS cluster in this study. In the second experiment, we used the classification and regression tree (CART technique to predict assignment of subject category with that the journals in the original subject category Management and in the MIS cluster produced in this study as positive examples, respectively. The trees generated by the two tests both used the occurring probabilities of the topic “management” as the main classification rule. However, in the latter test, we did not only obtain a simpler classification tree but also had a result with less predicting errors. This means that if all journals in the MIS cluster could be given with subject category Management, the retrieval results can be more effective and complete.

  14. Advances in Machine Technology.

    Science.gov (United States)

    Clark, William R; Villa, Gianluca; Neri, Mauro; Ronco, Claudio

    2018-01-01

    Continuous renal replacement therapy (CRRT) machines have evolved into devices specifically designed for critically ill over the past 40 years. In this chapter, a brief history of this evolution is first provided, with emphasis on the manner in which changes have been made to address the specific needs of the critically ill patient with acute kidney injury. Subsequently, specific examples of technology developments for CRRT machines are discussed, including the user interface, pumps, pressure monitoring, safety features, and anticoagulation capabilities. © 2018 S. Karger AG, Basel.

  15. The Machine within the Machine

    CERN Multimedia

    Katarina Anthony

    2014-01-01

    Although Virtual Machines are widespread across CERN, you probably won't have heard of them unless you work for an experiment. Virtual machines - known as VMs - allow you to create a separate machine within your own, allowing you to run Linux on your Mac, or Windows on your Linux - whatever combination you need.   Using a CERN Virtual Machine, a Linux analysis software runs on a Macbook. When it comes to LHC data, one of the primary issues collaborations face is the diversity of computing environments among collaborators spread across the world. What if an institute cannot run the analysis software because they use different operating systems? "That's where the CernVM project comes in," says Gerardo Ganis, PH-SFT staff member and leader of the CernVM project. "We were able to respond to experimentalists' concerns by providing a virtual machine package that could be used to run experiment software. This way, no matter what hardware they have ...

  16. Leveling L2 Texts through Readability: Combining Multilevel Linguistic Features with the CEFR

    Science.gov (United States)

    Sung, Yao-Ting; Lin, Wei-Chun; Dyson, Scott Benjamin; Chang, Kuo-En; Chen, Yu-Chia

    2015-01-01

    Selecting appropriate texts for L2 (second/foreign language) learners is an important approach to enhancing motivation and, by extension, learning. There is currently no tool for classifying foreign language texts according to a language proficiency framework, which makes it difficult for students and educators to determine the precise…

  17. Machine Learning for Medical Imaging.

    Science.gov (United States)

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

  18. Machine translation

    Energy Technology Data Exchange (ETDEWEB)

    Nagao, M

    1982-04-01

    Each language has its own structure. In translating one language into another one, language attributes and grammatical interpretation must be defined in an unambiguous form. In order to parse a sentence, it is necessary to recognize its structure. A so-called context-free grammar can help in this respect for machine translation and machine-aided translation. Problems to be solved in studying machine translation are taken up in the paper, which discusses subjects for semantics and for syntactic analysis and translation software. 14 references.

  19. Readability of Online Patient Educational Resources Found on NCI-Designated Cancer Center Web Sites.

    Science.gov (United States)

    Rosenberg, Stephen A; Francis, David; Hullett, Craig R; Morris, Zachary S; Fisher, Michael M; Brower, Jeffrey V; Bradley, Kristin A; Anderson, Bethany M; Bassetti, Michael F; Kimple, Randall J

    2016-06-01

    The NIH and Department of Health & Human Services recommend online patient information (OPI) be written at a sixth grade level. We used a panel of readability analyses to assess OPI from NCI-Designated Cancer Center (NCIDCC) Web sites. Cancer.gov was used to identify 68 NCIDCC Web sites from which we collected both general OPI and OPI specific to breast, prostate, lung, and colon cancers. This text was analyzed by 10 commonly used readability tests: the New Dale-Chall Readability Formula, Flesch Reading Ease scale, Flesch-Kinaid Grade Level, FORCAST scale, Fry Readability Graph, Simple Measure of Gobbledygook test, Gunning Frequency of Gobbledygook index, New Fog Count, Raygor Readability Estimate Graph, and Coleman-Liau Index. We tested the hypothesis that the readability of NCIDCC OPI was written at the sixth grade level. Secondary analyses were performed to compare readability of OPI between comprehensive and noncomprehensive centers, by region, and to OPI produced by the American Cancer Society (ACS). A mean of 30,507 words from 40 comprehensive and 18 noncomprehensive NCIDCCs was analyzed (7 nonclinical and 3 without appropriate OPI were excluded). Using a composite grade level score, the mean readability score of 12.46 (ie, college level: 95% CI, 12.13-12.79) was significantly greater than the target grade level of 6 (middle-school: Preadability metrics (P<.05). ACS OPI provides easier language, at the seventh to ninth grade level, across all tests (P<.01). OPI from NCIDCC Web sites is more complex than recommended for the average patient. Copyright © 2016 by the National Comprehensive Cancer Network.

  20. Readability of Patient Education Materials in Hand Surgery and Health Literacy Best Practices for Improvement.

    Science.gov (United States)

    Hadden, Kristie; Prince, Latrina Y; Schnaekel, Asa; Couch, Cory G; Stephenson, John M; Wyrick, Theresa O

    2016-08-01

    This study aimed to update a portion of a 2008 study of patient education materials from the American Society for Surgery of the Hand Web site with new readability results, to compare the results to health literacy best practices, and to make recommendations to the field for improvement. A sample of 77 patient education documents were downloaded from the American Society for Surgery of the Hand Web site, handcare.org, and assessed for readability using 4 readability tools. Mean readability grade-level scores were derived. Best practices for plain language for written health materials were compiled from 3 government agency sources. The mean readability of the 77 patient education documents in the study was 9.3 grade level. This reading level is reduced from the previous study in 2008 in which the overall mean was 10.6; however, the current sample grade level still exceeds recommended readability according to best practices. Despite a small body of literature on the readability of patient education materials related to hand surgery and other orthopedic issues over the last 7 years, readability was not dramatically improved in our current sample. Using health literacy as a framework, improvements in hand surgery patient education may result in better understanding and better outcomes for patients seeing hand surgeons. Improved understanding of patient education materials related to hand surgery may improve preventable negative outcomes that are clinically significant as well as contribute to improved quality of life for patients. Copyright © 2016 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

  1. Readability assessment of patient education materials on major otolaryngology association websites.

    Science.gov (United States)

    Eloy, Jean Anderson; Li, Shawn; Kasabwala, Khushabu; Agarwal, Nitin; Hansberry, David R; Baredes, Soly; Setzen, Michael

    2012-11-01

    Various otolaryngology associations provide Internet-based patient education material (IPEM) to the general public. However, this information may be written above the fourth- to sixth-grade reading level recommended by the American Medical Association (AMA) and National Institutes of Health (NIH). The purpose of this study was to assess the readability of otolaryngology-related IPEMs on various otolaryngology association websites and to determine whether they are above the recommended reading level for patient education materials. Analysis of patient education materials from 9 major otolaryngology association websites. The readability of 262 otolaryngology-related IPEMs was assessed with 8 numerical and 2 graphical readability tools. Averages were evaluated against national recommendations and between each source using analysis of variance (ANOVA) with post hoc Tukey's honestly significant difference (HSD) analysis. Mean readability scores for each otolaryngology association website were compared. Mean website readability scores using Flesch Reading Ease test, Flesch-Kincaid Grade Level, Coleman-Liau Index, SMOG grading, Gunning Fog Index, New Dale-Chall Readability Formula, FORCAST Formula, New Fog Count Test, Raygor Readability Estimate, and the Fry Readability Graph ranged from 20.0 to 57.8, 9.7 to 17.1, 10.7 to 15.9, 11.6 to 18.2, 10.9 to 15.0, 8.6 to 16.0, 10.4 to 12.1, 8.5 to 11.8, 10.5 to 17.0, and 10.0 to 17.0, respectively. ANOVA results indicate a significant difference (P < .05) between the websites for each individual assessment. The IPEMs found on all otolaryngology association websites exceed the recommended fourth- to sixth-grade reading level.

  2. How Readable Is BPH Treatment Information on the Internet? Assessing Barriers to Literacy in Prostate Health.

    Science.gov (United States)

    Koo, Kevin; Yap, Ronald L

    2017-03-01

    Information about benign prostatic hyperplasia (BPH) has become increasingly accessible on the Internet. Though the ability to find such material is encouraging, its readability and impact on informing patient decision making are not known. To evaluate the readability of Internet-based information about BPH in the context of website ownership and Health on the Net certification, three search engines were queried daily for 1 month with BPH-related keywords. Website ownership data and Health on the Net certification status were verified. Three readability analyses were performed: SMOG test, Dale-Chall readability formula, and Fry readability graph. An adjusted SMOG calculation was performed to reduce overestimation from medical jargon. After a total of 270 searches, 52 websites met inclusion criteria. Mean SMOG grade was 10.6 ( SD = 1.4) and 10.2 after adjustment. Mean Dale-Chall score was 9.1 ( SD = 0.6), or Grades 13 to 15. Mean Fry graph coordinates (173 syllables, 5.1 sentences) corresponded to Grade 15. Seven sites (13%) were at or below the average adult reading level based on SMOG; none of the sites qualified based on the other tests. Readability was significantly poorer for academic versus commercial sites and for Health on the Net-certified versus noncertified sites. In conclusion, online information about BPH treatment markedly exceeds the reading comprehension of most U.S. adults. Websites maintained by academic institutions and certified by the Health on the Net standard have more difficult readability. Efforts to improve literacy with respect to urological health should target content readability independent of reliability.

  3. [Global analysis of the readability of the informed consent forms used in public hospitals of Spain].

    Science.gov (United States)

    Mariscal-Crespo, M I; Coronado-Vázquez, M V; Ramirez-Durán, M V

    To analyse the readability of informed consent forms (ICF) used in Public Hospitals throughout Spain, with the aim of checking their function of providing comprehensive information to people who are making any health decision no matter where they are in Spain. A descriptive study was performed on a total of 11,339 ICF received from all over Spanish territory, of which 1617 ICF were collected from 4 web pages of Health Portal and the rest (9722) were received through email and/or telephone contact from March 2012 to February 2013. The readability level was studied using the Inflesz tool. A total of 372 ICF were selected and analysed using simple random sampling. The Inflesz scale and the Flesch-Szigriszt index were used to analyse the readability. The readability results showed that 62.4% of the ICF were rated as a "little difficult", the 23.4% as "normal", and the 13.4% were rated as "very difficult". The highest readability means using the Flesch index were scored in Andalusia with a mean of 56.99 (95% CI; 55.42-58.57) and Valencia with a mean of 51.93 (95% CI; 48.4-55.52). The lowest readability means were in Galicia with a mean of 40.77 (95% CI; 9.83-71.71) and Melilla, mean=41.82 (95% CI; 35.5-48.14). The readability level of Spanish informed consent forms must be improved because their scores using readability tools could not be classified in normal scales. Furthermore, there was very wide variability among Spanish ICF, which showed a lack of equity in information access among Spanish citizens. Copyright © 2017 SECA. Publicado por Elsevier España, S.L.U. All rights reserved.

  4. Machine Learning

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Machine learning, which builds on ideas in computer science, statistics, and optimization, focuses on developing algorithms to identify patterns and regularities in data, and using these learned patterns to make predictions on new observations. Boosted by its industrial and commercial applications, the field of machine learning is quickly evolving and expanding. Recent advances have seen great success in the realms of computer vision, natural language processing, and broadly in data science. Many of these techniques have already been applied in particle physics, for instance for particle identification, detector monitoring, and the optimization of computer resources. Modern machine learning approaches, such as deep learning, are only just beginning to be applied to the analysis of High Energy Physics data to approach more and more complex problems. These classes will review the framework behind machine learning and discuss recent developments in the field.

  5. Machine Translation

    Indian Academy of Sciences (India)

    Research Mt System Example: The 'Janus' Translating Phone Project. The Janus ... based on laptops, and simultaneous translation of two speakers in a dialogue. For more ..... The current focus in MT research is on using machine learning.

  6. [Readability and internet accessibility of informative documents for spinal cord injury patients in Spanish].

    Science.gov (United States)

    Bea-Muñoz, M; Medina-Sánchez, M; Flórez-García, M T

    2015-01-01

    Patients with spinal cord injuries and their carers have access to leaflets on Internet that they can use as educational material to complement traditional forms of education. The aim of this study is to evaluate the readability of informative documents in Spanish, obtained from Internet and aimed at patients with spinal cord injuries. A search was made with the Google search engine using the following key words: recommendation, advice, guide, manual, self-care, education and information, adding spinal cord injury, paraplegia and tetraplegia to each of the terms. We analyzed the first 50 results of each search. The readability of the leaflets was studied with the Flesch-Szigriszt index and the INFLESZ scale, both available on the INFLESZ program. Also indicated were year of publication, country and number of authors of the documents obtained. We obtained 16 documents, developed between 2001 and 2011. Readability oscillated between 43.34 (some-what difficult) and 62 (normal), with an average value of 51.56 (somewhat difficult). Only 4 pamphlets (25%) showed a Flesch-Szigriszt index of ≥ 55 (normal). There was no difference in readability by year, authors or country of publication. The readability of 75% of the documents studied was "somewhat difficult" according to the INFLESZ scale. These results coincide with previous studies, in both Spanish and English. If the readability of this type of documents is improved, it will be easier to achieve their educational goal.

  7. Readability Comparison of Pro- and Anti-Cancer Screening Online Messages in Japan

    Science.gov (United States)

    Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro

    2016-01-01

    Background: Cancer screening rates are lower in Japan than those in western countries. Health professionals publish pro-cancer screening messages on the internet to encourage audiences to undergo cancer screening. However, the information provided is often difficult to read for lay persons. Further, anti-cancer screening activists warn against cancer screening with messages on the Internet. We aimed to assess and compare the readability of pro- and anti-cancer screening online messages in Japan using a measure of readability. Methods: We conducted web searches at the beginning of September 2016 using two major Japanese search engines (Google.jp and Yahoo!.jp). The included websites were classified as “anti”, “pro”, or “neutral” depending on the claims, and “health professional” or “non-health professional” depending on the writers. Readability was determined using a validated measure of Japanese readability. Statistical analysis was conducted using two-way ANOVA. Results: In the total 159 websites analyzed, anti-cancer screening online messages were generally easier to read than pro-cancer screening online messages, Messages written by health professionals were more difficult to read than those written by non-health professionals. Claim × writer interaction was not significant. Conclusion: When health professionals prepare pro-cancer screening materials for publication online, we recommend they check for readability using readability assessment tools and improve text for easy comprehension when necessary. PMID:28125867

  8. Readability Assessment of Online Patient Education Material on Congestive Heart Failure

    Science.gov (United States)

    2017-01-01

    Background Online health information is being used more ubiquitously by the general population. However, this information typically favors only a small percentage of readers, which can result in suboptimal medical outcomes for patients. Objective The readability of online patient education materials regarding the topic of congestive heart failure was assessed through six readability assessment tools. Methods The search phrase “congestive heart failure” was employed into the search engine Google. Out of the first 100 websites, only 70 were included attending to compliance with selection and exclusion criteria. These were then assessed through six readability assessment tools. Results Only 5 out of 70 websites were within the limits of the recommended sixth-grade readability level. The mean readability scores were as follows: the Flesch-Kincaid Grade Level (9.79), Gunning-Fog Score (11.95), Coleman-Liau Index (15.17), Simple Measure of Gobbledygook (SMOG) index (11.39), and the Flesch Reading Ease (48.87). Conclusion Most of the analyzed websites were found to be above the sixth-grade readability level recommendations. Efforts need to be made to better tailor online patient education materials to the general population. PMID:28656111

  9. The Readability of AAOS Patient Education Materials: Evaluating the Progress Since 2008.

    Science.gov (United States)

    Roberts, Heather; Zhang, Dafang; Dyer, George S M

    2016-09-07

    The Internet has become a major resource for patients; however, patient education materials are frequently written at relatively high levels of reading ability. The purpose of this study was to evaluate the readability of patient education materials on the American Academy of Orthopaedic Surgeons (AAOS) web site. Readability scores were calculated for all patient education articles on the AAOS web site using 5 algorithms: Flesch Reading Ease, Flesch-Kincaid Grade Level, SMOG (Simple Measure of Gobbledygook) Grade, Coleman-Liau Index, and Gunning-Fog Index. The mean readability scores were compared across the anatomic categories to which they pertained. Using a liberal measure of readability, the Flesch-Kincaid Grade Level, 3.9% of articles were written at or below the recommended sixth-grade reading level, and 84% of the articles were written above the eighth-grade reading level. Articles in the present study had a lower mean Flesch-Kincaid Grade Level than those available in 2008 (p readability levels of AAOS articles are higher than generally recommended. Although the mean Flesch-Kincaid Grade Level was lower in the present study than it was in 2008, a need remains to improve the readability of AAOS patient education articles. Ensuring that online patient education materials are written at an appropriate reading grade level would be expected to improve physician-patient communication. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

  10. Readability and suitability assessment of patient education materials in rheumatic diseases.

    Science.gov (United States)

    Rhee, Rennie L; Von Feldt, Joan M; Schumacher, H Ralph; Merkel, Peter A

    2013-10-01

    Web-based patient education materials and printed pamphlets are frequently used by providers to inform patients about their rheumatic disease. Little attention has been given to the readability and appropriateness of patient materials. The objective of this study was to examine the readability and suitability of commonly used patient education materials for osteoarthritis (OA), rheumatoid arthritis, systemic lupus erythematosus, and vasculitis. Five or 6 popular patient resources for each disease were chosen for evaluation. Readability was measured using the Flesch-Kincaid reading grade level and suitability was determined by the Suitability Assessment of Materials (SAM), a score that considers characteristics such as content, graphics, layout/topography, and cultural appropriateness. Three different reviewers rated the SAM score and means were used in the analysis. Twenty-three resources written on the 4 diseases were evaluated. The education material for all 4 diseases studied had readability above the eighth-grade level and readability did not differ among the diseases. Only 5 of the 23 resources received superior suitability scores, and 3 of these 5 resources were written for OA. All 4 diseases received adequate suitability scores, with OA having the highest mean suitability score. Most patient education materials for rheumatic diseases are written at readability levels above the recommended sixth-grade reading level and have only adequate suitability. Developing more appropriate educational resources for patients with rheumatic diseases may improve patient comprehension. Copyright © 2013 by the American College of Rheumatology.

  11. Readability of American online patient education materials in urologic oncology: a need for simple communication.

    Science.gov (United States)

    Pruthi, Amanda; Nielsen, Matthew E; Raynor, Mathew C; Woods, Michael E; Wallen, Eric M; Smith, Angela B

    2015-02-01

    To determine the readability levels of reputable cancer and urologic Web sites addressing bladder, prostate, kidney, and testicular cancers. Online patient education materials (PEMs) for bladder, prostate, kidney, and testicular malignancies were evaluated from the American Cancer Society, American Society of Clinical Oncology, National Cancer Institute, Urology Care Foundation, Bladder Cancer Advocacy Network, Prostate Cancer Foundation, Kidney Cancer Association, and Testicular Cancer Resource Center. Grade level was determined using several readability indices, and analyses were performed on the basis of cancer type, Web site, and content area (general, causes, risk factors and prevention, diagnosis and staging, treatment, and post-treatment). Estimated grade level of online PEMs ranged from 9.2 to 14.2 with an overall mean of 11.7. Web sites for kidney cancer had the least difficult readability (11.3) and prostate cancer had the most difficult readability (12.1). Among specific Web sites, the most difficult readability levels were noted for the Urology Care Foundation Web site for bladder and prostate cancer and the Kidney Cancer Association and Testicular Cancer Resource Center for kidney and testes cancer. Readability levels within content areas varied on the basis of the disease and Web site. Online PEMs in urologic oncology are written at a level above the average American reader. Simplification of these resources is necessary to improve patient understanding of urologic malignancy. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Punctuation as readability and textuality factor in technical discourse

    Directory of Open Access Journals (Sweden)

    Carmen Sancho Guinda

    2002-04-01

    Full Text Available This paper studies the incidence of punctuation on the reading comprehension of technical discourse and its role as a factor of textuality. Starting out from the notions of textuality and punctuation functions formulated by different linguistic approaches, an analysis has been made to quantify the decoding skills and punctuating competence of 60 Aeronautical Engineering students, as well as to determine the nature and effects of their punctuation errors. The survey has been focused on the Full Stop, the comma and the hyphen due to their highly conflicting uses as regards the identification of immediate sentence constituents and semantic relationships. The results obtained suggest that most students have a poor knowledge of punctuation rules and little awareness of punctuation as a textual elementaffecting readability. Errors are in the main related to comma use and produced by transference, either of Spanish punctuating habits into English, or of individual prosodic patterns into writing, while meaning appears to be the prevailing punctuating criterion over sound and syntax. Punctuation proves an effective tool for the anticipation of implicit meanings and an untapped resource in the teaching of the diverse communicative and stylistic possibilities offered by technical texts.

  13. Analysis of factors temporarily impacting traffic sign readability

    Directory of Open Access Journals (Sweden)

    Majid Khalilikhah

    2016-10-01

    Full Text Available Traffic sign readability can be affected by the existence of dirt on traffic sign faces. However, among damaged signs, dirty traffic signs are unique since their damage is not permanent and they just can be cleaned instead of replaced. This study aimed to identify the most important factors contributing to traffic sign dirt. To do so, a large number of traffic signs in Utah were measured by deploying a vehicle instrumented with mobile LiDAR imaging and digital photolog technologies. Each individual daytime digital image was inspected for dirt. Location and climate observations obtained from official sources were compiled using ArcGIS throughout the process. To identify contributing factors to traffic sign dirt, the chi-square test was employed. To analyze the data and rank all of the factors based on their importance to the sign dirt, Random forests statistical model was utilized. After analyzing the data, it can be concluded that ground elevation, sign mount height, and air pollution had the highest effect on making traffic signs dirty. The findings of this investigation assist transportation agencies in determining traffic signs with a higher likelihood of sign dirt. In this way, agencies would schedule to clean such traffic signs more frequently.

  14. Readability and comprehension of self-report binge eating measures.

    Science.gov (United States)

    Richards, Lauren K; McHugh, R Kathryn; Pratt, Elizabeth M; Thompson-Brenner, Heather

    2013-04-01

    The validity of self-report binge eating instruments among individuals with limited literacy is uncertain. This study aims to evaluate reading grade level and multiple domains of comprehension of 13 commonly used self-report assessments of binge eating for use in low-literacy populations. We evaluated self-report binge eating measures with respect to reading grade levels, measure length, formatting and linguistic problems. All measures were written at a reading grade level higher than is recommended for patient materials (above the 5th to 6th grade level), and contained several challenging elements related to comprehension. Correlational analyses suggested that readability and comprehension elements were distinct contributors to measure difficulty. Individuals with binge eating who have low levels of educational attainment or limited literacy are often underrepresented in measure validation studies. Validity of measures and accurate assessment of symptoms depend on an individual's ability to read and comprehend instructions and items, and these may be compromised in populations with lower levels of literacy. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Machine Learning Method Applied in Readout System of Superheated Droplet Detector

    Science.gov (United States)

    Liu, Yi; Sullivan, Clair Julia; d'Errico, Francesco

    2017-07-01

    Direct readability is one advantage of superheated droplet detectors in neutron dosimetry. Utilizing such a distinct characteristic, an imaging readout system analyzes image of the detector for neutron dose readout. To improve the accuracy and precision of algorithms in the imaging readout system, machine learning algorithms were developed. Deep learning neural network and support vector machine algorithms are applied and compared with generally used Hough transform and curvature analysis methods. The machine learning methods showed a much higher accuracy and better precision in recognizing circular gas bubbles.

  16. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  17. Attention: A Machine Learning Perspective

    DEFF Research Database (Denmark)

    Hansen, Lars Kai

    2012-01-01

    We review a statistical machine learning model of top-down task driven attention based on the notion of ‘gist’. In this framework we consider the task to be represented as a classification problem with two sets of features — a gist of coarse grained global features and a larger set of low...

  18. Machine Protection

    International Nuclear Information System (INIS)

    Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg

    2012-01-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012

  19. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  20. Machine Protection

    CERN Document Server

    Zerlauth, Markus; Wenninger, Jörg

    2012-01-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

  1. Machine Protection

    Energy Technology Data Exchange (ETDEWEB)

    Zerlauth, Markus; Schmidt, Rüdiger; Wenninger, Jörg [European Organization for Nuclear Research, Geneva (Switzerland)

    2012-07-01

    The present architecture of the machine protection system is being recalled and the performance of the associated systems during the 2011 run will be briefly summarized. An analysis of the causes of beam dumps as well as an assessment of the dependability of the machine protection systems (MPS) itself is being presented. Emphasis will be given to events that risked exposing parts of the machine to damage. Further improvements and mitigations of potential holes in the protection systems will be evaluated along with their impact on the 2012 run. The role of rMPP during the various operational phases (commissioning, intensity ramp up, MDs...) will be discussed along with a proposal for the intensity ramp up for the start of beam operation in 2012.

  2. Machine vision systems using machine learning for industrial product inspection

    Science.gov (United States)

    Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

    2002-02-01

    Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

  3. Readability of Spine-Related Patient Education Materials From Leading Orthopedic Academic Centers.

    Science.gov (United States)

    Ryu, Justine H; Yi, Paul H

    2016-05-01

    Cross-sectional analysis of online spine-related patient education materials from leading academic centers. To assess the readability levels of spine surgery-related patient education materials available on the websites of academic orthopedic surgery departments. The Internet is becoming an increasingly popular resource for patient education. Yet many previous studies have found that Internet-based orthopedic-related patient education materials from subspecialty societies are written at a level too difficult for the average American; however, no prior study has assessed the readability of spine surgery-related patient educational materials from leading academic centers. All spine surgery-related articles from the online patient education libraries of the top five US News & World Report-ranked orthopedic institutions were assessed for readability using the Flesch-Kincaid (FK) readability test. Mean readability levels of articles amongst the five academic institutions and articles were compared. We also determined the number of articles with readability levels at or below the recommended sixth- or eight-grade levels. Intraobserver and interobserver reliability of readability assessment were assessed. A total of 122 articles were reviewed. The mean overall FK grade level was 11.4; the difference in mean FK grade level between each department varied significantly (range, 9.3-13.4; P Online patient education materials related to spine from academic orthopedic centers are written at a level too high for the average patient, consistent with spine surgery-related patient education materials provided by the American Academy of Orthopaedic Surgeons and spine subspecialty societies. This study highlights the potential difficulties patients might have in reading and comprehending the information in publicly available education materials related to spine. N/A.

  4. Readability levels of health pamphlets distributed in hospitals and health centres in Athens, Greece.

    Science.gov (United States)

    Kondilis, B K; Akrivos, P D; Sardi, T A; Soteriades, E S; Falagas, M E

    2010-10-01

    Health literacy is important in the medical and social sciences due to its impact on behavioural and health outcomes. Nevertheless, little is known about it in Greece, including patients' level of understanding health brochures and pamphlets distributed in Greek hospitals and clinics. Observational study in the greater metropolitan area of Athens, Greece. Pamphlets and brochures written in the Greek language were collected from 17 hospitals and healthcare centres between the spring and autumn of 2006. Readability of pamphlets using the Flesch-Kincaid, Simple Measure of Gobbledygook (SMOG) and Fog methods was calculated based on a Greek readability software. Out of 70 pamphlets collected from 17 hospitals, 37 pamphlets met the criteria for the study. The average readability level of all scanned pamphlets was ninth to 10th grade, corresponding to a readability level of 'average'. A highly significant difference (PPamphlets from private hospitals were one grade more difficult than those from public hospitals. Approximately 43.7% of the Greek population aged ≥20 years would not be able to comprehend the available pamphlets, which were found to have an average readability level of ninth to 10th grade. Further research examining readability levels in the context of health literacy in Greece is warranted. This effort paves the way for additional research in the field of readability levels of health pamphlets in the Greek language, the sources of health information, and the level of understanding of key health messages by the population. Copyright © 2010 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  5. Teletherapy machine

    International Nuclear Information System (INIS)

    Panyam, Vinatha S.; Rakshit, Sougata; Kulkarni, M.S.; Pradeepkumar, K.S.

    2017-01-01

    Radiation Standards Section (RSS), RSSD, BARC is the national metrology institute for ionizing radiation. RSS develops and maintains radiation standards for X-ray, beta, gamma and neutron radiations. In radiation dosimetry, traceability, accuracy and consistency of radiation measurements is very important especially in radiotherapy where the success of patient treatment is dependent on the accuracy of the dose delivered to the tumour. Cobalt teletherapy machines have been used in the treatment of cancer since the early 1950s and India had its first cobalt teletherapy machine installed at the Cancer Institute, Chennai in 1956

  6. Readability of HIV/AIDS educational materials: the role of the medium of communication, target audience, and producer characteristics.

    Science.gov (United States)

    Wells, J A

    1994-12-01

    The reading difficulty of many HIV/AIDS brochures and pamphlets limits their effectiveness. This analysis addresses correlates of readability in 136 HIV/AIDS educational items. Readability is measured using the SMOG Index. The medium of communication is significantly related to readability: comic books and brochures are, on average, more readable than books and pamphlets (10.9 versus 11.9). The target audience also differentiates readability. Materials for HIV antibody test seekers, the general community, and sexually active adults have a more difficult reading grade, averaging 12.1, whereas materials for ethnic minorities average a more readable 9.2. The producer organization's type and location are unrelated to readability, but an AIDS-specific organizational focus correlates with better readability (grade 10.8 vs. 11.8). These findings remain significant in multivariate analysis. The results indicate that brochures and comics are more likely to be comprehended by low-literacy populations, that an understanding of the literacy of target audiences is needed to produce materials with appropriate reading levels, and that policies to influence producer organizations may result in the creation of more readable materials.

  7. Design of a 10 MJ fast discharging homopolar machine

    International Nuclear Information System (INIS)

    Stillwagon, R.E.; Thullen, P.

    1977-01-01

    The design of a fast discharging homopolar machine is described. The machine capacity is 10 MJ with a 30 ms energy delivery time. The salient features of the machine are relatively high terminal voltage, fast discharge time, high power density and high efficiency. The machine integrates several new technologies including high surface speeds, large superconducting magnets and current collection at high density

  8. Machine testning

    DEFF Research Database (Denmark)

    De Chiffre, Leonardo

    This document is used in connection with a laboratory exercise of 3 hours duration as a part of the course GEOMETRICAL METROLOGY AND MACHINE TESTING. The exercise includes a series of tests carried out by the student on a conventional and a numerically controled lathe, respectively. This document...

  9. Readability assessment of online patient education materials provided by the European Association of Urology.

    Science.gov (United States)

    Betschart, Patrick; Zumstein, Valentin; Bentivoglio, Maico; Engeler, Daniel; Schmid, Hans-Peter; Abt, Dominik

    2017-12-01

    To assess the readability of the web-based patient education material provided by the European Association of Urology. English patient education materials (PEM) as available in May 2017 were obtained from the EAU website. Each topic was analyzed separately using six well-established readability assessment tools, including Flesch-Kincaid Grade Level (FKGL), SMOG Grade Level (SMOG), Coleman-Liau Index (CLI), Gunning Fog Index (GFI), Flesch Reading Ease Formula (FRE) and Fry Readability Graph (FRG). A total of 17 main topics were identified of which separate basic and in-depth information is provided for 14 topics. Calculation of grade levels (FKGL, SMOG, CLI, GFI) showed readability scores of 7th-13th grade for basic information, 8th-15th grade for in-depth information and 7th-15th grade for single PEM. Median FRE score was 54 points (range 45-65) for basic information and 56 points (41-64) for in-depth information. The FRG as a graphical assessment revealed only 13 valid results with an approximate 8th-17th grade level. The EAU provides carefully worked out PEM for 17 urological topics. Although improved readability compared to similar analyses was found, a simplification of certain chapters might be helpful to facilitate better patient understanding.

  10. Quality and readability assessment of websites related to recurrent respiratory papillomatosis.

    Science.gov (United States)

    San Giorgi, Michel R M; de Groot, Olivier S D; Dikkers, Frederik G

    2017-10-01

    Recurrent respiratory papillomatosis (RRP) is a rare disease for which a limited number of information sources for patients exist. The role of the Internet in the patient-physician relationship is increasing. More and more patients search for online health information, which should be of good quality and easy readable. The study aim was to investigate the quality and readability of English online health information about RRP. Quality and readability assessment of online information. Relevant information was collected using three different search engines and seven different search terms. Quality was assessed with the DISCERN instrument. The Flesch Reading Ease Score (FRES) and average grade level (AGL) were determined to measure readability of the English websites. Fifty-one English websites were included. The mean DISCERN score of the websites is 28.1 ± 9.7 (poor quality); the mean FRES is 41.3 ± 14.9 (difficult to read); and the mean AGL is 12.6 ± 2.3. The quality and readability of English websites about RRP is alarmingly poor. NA. Laryngoscope, 127:2293-2297, 2017. © 2017 The Authors The Laryngoscope published by Wiley Periodicals, Inc. on behalf of American Laryngological, Rhinological and Otological Society Inc, “The Triological Society” and American Laryngological Association (ALA).

  11. Informed consent recall and comprehension in orthodontics: traditional vs improved readability and processability methods.

    Science.gov (United States)

    Kang, Edith Y; Fields, Henry W; Kiyak, Asuman; Beck, F Michael; Firestone, Allen R

    2009-10-01

    Low general and health literacy in the United States means informed consent documents are not well understood by most adults. Methods to improve recall and comprehension of informed consent have not been tested in orthodontics. The purposes of this study were to evaluate (1) recall and comprehension among patients and parents by using the American Association of Orthodontists' (AAO) informed consent form and new forms incorporating improved readability and processability; (2) the association between reading ability, anxiety, and sociodemographic variables and recall and comprehension; and (3) how various domains (treatment, risk, and responsibility) of information are affected by the forms. Three treatment groups (30 patient-parent pairs in each) received an orthodontic case presentation and either the AAO form, an improved readability form (MIC), or an improved readability and processability (pairing audio and visual cues) form (MIC + SS). Structured interviews were transcribed and coded to evaluate recall and comprehension. Significant relationships among patient-related variables and recall and comprehension explained little of the variance. The MIC + SS form significantly improved patient recall and parent recall and comprehension. Recall was better than comprehension, and parents performed better than patients. The MIC + SS form significantly improved patient treatment comprehension and risk recall and parent treatment recall and comprehension. Patients and parents both overestimated their understanding of the materials. Improving the readability of consent materials made little difference, but combining improved readability and processability benefited both patients' recall and parents' recall and comprehension compared with the AAO form.

  12. Enhancing the Radiologist-Patient Relationship through Improved Communication: A Quantitative Readability Analysis in Spine Radiology.

    Science.gov (United States)

    Hansberry, D R; Donovan, A L; Prabhu, A V; Agarwal, N; Cox, M; Flanders, A E

    2017-06-01

    More than 75 million Americans have less than adequate health literacy skills according to the National Center for Education Statistics. Readability scores are used as a measure of how well populations read and understand patient education materials. The purpose of this study was to assess the readability of Web sites dedicated to patient education for radiologic spine imaging and interventions. Eleven search terms relevant to radiologic spine imaging were searched on the public Internet, and the top 10 links for each term were collected and analyzed to determine readability scores by using 10 well-validated quantitative readability assessments from patient-centered education Web sites. The search terms included the following: x-ray spine, CT spine, MR imaging spine, lumbar puncture, kyphoplasty, vertebroplasty, discogram, myelogram, cervical spine, thoracic spine, and lumbar spine. Collectively, the 110 articles were written at an 11.3 grade level (grade range, 7.1-16.9). None of the articles were written at the American Medical Association and National Institutes of Health recommended 3rd-to-7th grade reading levels. The vertebroplasty articles were written at a statistically significant ( P readability scores of the articles and the American Medical Association and National Institutes of Health recommended guidelines, it is likely that many patients do not fully benefit from these resources. © 2017 by American Journal of Neuroradiology.

  13. Readability of Healthcare Literature for Gastroparesis and Evaluation of Medical Terminology in Reading Difficulty.

    Science.gov (United States)

    Meillier, Andrew; Patel, Shyam

    2017-02-01

    Gastroparesis is a chronic condition that can be further enhanced with patient understanding. Patients' education resources on the Internet have become increasingly important in improving healthcare literacy. We evaluated the readability of online resources for gastroparesis and the influence by medical terminology. Google searches were performed for "gastroparesis", "gastroparesis patient education material" and "gastroparesis patient information". Following, all medical terminology was determined if included on Taber's Medical Dictionary 22nd Edition. The medical terminology was replaced independently with "help" and "helping". Web resources were analyzed with the Readability Studio Professional Edition (Oleander Solutions, Vandalia, OH) using 10 different readability scales. The average of the 26 patient education resources was 12.7 ± 1.8 grade levels. The edited "help" group had 6.6 ± 1.0 and "helping" group had 10.4 ± 2.1 reading levels. In comparing the three groups, the "help" and "helping" groups had significantly lower readability levels (P Medical Association. Medical terminology was shown to be the cause for this elevated readability level with all, but four resources within the recommended grade levels following word replacement.

  14. Calisthenics with Words: The Effect of Readability and Investor Sophistication on Investors’ Performance Judgment

    Directory of Open Access Journals (Sweden)

    Xiao Carol Cui

    2016-01-01

    Full Text Available Since the 1990s, the SEC has advocated for financial disclosures to be in “plain English” so that they would be more readable and informative. Past research has shown that high readability is related to more extreme investor judgments of firm performance. Processing fluency is the prevalent theory to explain this: higher readability increases the investor’s subconscious reliance on the disclosure, so positive (negative news leads to more positive (negative judgments. The relationship may not be so simple, though: drawing on research from cognitive psychology, I predict and find that investor financial literacy simultaneously influences investor decision-making, and that it has an interactive effect with readability. When presented with financial disclosure containing conflicting financial information, investors with higher financial literacy make more negative judgments than investors with low financial literacy when the disclosure is easy to read, but the effect becomes insignificant when the disclosure becomes difficult to read. This effect is moderated by a comprehension gap between the two investor groups. Financial literacy and readability interact to impact both how and how well the investor processes financial information.

  15. Readability assessment of Internet-based patient education materials related to endoscopic sinus surgery.

    Science.gov (United States)

    Cherla, Deepa V; Sanghvi, Saurin; Choudhry, Osamah J; Liu, James K; Eloy, Jean Anderson

    2012-08-01

    Numerous professional societies, clinical practices, and hospitals provide Internet-based patient education materials (PEMs) to the general public, but not all of this information is written at a reading level appropriate for the average patient. The National Institutes of Health and the US Department of Health and Human Services recommend that PEMs be written at or below the sixth-grade level. Our purpose was to assess the readability of endoscopic sinus surgery (ESS)-related PEMs available on the Internet and compare readability levels of PEMs provided by three sources: professional societies, clinical practices, and hospitals. A descriptive and correlational design was used for this study. The readability of 31 ESS-related PEMs was assessed with four different readability indices: Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (Gunning FOG). Averages were evaluated against national recommendations and between each source using analysis of variance and t tests. The majority of PEMs (96.8%) were written above the recommended sixth-grade reading level, based on FKGL (P Internet-based PEMs related to ESS, regardless of source type, were written well above the recommended sixth-grade level. Materials from the hospitals/university-affiliated websites had lower readability scores, but were still above recommended levels. Web-based PEMs pertaining to ESS should be written with the average patient in mind. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

  16. Readability of Patient Education Materials From the Web Sites of Orthopedic Implant Manufacturers.

    Science.gov (United States)

    Yi, Meghan M; Yi, Paul H; Hussein, Khalil I; Cross, Michael B; Della Valle, Craig J

    2017-12-01

    Prior studies indicate that orthopedic patient education materials are written at a level that is too high for the average patient. The purpose of this study was to assess the readability of online patient education materials provided by orthopedic implant manufacturers. All patient education articles available in 2013 from the web sites of the 5 largest orthopedic implant manufacturers were identified. Each article was evaluated with the Flesch-Kincaid (FK) readability test. The number of articles with readability ≤ the eighth-grade level (average reading ability of US adults) and the sixth-grade level (recommended level for patient education materials) was determined. Mean readability levels of each company's articles were compared using analysis of variance (significance set at P articles were reviewed from the 5 largest implant manufacturers. The mean overall FK grade level was 10.9 (range, 3.8-16.1). Only 58 articles (10%) were written ≤ the eighth-grade level, and only 13 (2.2%) were ≤ the sixth-grade level. The mean FK grade level was significantly different among groups (Smith & Nephew = 12.0, Stryker = 11.6, Biomet = 11.3, DePuy = 10.6, Zimmer = 10.1; P education materials from implant manufacturers are written at a level too high to be comprehended by the average patient. Future efforts should be made to improve the readability of orthopedic patient education materials. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Machine rates for selected forest harvesting machines

    Science.gov (United States)

    R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

    2002-01-01

    Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

  18. Improving Layman Readability of Clinical Narratives with Unsupervised Synonym Replacement.

    Science.gov (United States)

    Moen, Hans; Peltonen, Laura-Maria; Koivumäki, Mikko; Suhonen, Henry; Salakoski, Tapio; Ginter, Filip; Salanterä, Sanna

    2018-01-01

    We report on the development and evaluation of a prototype tool aimed to assist laymen/patients in understanding the content of clinical narratives. The tool relies largely on unsupervised machine learning applied to two large corpora of unlabeled text - a clinical corpus and a general domain corpus. A joint semantic word-space model is created for the purpose of extracting easier to understand alternatives for words considered difficult to understand by laymen. Two domain experts evaluate the tool and inter-rater agreement is calculated. When having the tool suggest ten alternatives to each difficult word, it suggests acceptable lay words for 55.51% of them. This and future manual evaluation will serve to further improve performance, where also supervised machine learning will be used.

  19. Beyond Readability: Investigating Coherence of Clinical Text for Consumers

    Science.gov (United States)

    Hetzel, Scott; Dalrymple, Prudence; Keselman, Alla

    2011-01-01

    Background A basic tenet of consumer health informatics is that understandable health resources empower the public. Text comprehension holds great promise for helping to characterize consumer problems in understanding health texts. The need for efficient ways to assess consumer-oriented health texts and the availability of computationally supported tools led us to explore the effect of various text characteristics on readers’ understanding of health texts, as well as to develop novel approaches to assessing these characteristics. Objective The goal of this study was to compare the impact of two different approaches to enhancing readability, and three interventions, on individuals’ comprehension of short, complex passages of health text. Methods Participants were 80 university staff, faculty, or students. Each participant was asked to “retell” the content of two health texts: one a clinical trial in the domain of diabetes mellitus, and the other typical Visit Notes. These texts were transformed for the intervention arms of the study. Two interventions provided terminology support via (1) standard dictionary or (2) contextualized vocabulary definitions. The third intervention provided coherence improvement. We assessed participants’ comprehension of the clinical texts through propositional analysis, an open-ended questionnaire, and analysis of the number of errors made. Results For the clinical trial text, the effect of text condition was not significant in any of the comparisons, suggesting no differences in recall, despite the varying levels of support (P = .84). For the Visit Note, however, the difference in the median total propositions recalled between the Coherent and the (Original + Dictionary) conditions was significant (P = .04). This suggests that participants in the Coherent condition recalled more of the original Visit Notes content than did participants in the Original and the Dictionary conditions combined. However, no difference was seen

  20. Remote filter handling machine for Sizewell B

    International Nuclear Information System (INIS)

    Barker, D.

    1993-01-01

    Two Filter Handling machines (FHM) have been supplied to Nuclear Electric plc for use at Sizewell B Power Station. These machines have been designed and built following ALARP principles with the functional objective being to remove radioactive filter cartridges from a filter housing and replace them with clean filter cartridges. Operation of the machine is achieved by the prompt of each distinct task via an industrial computer or the prompt of a full cycle using the automatic mode. The design of the machine features many aspects demonstrating ALARP while keeping the machine simple, robust and easy to maintain. (author)

  1. Man machine interaction for operator information systems : a general purpose display package on PC/AT

    International Nuclear Information System (INIS)

    Chandra, A.K.; Dubey, B.P.; Deshpande, S.V.; Vaidya, U.W.; Khandekar, A.B.

    1991-01-01

    Several operator information systems for nuclear plants have been developed at Reactor Control Division of BARC and these have involved extensive operator interaction to extract the maximum information from the systems. Each of these systems used a different scheme for operator interaction. A composite package has now been developed on PC/AT with EGA/VGA for use with any system to obviate the necessity to develop new software for each project. This permits information to be displayed in various formats viz. trend and history curves, tabular data, bar graphs and core matrix (both for 235 and 500 MWe cores). It also allows data to be printed and plotted using multi colour plotter. This package thus integrates all the features of the earlier systems. It also integrates the operator interaction scheme. It uses window based pull down menus to select parameters to be fed into a particular display format. Within any display format the operator has significant flexibility to modify the selected parameters using context dependent soft keys. The package also allows data to be retrieved in machine readable form. This report describes the various user friendly functions implemented and also the design of the system software. (author). 1 tab., 10 fig., 3 refs

  2. Electric machines

    CERN Document Server

    Gross, Charles A

    2006-01-01

    BASIC ELECTROMAGNETIC CONCEPTSBasic Magnetic ConceptsMagnetically Linear Systems: Magnetic CircuitsVoltage, Current, and Magnetic Field InteractionsMagnetic Properties of MaterialsNonlinear Magnetic Circuit AnalysisPermanent MagnetsSuperconducting MagnetsThe Fundamental Translational EM MachineThe Fundamental Rotational EM MachineMultiwinding EM SystemsLeakage FluxThe Concept of Ratings in EM SystemsSummaryProblemsTRANSFORMERSThe Ideal n-Winding TransformerTransformer Ratings and Per-Unit ScalingThe Nonideal Three-Winding TransformerThe Nonideal Two-Winding TransformerTransformer Efficiency and Voltage RegulationPractical ConsiderationsThe AutotransformerOperation of Transformers in Three-Phase EnvironmentsSequence Circuit Models for Three-Phase Transformer AnalysisHarmonics in TransformersSummaryProblemsBASIC MECHANICAL CONSIDERATIONSSome General PerspectivesEfficiencyLoad Torque-Speed CharacteristicsMass Polar Moment of InertiaGearingOperating ModesTranslational SystemsA Comprehensive Example: The ElevatorP...

  3. Charging machine

    International Nuclear Information System (INIS)

    Medlin, J.B.

    1976-01-01

    A charging machine for loading fuel slugs into the process tubes of a nuclear reactor includes a tubular housing connected to the process tube, a charging trough connected to the other end of the tubular housing, a device for loading the charging trough with a group of fuel slugs, means for equalizing the coolant pressure in the charging trough with the pressure in the process tubes, means for pushing the group of fuel slugs into the process tube and a latch and a seal engaging the last object in the group of fuel slugs to prevent the fuel slugs from being ejected from the process tube when the pusher is removed and to prevent pressure liquid from entering the charging machine. 3 claims, 11 drawing figures

  4. Homopolar machine design

    International Nuclear Information System (INIS)

    Thullen, P.

    1978-01-01

    A general conceptual design for a disc-type homopolar machine is presented. This machine uses a superconducting, air-core, solenoidal field winding with a peak field of 8 T. A total energy of 500 MJ is stored in two counter-rotating disc rotors that operate at a surface speed of 200 m/s. Terminal voltages of 500 to 2000 V are obtained over the range of designs studied. Brush systems to collect 3 MA are investigated. Various brush materials are discussed to determine their usefulness in this application. Sufficient information on operating characteristics in high-power applications is only available for copper-graphite brushes. The use of sliding brushes for terminal voltage regulation is discussed. This feature cannot provide a great deal of flexibility in this particular application although it may be useful during start-up. The brush system is the most demanding feature of this design. Few systems in the million ampere range have been constructed, consequently, it is not possible to predict the behavior of this brush system with great certainty. A detailed design of the brushes should be undertaken. It is estimated that the cost of such a machine will range from 0.5 to 1.5 cents per joule

  5. Web-based information on the treatment of oral leukoplakia - quality and readability.

    Science.gov (United States)

    Wiriyakijja, Paswach; Fedele, Stefano; Porter, Stephen; Ni Riordain, Richeal

    2016-09-01

    To categorise the content and assess the quality and readability of the online information regarding the treatment for oral leukoplakia. An online search using the term 'leukoplakia treatment' was carried out on 8th June 2015 using the Google search engine. The content, quality and readability of the first 100 sites were explored. The quality of the web information was assessed using the following tools, the DISCERN instrument and the Journal of the American Medical Association (JAMA) benchmarks for website analysis and the HON seal. Readability was assessed via the Flesch Reading Ease Score. The search strategy generated 357 000 sites on the Google search engine. Due to duplicate links, non-operating links and irrelevant links, a total of 47 of the first 100 websites were included in this study. The mean overall rating achieved by included websites using the DISCERN instrument was 2.3. With regard to the JAMA benchmarks, the vast majority of examined websites (95.7%) completely fulfilled the disclosure benchmark and less than 50% of included websites met the three remaining criteria. A mean total readability score of 47.5 was recorded with almost 90% of websites having a readability level ranging from fairly difficult to very difficult. Based on this study, the online health information regarding oral leukoplakia has challenging readability with content of questionable accuracy. As patients often search for health information online, it would be prudent for clinicians to highlight the caution with which online information should be interpreted. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  6. Readability of informed consent forms in clinical trials conducted in a skin research center

    Science.gov (United States)

    Samadi, Aniseh; Asghari, Fariba

    2016-01-01

    Obtaining informed consents is one of the most fundamental principles in conducting a clinical trial. In order for the consent to be informed, the patient must receive and comprehend the information appropriately. Complexity of the consent form is a common problem that has been shown to be a major barrier to comprehension for many patients. The objective of this study was to assess the readability of different templates of informed consent forms (ICFs) used in clinical trials in the Center for Research and Training in Skin Diseases and Leprosy (CRTSDL), Tehran, Iran. This study was conducted on ICFs of 45 clinical trials of the CRTSDL affiliated with Tehran University of Medical Sciences. ICFs were tested for reading difficulty, using the readability assessments formula adjusted for the Persian language including the Flesch–Kincaid reading ease score, Flesch–Kincaid grade level, and Gunning fog index. Mean readability score of the whole text of ICFs as well as their 7 main information parts were calculated. The mean ± SD Flesch Reading Ease score for all ICFs was 31.96 ± 5.62 that is in the difficult range. The mean ± SD grade level was calculated as 10.71 ± 1.8 (8.23–14.09) using the Flesch–Kincaid formula and 14.64 ± 1.22 (12.67–18.27) using the Gunning fog index. These results indicate that the text is expected to be understandable for an average student in the 11th grade, while the ethics committee recommend grade level 8 as the standard readability level for ICFs. The results showed that the readability scores of ICFs assessed in our study were not in the acceptable range. This means they were too complex to be understood by the general population. Ethics committees must examine the simplicity and readability of ICFs used in clinical trials. PMID:27471590

  7. Cauda equina syndrome: assessing the readability and quality of patient information on the Internet.

    Science.gov (United States)

    O'Neill, Shane Ciaran; Baker, Joseph Frederick; Fitzgerald, Conall; Fleming, Christina; Rowan, Fiachra; Byrne, Damien; Synnott, Keith

    2014-05-01

    A readability and quality control Internet-based study using recognized quality scoring systems. To assess the readability and quality of Internet information relating to cauda equina syndrome accessed through common search engines. Access to health-related Internet information has increased dramatically during the past decade. A significant proportion of this information has been demonstrated to be set at too high a level for general comprehension. Despite this, searching for health-related information is now the third most popular online activity. A total of 125 cauda equina syndrome Web sites were analyzed from the 5 most popular Internet search engines: Google, Bing, Yahoo, Ask, and AOL. Web site authorship was classified: academic, physician, medico-legal, commercial, or discussion/social media. Readability of each Web site was assessed using the Flesch Reading Ease score, the Flesch-Kincaid grade level, and the Gunning Fog Index. Quality was calculated using the DISCERN instrument and The Journal of the American Medical Association benchmark criteria. The presence of HON-code certification was also assessed. Fifty-two individual Web sites were identified and assessed. The majority of Web sites were academic or physician compiled (53.8%; 28/52); however, a significant minority of Web sites were medico-legal related (19.2%; 10/52). Just 13.5% (7/52) of Web sites were at or below the recommended sixth-grade readability level. HON-code certified Web sites achieved significantly greater DISCERN (P = 0.0006) and The Journal of the American Medical Association (P = 0.0002) scores. Internet information relating to cauda equina syndrome is of variable quality and largely set at an inappropriate readability level. Given this variability in quality, health care providers should direct patients to known sources of reliable, readable online information. Identification of reliable sources may be aided by known markers of quality such as HON-code certification.

  8. Assessment of readability, understandability, and completeness of pediatric hospital medicine discharge instructions.

    Science.gov (United States)

    Unaka, Ndidi I; Statile, Angela; Haney, Julianne; Beck, Andrew F; Brady, Patrick W; Jerardi, Karen E

    2017-02-01

    The average American adult reads at an 8th-grade level. Discharge instructions written above this level might increase the risk of adverse outcomes for children as they transition from hospital to home. We conducted a cross-sectional study at a large urban academic children's hospital to describe readability levels, understandability scores, and completeness of written instructions given to families at hospital discharge. Two hundred charts for patients discharged from the hospital medicine service were randomly selected for review. Written discharge instructions were extracted and scored for readability (Fry Readability Scale [FRS]), understandability (Patient Education Materials Assessment Tool [PEMAT]), and completeness (5 criteria determined by consensus). Descriptive statistics enumerated the distribution of readability, understandability, and completeness of written discharge instructions. Of the patients included in the study, 51% were publicly insured. Median age was 3.1 years, and median length of stay was 2.0 days. The median readability score corresponded to a 10th-grade reading level (interquartile range, 8-12; range, 1-13). Median PEMAT score was 73% (interquartile range, 64%-82%; range, 45%-100%); 36% of instructions scored below 70%, correlating with suboptimal understandability. The diagnosis was described in only 33% of the instructions. Although explicit warning signs were listed in most instructions, 38% of the instructions did not include information on the person to contact if warning signs developed. Overall, the readability, understandability, and completeness of discharge instructions were subpar. Efforts to improve the content of discharge instructions may promote safe and effective transitions home. Journal of Hospital Medicine 2017;12:98-101. © 2017 Society of Hospital Medicine.

  9. The quality and readability of online consumer information about gynecologic cancer.

    Science.gov (United States)

    Sobota, Aleksandra; Ozakinci, Gozde

    2015-03-01

    The Internet has become an important source of health-related information for consumers, among whom younger women constitute a notable group. The aims of this study were (1) to evaluate the quality and readability of online information about gynecologic cancer using validated instruments and (2) to relate the quality of information to its readability. Using the Alexa Rank, we obtained a list of 35 Web pages providing information about 7 gynecologic malignancies. These were assessed using the Health on the Net (HON) seal of approval, the Journal of the American Medical Association (JAMA) benchmarks, and the DISCERN instrument. Flesch readability score was calculated for sections related to symptoms and signs and treatment. Less than 30% of the Web pages displayed the HON seal or achieved all JAMA benchmarks. The majority of the treatment sections were of moderate to high quality according to the DISCERN. There was no significant relationship between the presence of the HON seal and readability. Web pages achieving all JAMA benchmarks were significantly more difficult to read and understand than Web pages that missed any of the JAMA benchmarks. Treatment-related content of moderate to high quality as assessed by the DISCERN had a significantly better readability score than the low-quality content. The online information about gynecologic cancer provided by the most frequently visited Web pages is of variable quality and in general difficult to read and understand. The relationship between the quality and readability remains unclear. Health care providers should direct their patients to reliable material online because patients consider the Internet as an important source of information.

  10. An experimental study on the readability of the digital images in the furcal bone defects

    International Nuclear Information System (INIS)

    Oh, Bong Hyeon; Hwang, Eui Hwan; Lee, Sang Rae

    1995-01-01

    The aim of this study was to evaluate and compare observer performance between conventional radiographs and their digitized images for the detection of bone loss in the bifurcation of mandibular first molar. One dried human mandible with minimal periodontal bone loss around the first molar was selected and serially enlarged 27 step defects were prepared in the bifurcation area. The mandible was radiographed with exposure time of 0.12, 0.20, 0.25, 0.32, 0.40, 0.64 seconds, after each successive step in the preperation and all radiographs were digitized with IBM-PC/32 bit-Dx compatible, video camera (VM-S8200, Hitachi Co., Japan), and color monitor (Multisync 3D, NEC, Japan). Sylvia Image Capture Board for the ADC (analog to digital converter) was used. The following results obtained: 1. In the conventional radiographs, the mean score of the readability was higher at the condition of exposure time with 0.32 second. Also, as the size of artificial lesion was increased, the readability of radiographs was elevated (p<0.05). 2. In the digital images, the mean score of the readability was higher at the condition of exposure time with 0.40 second. Also, as the size of artificial lesion was increased, the readability of digital images was elevated (p<0.05). 3. At the same exposure time, the mean scores of readability were mostly higher in the digitized images. As the exposure time was increased, the digital images were superior to radiographs in readability. 4. As the size of lesion was changed, the digital images were superior to radiographs in detecting small lesion. 5. The coefficient of variation of mean score has no significant difference between digital images and radiographs.

  11. Genesis machines

    CERN Document Server

    Amos, Martyn

    2014-01-01

    Silicon chips are out. Today's scientists are using real, wet, squishy, living biology to build the next generation of computers. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Much smaller and more intelligent, these organic computers open up revolutionary possibilities. Tracing the history of computing and revealing a brave new world to come, Genesis Machines describes how this new technology will change the way we think not just about computers - but about life itself.

  12. How Readability and Topic Incidence Relate to Performance on Mathematics Story Problems in Computer-Based Curricula

    Science.gov (United States)

    Walkington, Candace; Clinton, Virginia; Ritter, Steven N.; Nathan, Mitchell J.

    2015-01-01

    Solving mathematics story problems requires text comprehension skills. However, previous studies have found few connections between traditional measures of text readability and performance on story problems. We hypothesized that recently developed measures of readability and topic incidence measured by text-mining tools may illuminate associations…

  13. Readability Levels of the Reading Passages in the ITED: Final Report. Iowa Testing Programs Research Report. Number 6.

    Science.gov (United States)

    Forsyth, Robert

    The readability level of passages from three subtests of the Iowa Tests of Educational Development (ITED), Forms X-6 and Y-6, were compared with the readability level of passages selected from the Des Moines Resister, Reader's Digest, Time, Newsweek, Saturday Review, and 18 high school textbooks from the fields of social studies, science, and…

  14. Representational Machines

    DEFF Research Database (Denmark)

    Photography not only represents space. Space is produced photographically. Since its inception in the 19th century, photography has brought to light a vast array of represented subjects. Always situated in some spatial order, photographic representations have been operatively underpinned by social...... to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...... possibilities, and genre distinctions. Presenting several distinct ways of producing space photographically, this book opens a new and important field of inquiry for photography research....

  15. Shear machines

    International Nuclear Information System (INIS)

    Astill, M.; Sunderland, A.; Waine, M.G.

    1980-01-01

    A shear machine for irradiated nuclear fuel elements has a replaceable shear assembly comprising a fuel element support block, a shear blade support and a clamp assembly which hold the fuel element to be sheared in contact with the support block. A first clamp member contacts the fuel element remote from the shear blade and a second clamp member contacts the fuel element adjacent the shear blade and is advanced towards the support block during shearing to compensate for any compression of the fuel element caused by the shear blade (U.K.)

  16. Electricity of machine tool

    International Nuclear Information System (INIS)

    Gijeon media editorial department

    1977-10-01

    This book is divided into three parts. The first part deals with electricity machine, which can taints from generator to motor, motor a power source of machine tool, electricity machine for machine tool such as switch in main circuit, automatic machine, a knife switch and pushing button, snap switch, protection device, timer, solenoid, and rectifier. The second part handles wiring diagram. This concludes basic electricity circuit of machine tool, electricity wiring diagram in your machine like milling machine, planer and grinding machine. The third part introduces fault diagnosis of machine, which gives the practical solution according to fault diagnosis and the diagnostic method with voltage and resistance measurement by tester.

  17. Environmentally Friendly Machining

    CERN Document Server

    Dixit, U S; Davim, J Paulo

    2012-01-01

    Environment-Friendly Machining provides an in-depth overview of environmentally-friendly machining processes, covering numerous different types of machining in order to identify which practice is the most environmentally sustainable. The book discusses three systems at length: machining with minimal cutting fluid, air-cooled machining and dry machining. Also covered is a way to conserve energy during machining processes, along with useful data and detailed descriptions for developing and utilizing the most efficient modern machining tools. Researchers and engineers looking for sustainable machining solutions will find Environment-Friendly Machining to be a useful volume.

  18. Readability Levels of Health-Based Websites: From Content to Comprehension

    Science.gov (United States)

    Schutten, Mary; McFarland, Allison

    2009-01-01

    Three of the national health education standards include decision-making, accessing information and analyzing influences. WebQuests are a popular inquiry-oriented method used by secondary teachers to help students achieve these content standards. While WebQuests support higher level thinking skills, the readability level of the information on the…

  19. Readability assessment of online patient education materials from academic otolaryngology-head and neck surgery departments.

    Science.gov (United States)

    Svider, Peter F; Agarwal, Nitin; Choudhry, Osamah J; Hajart, Aaron F; Baredes, Soly; Liu, James K; Eloy, Jean Anderson

    2013-01-01

    The aim of this study was to compare the readability of online patient education materials among academic otolaryngology departments in the mid-Atlantic region, with the purpose of determining whether these commonly used online resources were written at a level readily understood by the average American. A readability analysis of online patient education materials was performed using several commonly used readability assessments including the Flesch Reading Ease Score, the Flesch-Kincaid Grade Level, Simple Measure of Gobbledygook, Gunning Frequency of Gobbledygook, the New Dale-Chall Test, the Coleman-Liau Index, the New Fog Count, the Raygor Readability Estimate, the FORCAST test, and the Fry Graph. Most patient education materials from these programs were written at or above an 11th grade reading level, considerably above National Institutes of Health guidelines for recommended difficulty. Patient educational materials from academic otolaryngology Web sites are written at too difficult a reading level for a significant portion of patients and can be simplified. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Development of SMOG-Cro readability formula for healthcare communication and patient education.

    Science.gov (United States)

    Brangan, Sanja

    2015-03-01

    Effective communication shows a positive impact on patient satisfaction, compliance and medical outcomes, at the same time reducing the healthcare costs. Written information for patients needs to correspond to health literacy levels of the intended audiences. Readability formulas correlate well with the reading and comprehension tests but are considered an easier and quicker method to estimate a text difficulty. SMOG readability formula designed for English language needs to be modified if used for texts in other languages. The aim of this study was to develop a readability formula based on SMOG, that could be used to estimate text difficulty of written materials for patients in Croatian language. Contras- tive analysis of English and Croatian language covering a corpus of almost 100,000 running words showed clear linguis- tic differences in the number of polysyllabic words. The new formula, named SMOG-Cro, is presented as an equation: SMOG-Cro = 2 + √4+ syllables, with the score showing the number of years of education a person needs to be able to understand a piece of writing. The presented methodology could help in the development of readability formulas for other languages. We hope the results of this study are soon put into practice for more effective healthcare communication and patient education, and for development of a health literacy assessment tool in Croatian language.

  1. Reconstructing Readability: Recent Developments and Recommendations in the Analysis of Text Difficulty

    Science.gov (United States)

    Benjamin, Rebekah George

    2012-01-01

    Largely due to technological advances, methods for analyzing readability have increased significantly in recent years. While past researchers designed hundreds of formulas to estimate the difficulty of texts for readers, controversy has surrounded their use for decades, with criticism stemming largely from their application in creating new texts…

  2. Readability of alphanumeric characters having various contrast levels as a function of age and illumination mode.

    Science.gov (United States)

    1977-07-01

    Readability data of alphanumeric characters that vary in figure-to- ground contrast ratio were obtained from 36 subjects; 12 subjects were placed in each of three age groups (20-25 yr, 40-45 yr, and 60-65 yr). Minimum illuminance required to identify...

  3. Readability Statistics of Patient Information Leaflets in a Speech and Language Therapy Department

    Science.gov (United States)

    Pothier, Louise; Day, Rachael; Harris, Catherine; Pothier, David D.

    2008-01-01

    Background: Information leaflets are commonly used in Speech and Language Therapy Departments. Despite widespread use, they can be of variable quality. Aims: To revise current departmental leaflets using the National Health Service (NHS) Toolkit for Producing Patient Information and to test the effect that this has on the readability scores of the…

  4. Toward the Development of a Model to Estimate the Readability of Credentialing-Examination Materials

    Science.gov (United States)

    Badgett, Barbara A.

    2010-01-01

    The purpose of this study was to develop a set of procedures to establish readability, including an equation, that accommodates the multiple-choice item format and occupational-specific language related to credentialing examinations. The procedures and equation should be appropriate for learning materials, examination materials, and occupational…

  5. Assessing the Readability of Geoscience Textbooks, Laboratory Manuals, and Supplemental Materials

    Science.gov (United States)

    Hippensteel, Scott P.

    2015-01-01

    Reading materials used in undergraduate science classes have not received the same attention in the literature as those used in secondary schools. Additionally, reports critical of college textbooks and their prose are common. To assess both problems and determine the readability of assignments and texts used by geoscience faculty at the…

  6. An evaluation of the readability of drinking water quality reports: a national assessment.

    Science.gov (United States)

    Roy, Siddhartha; Phetxumphou, Katherine; Dietrich, Andrea M; Estabrooks, Paul A; You, Wen; Davy, Brenda M

    2015-09-01

    The United States Environmental Protection Agency mandates that community water systems (or water utilities) provide annual consumer confidence reports (CCRs)--water quality reports--to their consumers. These reports encapsulate information regarding sources of water, detected contaminants, regulatory compliance, and educational material. These reports have excellent potential for providing the public with accurate information on the safety of tap water, but there is a lack of research on the degree to which the information can be understood by a large proportion of the population. This study evaluated the readability of a nationally representative sample of 30 CCRs, released between 2011 and 2013. Readability (or 'comprehension difficulty') was evaluated using Flesch-Kincaid readability tests. The analysis revealed that CCRs were written at the 11th-14th grade level, which is well above the recommended 6th-7th grade level for public health communications. The CCR readability ease was found to be equivalent to that of the Harvard Law Review journal. These findings expose a wide chasm that exists between current water quality reports and their effectiveness toward being understandable to US residents. Suggestions for reorienting language and scientific information in CCRs to be easily comprehensible to the public are offered.

  7. Readability of self-illuminated signs obscured by black fuel-fire smoke.

    Science.gov (United States)

    1980-07-01

    This study, using black fuel-fire generated smoke, is a partial replication of an earlier study using an inert white smoke as the obscuring agent in the study of the readability of smoke-obscured, self-illuminated emergency exit signs. : The results ...

  8. Assessing the Readability of College Textbooks in Public Speaking: Attending to Entry Level Instruction

    Science.gov (United States)

    Schneider, David E.

    2011-01-01

    More research is needed that examines textbooks intended for the entry level college classroom. This study offers valuable information to academics that adopt a public speaking textbook for instruction as well as objective feedback to the collective authors. Readability levels of 22 nationally published textbooks, based on McGlaughlin's (1969)…

  9. Improving Readability in an Explicit Genre-Based Approach: The Case of an EFL Workplace Context

    Science.gov (United States)

    Albino, Gabriel

    2017-01-01

    The present study investigates how learners of English as a foreign language (EFL) improve the readability of their texts in an explicit genre-based approach that is utilized in an oil and gas exploration workplace in Angola. By drawing on the English for Specific Purposes and Systemic Functional Linguistics genre traditions, the study engages 18…

  10. Research Translation Strategies to Improve the Readability of Workplace Health Promotion Resources

    Science.gov (United States)

    Wallace, Alison; Joss, Nerida

    2016-01-01

    Without deliberate and resourced translation, research evidence is unlikely to inform policy and practice. This paper describes the processes and practical solutions used to translate evaluation research findings to improve the readability of print materials in a large scale worksite health programme. It is argued that a knowledge brokering and…

  11. Readability of Igbo Language Textbook in Use in Nigerian Secondary Schools

    Science.gov (United States)

    Eze, Nneka Justina

    2015-01-01

    This study assessed the readability of Igbo language textbook in use in Nigerian secondary schools. Five Igbo Language textbook were evaluated. The study employed an evaluation research design. The study was conducted in South Eastern Geopolitical zone of Nigeria which is predominantly the Igbo tribe of Nigeria. Four hundred secondary school…

  12. The readability of pediatric patient education materials on the World Wide Web.

    Science.gov (United States)

    D'Alessandro, D M; Kingsley, P; Johnson-West, J

    2001-07-01

    Literacy is a national and international problem. Studies have shown the readability of adult and pediatric patient education materials to be too high for average adults. Materials should be written at the 8th-grade level or lower. To determine the general readability of pediatric patient education materials designed for adults on the World Wide Web (WWW). GeneralPediatrics.com (http://www.generalpediatrics.com) is a digital library serving the medical information needs of pediatric health care providers, patients, and families. Documents from 100 different authoritative Web sites designed for laypersons were evaluated using a built-in computer software readability formula (Flesch Reading Ease and Flesch-Kincaid reading levels) and hand calculation methods (Fry Formula and SMOG methods). Analysis of variance and paired t tests determined significance. Eighty-nine documents constituted the final sample; they covered a wide spectrum of pediatric topics. The overall Flesch Reading Ease score was 57.0. The overall mean Fry Formula was 12.0 (12th grade, 0 months of schooling) and SMOG was 12.2. The overall Flesch-Kincaid grade level was significantly lower (Peducation materials on the WWW are not written at an appropriate reading level for the average adult. We propose that a practical reading level and how it was determined be included on all patient education materials on the WWW for general guidance in material selection. We discuss suggestions for improved readability of patient education materials.

  13. Spanish Readability Formulas for Elementary-Level Texts: A Validation Study.

    Science.gov (United States)

    Parker, Richard I.; Hasbrouck, Jan E.; Weaver, Laurie

    2001-01-01

    Uses two formulas developed for Spanish language text to analyze 9 stories that were read by 36 Spanish-speaking second graders with limited English proficiency. Finds that the Spanish readability formulas only weakly predicted student performance, indicating the need to pursue broader, qualitative indices of difficulty for Spanish text. (SG)

  14. Aligning Theme and Information Structure to Improve the Readability of Technical Writing

    Science.gov (United States)

    Moore, N. A. J.

    2006-01-01

    The readability of technical writing, and technical manuals in particular, especially for second language readers, can be noticeably improved by pairing Theme with Given and Rheme with New. This allows for faster processing of text and easier access to the "method of development" of the text. Typical Theme-Rheme patterns are described, and the…

  15. Textbook Readability and Student Performance in Online Introductory Corporate Finance Classes

    Science.gov (United States)

    Peng, Chien-Chih

    2015-01-01

    This paper examines whether the choice of a more readable textbook can improve student performance in online introductory corporate finance classes. The ordinary least squares regression model is employed to analyze a sample of 206 students during the period from 2008 to 2012. The results of this study show that the student's age, student's major,…

  16. Improving Readability of an Evaluation Tool for Low-Income Clients Using Visual Information Processing Theories

    Science.gov (United States)

    Townsend, Marilyn S.; Sylva, Kathryn; Martin, Anna; Metz, Diane; Wooten-Swanson, Patti

    2008-01-01

    Literacy is an issue for many low-income audiences. Using visual information processing theories, the goal was improving readability of a food behavior checklist and ultimately improving its ability to accurately capture existing changes in dietary behaviors. Using group interviews, low-income clients (n = 18) evaluated 4 visual styles. The text…

  17. Evaluation of Quality and Readability of Health Information Websites Identified through India's Major Search Engines.

    Science.gov (United States)

    Raj, S; Sharma, V L; Singh, A J; Goel, S

    2016-01-01

    Background. The available health information on websites should be reliable and accurate in order to make informed decisions by community. This study was done to assess the quality and readability of health information websites on World Wide Web in India. Methods. This cross-sectional study was carried out in June 2014. The key words "Health" and "Information" were used on search engines "Google" and "Yahoo." Out of 50 websites (25 from each search engines), after exclusion, 32 websites were evaluated. LIDA tool was used to assess the quality whereas the readability was assessed using Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), and SMOG. Results. Forty percent of websites (n = 13) were sponsored by government. Health On the Net Code of Conduct (HONcode) certification was present on 50% (n = 16) of websites. The mean LIDA score (74.31) was average. Only 3 websites scored high on LIDA score. Only five had readability scores at recommended sixth-grade level. Conclusion. Most health information websites had average quality especially in terms of usability and reliability and were written at high readability levels. Efforts are needed to develop the health information websites which can help general population in informed decision making.

  18. Health literacy and the Internet: a study on the readability of Australian online health information.

    Science.gov (United States)

    Cheng, Christina; Dunn, Matthew

    2015-08-01

    Almost 80% of Australian Internet users seek out health information online so the readability of this information is important. This study aimed to evaluate the readability of Australian online health information and determine if it matches the average reading level of Australians. Two hundred and fifty-one web pages with information on 12 common health conditions were identified across sectors. Readability was assessed by the Flesch-Kincaid (F-K), Simple Measure of Gobbledygook (SMOG) and Flesch Reading Ease (FRE) formulas, with grade 8 adopted as the average Australian reading level. The average reading grade measured by F-K and SMOG was 10.54 and 12.12 respectively. The mean FRE was 47.54, a 'difficult-to-read' score. Only 0.4% of web pages were written at or below grade 8 according to SMOG. Information on dementia was the most difficult to read overall, while obesity was the most difficult among government websites. The findings suggest that the readability of Australian health websites is above the average Australian levels of reading. A quantifiable guideline is needed to ensure online health information accommodates the reading needs of the general public to effectively use the Internet as an enabler of health literacy. © 2015 Public Health Association of Australia.

  19. Machine Protection

    CERN Document Server

    Schmidt, R

    2014-01-01

    The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an ...

  20. CANDU 9 fuelling machine carriage

    Energy Technology Data Exchange (ETDEWEB)

    Ullrich, D J; Slavik, J F [Atomic Energy of Canada Ltd., Saskatoon, SK (Canada)

    1997-12-31

    Continuous, on-power refuelling is a key feature of all CANDU reactor designs and is essential to maintaining high station capacity factors. The concept of a fuelling machine carriage can be traced to the early CANDU designs, such as the Douglas Point Nuclear Generating Station. In the CANDU 9 480NU unit, the combination of a mobile carriage and a proven fuelling machine head design comprises an effective means of transporting fuel between the reactor and the fuel transfer ports. It is a suitable alternative to the fuelling machine bridge system that has been utilized in the CANDU 6 reactor units. The CANDU 9 480NU fuel handling system successfully combines features that meet the project requirements with respect to fuelling performance, functionality, seismic qualification and the use of proven components. The design incorporates improvements based on experience and applicable current technologies. (author). 4 figs.

  1. CANDU 9 fuelling machine carriage

    International Nuclear Information System (INIS)

    Ullrich, D.J.; Slavik, J.F.

    1996-01-01

    Continuous, on-power refuelling is a key feature of all CANDU reactor designs and is essential to maintaining high station capacity factors. The concept of a fuelling machine carriage can be traced to the early CANDU designs, such as the Douglas Point Nuclear Generating Station. In the CANDU 9 480NU unit, the combination of a mobile carriage and a proven fuelling machine head design comprises an effective means of transporting fuel between the reactor and the fuel transfer ports. It is a suitable alternative to the fuelling machine bridge system that has been utilized in the CANDU 6 reactor units. The CANDU 9 480NU fuel handling system successfully combines features that meet the project requirements with respect to fuelling performance, functionality, seismic qualification and the use of proven components. The design incorporates improvements based on experience and applicable current technologies. (author). 4 figs

  2. Readability of Orthopaedic Patient-reported Outcome Measures: Is There a Fundamental Failure to Communicate?

    Science.gov (United States)

    Perez, Jorge L; Mosher, Zachary A; Watson, Shawna L; Sheppard, Evan D; Brabston, Eugene W; McGwin, Gerald; Ponce, Brent A

    2017-08-01

    Patient-reported outcome measures (PROMs) are increasingly used to quantify patients' perceptions of functional ability. The American Medical Association and NIH suggest patient materials be written at or below 6th to 8th grade reading levels, respectively, yet one recent study asserts that few PROMs comply with these recommendations, and suggests that the majority of PROMs are written at too high of a reading level for self-administered patient use. Notably, this study was limited in its use of only one readability algorithm, although there is no commonly accepted, standard readability algorithm for healthcare-related materials. Our study, using multiple readability equations and heeding equal weight to each, hopes to yield a broader, all-encompassing estimate of readability, thereby offering a more accurate assessment of the readability of orthopaedic PROMS. (1) What proportion of orthopaedic-related PROMs and orthopaedic-related portions of the NIH Patient Reported Outcomes Measurement Information System (PROMIS ® ) are written at or below the 6th and 8th grade levels? (2) Is there a correlation between the number of questions in the PROM and reading level? (3) Using systematic edits based on guidelines from the Centers for Medicare and Medicaid Services, what proportion of PROMs achieved American Medical Association and NIH-recommended reading levels? Eighty-six (86) independent, orthopaedic and general wellness PROMs, drawn from commonly referenced orthopaedic websites and prior studies, were chosen for analysis. Additionally, owing to their increasing use in orthopaedics, four relevant short forms, and 11 adult, physical health question banks from the PROMIS ® , were included for analysis. All documents were analyzed for reading grade levels using 19 unique readability algorithms. Descriptive statistics were performed using SPSS Version 22.0. The majority of the independent PROMs (64 of 86; 74%) were written at or below the 6th grade level, with 81 of 86

  3. What parents are reading about laryngomalacia: Quality and readability of internet resources on laryngomalacia.

    Science.gov (United States)

    Corredera, Erica; Davis, Kara S; Simons, Jeffrey P; Jabbour, Noel

    2018-05-01

    The goal of this study is to measure the quality and readability of websites related to laryngomalacia, and to compare the quality and readability scores for the sites accessed through the most popular search engines. Laryngomalacia is a common diagnosis in children but is often difficult for parents to comprehend. As information available on the internet is unregulated, the quality and readability of this information may vary. An advanced search on Google, Yahoo, and Bing was conducted using the terms "laryngomalacia" OR "soft larynx" OR "floppy voice box." The first ten websites meeting inclusion and exclusion criteria were evaluated, for each search engine. Quality and readability were assessed using the DISCERN criteria and the Flesch reading ease scoring (FRES) and Flesch-Kincaid grade level (FKGL) tests, respectively. The top 10 hits on each search engine yielded 15 unique web pages. The median DISCERN score (out of a possible high-score of 80) was 48.5 (SD 12.6). The median USA grade-level estimated by the FKGL was 11.3 (SD 1.4). Only one website (6.7%), had a readability score in the optimal range of 6th to 8th grade reading level. DISCERN scores did not correlate with FKGL scores (r = 0.10). Online information discussing laryngomalacia often varies in quality and may not be easily comprehensible to the public. It is important for healthcare professionals to understand the quality of health information accessible to patients as it may influence medical decision-making by patient families. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Dr Google: The readability and accuracy of patient education websites for Graves' disease treatment.

    Science.gov (United States)

    Purdy, Amanda C; Idriss, Almoatazbellah; Ahern, Susan; Lin, Elizabeth; Elfenbein, Dawn M

    2017-11-01

    National guidelines emphasize the importance of incorporating patient preferences into the recommendations for the treatment of Graves' disease. Many patients use the Internet to obtain health information, and search results can affect their treatment decisions. This study compares the readability and accuracy of patient-oriented online resources for the treatment of Graves' disease by website affiliation and treatment modality. A systematic Internet search was used to identify the top websites discussing the treatment of Graves' disease. Readability was measured using 5 standardized tests. Accuracy was assessed by a blinded, expert panel, which scored the accuracy of sites on a scale of 1 to 5. Mean readability and accuracy scores were compared among website affiliations and treatment modalities. We identified 13 unique websites, including 2 academic, 2 government, 5 nonprofit, and 4 private sites. There was a difference in both readability (mean 13.2, range 9.1-15.7, P = .003) and accuracy (mean 4.04, range 2.75-4.50, P = .019) based on website affiliation. Government sites (mean readability 11.1) were easier to read than academic (14.3, P < .01), nonprofit (13.9, P < .01), and private sites (13.5, P < .05). Academic sites (mean accuracy 4.50) were more accurate than private sites (3.56, P < .05). Online patient resources for the treatment of Graves' disease are written at an inappropriately high reading level. Academic sites contain both the most accurate and the most difficult to read information. Private sites represented the majority of our top results but contained the least accurate information. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Readability of internet-sourced patient education material related to “labour analgesia”

    Science.gov (United States)

    Boztas, Nilay; Omur, Dilek; Ozbılgın, Sule; Altuntas, Gözde; Piskin, Ersan; Ozkardesler, Sevda; Hanci, Volkan

    2017-01-01

    Abstract We evaluated the readability of Internet-sourced patient education materials (PEMs) related to “labour analgesia.” In addition to assessing the readability of websites, we aimed to compare commercial, personal, and academic websites. We used the most popular search engine (http://www.google.com) in our study. The first 100 websites in English that resulted from a search for the key words “labour analgesia” were scanned. Websites that were not in English, graphs, pictures, videos, tables, figures and list formats in the text, all punctuation, the number of words in the text is less than 100 words, feedback forms not related to education, (Uniform Resource Locator) URL websites, author information, references, legal disclaimers, and addresses and telephone numbers were excluded. The texts included in the study were assessed using the Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (FOG) readability formulae. The number of Latin words within the text was determined. Analysis of 300-word sections of the texts revealed that the mean FRES was 47.54 ± 12.54 (quite difficult), mean FKGL and SMOG were 11.92 ± 2.59 and 10.57 ± 1.88 years of education, respectively, and mean Gunning FOG was 14.71 ± 2.76 (very difficult). Within 300-word sections, the mean number of Latin words was identified as 16.56 ± 6.37. In our study, the readability level of Internet-sourced PEM related to “labour analgesia” was identified to be quite high indicating poor readability. PMID:29137057

  6. Analysis of the readability of patient education materials from surgical subspecialties.

    Science.gov (United States)

    Hansberry, David R; Agarwal, Nitin; Shah, Ravi; Schmitt, Paul J; Baredes, Soly; Setzen, Michael; Carmel, Peter W; Prestigiacomo, Charles J; Liu, James K; Eloy, Jean Anderson

    2014-02-01

    Patients are increasingly using the Internet as a source of information on medical conditions. Because the average American adult reads at a 7th- to 8th-grade level, the National Institutes of Health recommend that patient education material be written between a 4th- and 6th-grade level. In this study, we assess and compare the readability of patient education materials on major surgical subspecialty Web sites relative to otolaryngology. Descriptive and correlational design. Patient education materials from 14 major surgical subspecialty Web sites (American Society of Colon and Rectal Surgeons, American Association of Endocrine Surgeons, American Society of General Surgeons, American Society for Metabolic and Bariatric Surgery, American Association of Neurological Surgeons, American Congress of Obstetricians and Gynecologists, American Academy of Ophthalmology, American Academy of Orthopedic Surgeons, American Academy of Otolaryngology-Head and Neck Surgery, American Pediatric Surgical Association, American Society of Plastic Surgeons, Society for Thoracic Surgeons, and American Urological Association) were downloaded and assessed for their level of readability using 10 widely accepted readability scales. The readability level of patient education material from all surgical subspecialties was uniformly too high. Average readability levels across all subspecialties ranged from the 10th- to 15th-grade level. Otolaryngology and other surgical subspecialties Web sites have patient education material written at an education level that the average American may not be able to understand. To reach a broader population of patients, it might be necessary to rewrite patient education material at a more appropriate level. N/A. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

  7. Assessment of readability, quality and popularity of online information on ureteral stents.

    Science.gov (United States)

    Mozafarpour, Sarah; Norris, Briony; Borin, James; Eisner, Brian H

    2018-02-12

    To evaluate the quality and readability of online information on ureteral stents. Google.com was queried using the search terms "ureteric stent", "ureteral stent", "double J stent" and, "Kidney stent" derived from Google AdWords. Website popularity was determined using Google Rank and the Alexa tool. Website quality assessment was performed using the following criteria: Journal of the American Medical Association (JAMA) benchmarks, Health on the Net (HON) criteria, and a customized DISCERN questionnaire. The customized DISCERN questionnaire was developed by combining the short validated DISCERN questionnaire with additional stent-specific items including definition, placement, complications, limitations, removal and "when to seek help". Scores related to stent items were considered as the "stent score" (SS). Readability was evaluated using five readability tests. Thirty-two websites were included. The mean customized DISCERN score and "stent score" were 27.1 ± 7.1 (maximum possible score = 59) and 14.6 ± 3.8 (maximum possible score = 24), respectively. A minority of websites adequately addressed "stent removal" and "when to seek medical attention". Only two websites (6.3%) had HON certification (drugs.com, radiologyinfo.org) and only one website (3.3%) met all JAMA criteria (bradyurology.blogspot.com). Readability level was higher than the American Medical Association recommendation of sixth-grade level for more than 75% of the websites. There was no correlation between Google rank, Alexa rank, and the quality scores (P > 0.05). Among the 32 most popular websites on the topic of ureteral stents, online information was highly variable. The readability of many of the websites was far higher than standard recommendations and the online information was questionable in many cases. These findings suggest a need for improved online resources in order to better educate patients about ureteral stents and also should inform physicians that popular websites may

  8. Readability assessment of internet-based patient education materials related to facial fractures.

    Science.gov (United States)

    Sanghvi, Saurin; Cherla, Deepa V; Shukla, Pratik A; Eloy, Jean Anderson

    2012-09-01

    Various professional societies, clinical practices, hospitals, and health care-related Web sites provide Internet-based patient education material (IPEMs) to the general public. However, this information may be written above the 6th-grade reading level recommended by the US Department of Health and Human Services. The purpose of this study is to assess the readability of facial fracture (FF)-related IPEMs and compare readability levels of IPEMs provided by four sources: professional societies, clinical practices, hospitals, and miscellaneous sources. Analysis of IPEMs on FFs available on Google.com. The readability of 41 FF-related IPEMs was assessed with four readability indices: Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (Gunning FOG). Averages were evaluated against national recommendations and between each source using analysis of variance and t tests. Only 4.9% of IPEMs were written at or below the 6th-grade reading level, based on FKGL. The mean readability scores were: FRES 54.10, FKGL 9.89, SMOG 12.73, and Gunning FOG 12.98, translating into FF-related IPEMs being written at a "difficult" writing level, which is above the level of reading understanding of the average American adult. IPEMs related to FFs are written above the recommended 6th-grade reading level. Consequently, this information would be difficult to understand by the average US patient. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

  9. Readability of internet-sourced patient education material related to "labour analgesia".

    Science.gov (United States)

    Boztas, Nilay; Omur, Dilek; Ozbılgın, Sule; Altuntas, Gözde; Piskin, Ersan; Ozkardesler, Sevda; Hanci, Volkan

    2017-11-01

    We evaluated the readability of Internet-sourced patient education materials (PEMs) related to "labour analgesia." In addition to assessing the readability of websites, we aimed to compare commercial, personal, and academic websites.We used the most popular search engine (http://www.google.com) in our study. The first 100 websites in English that resulted from a search for the key words "labour analgesia" were scanned. Websites that were not in English, graphs, pictures, videos, tables, figures and list formats in the text, all punctuation, the number of words in the text is less than 100 words, feedback forms not related to education, (Uniform Resource Locator) URL websites, author information, references, legal disclaimers, and addresses and telephone numbers were excluded.The texts included in the study were assessed using the Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (FOG) readability formulae. The number of Latin words within the text was determined.Analysis of 300-word sections of the texts revealed that the mean FRES was 47.54 ± 12.54 (quite difficult), mean FKGL and SMOG were 11.92 ± 2.59 and 10.57 ± 1.88 years of education, respectively, and mean Gunning FOG was 14.71 ± 2.76 (very difficult). Within 300-word sections, the mean number of Latin words was identified as 16.56 ± 6.37.In our study, the readability level of Internet-sourced PEM related to "labour analgesia" was identified to be quite high indicating poor readability.

  10. Readability assessment of internet-based patient education materials related to mammography for breast cancer screening.

    Science.gov (United States)

    AlKhalili, Rend; Shukla, Pratik A; Patel, Ronak H; Sanghvi, Saurin; Hubbi, Basil

    2015-03-01

    The US Department of Health and Human Services (USDHHS) recommends that Internet-based patient education materials (IPEMs) be written below the sixth-grade reading level to target the average American adult. This study was designed to determine the readability of IPEMs regarding mammography for breast cancer screening. Three-hundred mammography-related Web sites were reviewed for IPEMs. Forty-two IPEMs that met the Health on the Net Foundation Code of Conduct were assessed for readability level with four readability indices that use existing algorithms based on word and sentence length to quantitatively analyze Internet sources for language intricacy including the following: Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease Score (FRES), Simple Measure of Gobbledygook (SMOG), and Gunning Frequency of Gobbledygook (Gunning FOG; GFOG). Results were compared to national recommendations, and intergroup analysis was performed. No IPEMs (0%) regarding mammography were written at or below the sixth-grade reading level, based on FKGL. The mean readability scores were as follows: FRES, 49.04 ± 10.62; FKGL, 10.71 ± 2.01; SMOG, 13.33 ± 1.67; and Gunning FOG, 14.32 ± 2.18. These scores indicate that the readability of mammography IPEMs is written at a "difficult" level, significantly above the recommended sixth-grade reading level (P < .05) determined by the USDHHS. IPEMs related to mammography are written well above the recommended sixth-grade level and likely reflect other IPEMs in diagnostic radiology. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  11. Readability of pediatric otolaryngology information by children's hospitals and academic institutions.

    Science.gov (United States)

    Wong, Kevin; Levi, Jessica R

    2017-04-01

    Evaluate the readability of pediatric otolaryngology-related patient education materials from leading online sources. Cross-sectional analysis. All pediatric otolaryngology-related articles from the online patient health libraries of the top 10 US News & World Report-ranked children's hospitals, top 5 Doximity-ranked pediatric otolaryngology fellowships, and the American Academy of Otolaryngology-Head and Neck Surgery were collected. Each article was copied in plain text format into a blank document. Web page navigation, appointment information, references, author information, appointment information, acknowledgements, and disclaimers were removed. Follow-up editing was also performed to remove paragraph breaks, colons, semicolons, numbers, percentages, and bullets. Readability grade was calculated using the Flesch-Kincaid Grade Level, Flesch Reading Ease Score, Gunning-Fog Index, Coleman-Liau Index, Automated Readability Index, and Simple Measure of Gobbledygook. Intraobserver and interobserver reliability were assessed. A total of 502 articles were analyzed. Intraobserver and interobserver reliability were both excellent, with an intraclass correlation coefficient of 0.99 and 0.96, respectively. The average readability grade across all authorships and readability assessments exceeded the reading ability of the average American adult. Only 142 articles (28.3%) were written at or below the reading ability of the average American adult, whereas the remaining 360 articles (71.7%) were written above the reading level of the average adult. Current online health information related to pediatric otolaryngology may be too difficult for the average reader to understand. Revisions may be necessary for current materials to benefit a larger readership. NA Laryngoscope, 127:E138-E144, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

  12. Readability of patient education materials available at the point of care.

    Science.gov (United States)

    Stossel, Lauren M; Segar, Nora; Gliatto, Peter; Fallar, Robert; Karani, Reena

    2012-09-01

    Many patient education materials (PEMs) available on the internet are written at high school or college reading levels, rendering them inaccessible to the average US resident, who reads at or below an 8(th) grade level. Currently, electronic health record (EHR) providers partner with companies that produce PEMs, allowing clinicians to access PEMs at the point of care. To assess the readability of PEMs provided by a popular EHR vendor as well as the National Library of Medicine (NLM). We included PEMs from Micromedex, EBSCO, and MedlinePlus. Micromedex and EBSCO supply PEMs to Meditech, a popular EHR supplier in the US. MedlinePlus supplies the NLM. These PEM databases have high market penetration and accessibility. Grade reading level of the PEMs was calculated using three validated indices: Simple Measure of Gobbledygook (SMOG), Gunning Fog (GFI), and Flesch-Kincaid (FKI). The percentage of documents above target readability and average readability scores from each database were calculated. We randomly sampled 100 disease-matched PEMs from three databases (n = 300 PEMs). Depending on the readability index used, 30-100% of PEMs were written above the 8(th) grade level. The average reading level for MedlinePlus, EBSCO, and Micromedex PEMs was 10.2 (1.9), 9.7 (1.3), and 8.6 (0.9), respectively (p ≤ 0.000) as estimated by the GFI. Estimates of readability using SMOG and FKI were similar. The majority of PEMS available through the NLM and a popular EHR were written at reading levels considerably higher than that of the average US adult.

  13. Clustering Categories in Support Vector Machines

    DEFF Research Database (Denmark)

    Carrizosa, Emilio; Nogales-Gómez, Amaya; Morales, Dolores Romero

    2017-01-01

    The support vector machine (SVM) is a state-of-the-art method in supervised classification. In this paper the Cluster Support Vector Machine (CLSVM) methodology is proposed with the aim to increase the sparsity of the SVM classifier in the presence of categorical features, leading to a gain in in...

  14. Toroidal field coils for the PDX machine

    International Nuclear Information System (INIS)

    Bushnell, C.W.

    1975-01-01

    This paper describes the engineering design features of the TF coils for the PDX machine. Included are design details of the electrical insulation, water cooling, and coil segment joint which allows access to the central machine area. A discussion of the problems anticipated in the manufacture and the planned solutions are presented

  15. Refueling machine for a nuclear reactor

    International Nuclear Information System (INIS)

    Kowalski, E.F.; Hornak, L.P.; Swidwa, K.J.

    1981-01-01

    An improved refuelling machine for inserting and removing fuel assemblies from a nuclear reactor is described which has been designed to increase the reliability of such machines. The system incorporates features which enable the refuelling operation to be performed more efficiently and economically. (U.K.)

  16. 基于特征选择支持向量机的柱塞泵智能诊断%Intelligent Fault Diagnosis for Plunger Pump Based on Features Selection and Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    崔英; 杜文辽; 孙旺; 李彦明

    2013-01-01

    柱塞泵是工程机械的关键部件,其性能好坏将直接影响整个设备的正常工作。针对柱塞泵提出基于特征选择支持向量机的智能诊断方法。对采集的振动信号基于小波包分解提取能量特征,然后利用Fisher准则函数选择对智能诊断最有利的特征,利用支持向量机进行训练,并将每个二类支持向量机按二叉树的组织形式构成系统的诊断模型。以汽车起重机柱塞泵为研究对象,其6种故障形式,包括正常、轴承内圈故障、滚动体故障、柱塞故障、配流盘故障、斜盘故障,用于检验所提算法的诊断能力,并与传统的BP神经网络和最近的蚁群神经网络方法进行对比。诊断结果表明:所提出的算法优于另外两种方法,具有较好的诊断效果。%In truck crane,the plunger pump is the key equipment,and the quality of the pump affects directly the performance of whole mechanical system. A novel intelligent diagnosis method based on features selection and support vector machine (SVM)was proposed for plunger pump in truck crane. Based on the wavelet packet decompose,the wavelet packet energy was extracted from the original vibration signal to represent the condition of equipment. Then,the Fisher criterion was utilized to select the most suitable fea-tures for diagnosis. Finally,each two-class SVM with binary tree architecture was trained to recognize the condition of mechanism. The proposed method was employed in the diagnosis of plunger pump in truck crane. The six states,including normal state,bearing inner race fault,bearing roller fault,plunger fault,thrust plate wear fault,and swash plate wear fault,were used to test the classification performance of the proposed Fisher-SVMs model,which was compared with the classical and the latest models,such as BP ANN,ANT ANN,respectively. The experimental results show that the Fisher-SVMs is superior to the other two models,and gets a promising re-sult.

  17. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  18. Machine Protection

    International Nuclear Information System (INIS)

    Schmidt, R

    2014-01-01

    The protection of accelerator equipment is as old as accelerator technology and was for many years related to high-power equipment. Examples are the protection of powering equipment from overheating (magnets, power converters, high-current cables), of superconducting magnets from damage after a quench and of klystrons. The protection of equipment from beam accidents is more recent. It is related to the increasing beam power of high-power proton accelerators such as ISIS, SNS, ESS and the PSI cyclotron, to the emission of synchrotron light by electron–positron accelerators and FELs, and to the increase of energy stored in the beam (in particular for hadron colliders such as LHC). Designing a machine protection system requires an excellent understanding of accelerator physics and operation to anticipate possible failures that could lead to damage. Machine protection includes beam and equipment monitoring, a system to safely stop beam operation (e.g. dumping the beam or stopping the beam at low energy) and an interlock system providing the glue between these systems. The most recent accelerator, the LHC, will operate with about 3 × 10 14 protons per beam, corresponding to an energy stored in each beam of 360 MJ. This energy can cause massive damage to accelerator equipment in case of uncontrolled beam loss, and a single accident damaging vital parts of the accelerator could interrupt operation for years. This article provides an overview of the requirements for protection of accelerator equipment and introduces the various protection systems. Examples are mainly from LHC, SNS and ESS

  19. A topological insight into restricted Boltzmann machines

    NARCIS (Netherlands)

    Mocanu, D.C.; Mocanu, E.; Nguyen, H.P.; Gibescu, M.; Liotta, A.

    Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep artificial neural networks for automatic features extraction, unsupervised weights initialization, but also as density estimators. Thus, their generative and discriminative

  20. Xeml Lab: a tool that supports the design of experiments at a graphical interface and generates computer-readable metadata files, which capture information about genotypes, growth conditions, environmental perturbations and sampling strategy.

    Science.gov (United States)

    Hannemann, Jan; Poorter, Hendrik; Usadel, Björn; Bläsing, Oliver E; Finck, Alex; Tardieu, Francois; Atkin, Owen K; Pons, Thijs; Stitt, Mark; Gibon, Yves

    2009-09-01

    Data mining depends on the ability to access machine-readable metadata that describe genotypes, environmental conditions, and sampling times and strategy. This article presents Xeml Lab. The Xeml Interactive Designer provides an interactive graphical interface at which complex experiments can be designed, and concomitantly generates machine-readable metadata files. It uses a new eXtensible Mark-up Language (XML)-derived dialect termed XEML. Xeml Lab includes a new ontology for environmental conditions, called Xeml Environment Ontology. However, to provide versatility, it is designed to be generic and also accepts other commonly used ontology formats, including OBO and OWL. A review summarizing important environmental conditions that need to be controlled, monitored and captured as metadata is posted in a Wiki (http://www.codeplex.com/XeO) to promote community discussion. The usefulness of Xeml Lab is illustrated by two meta-analyses of a large set of experiments that were performed with Arabidopsis thaliana during 5 years. The first reveals sources of noise that affect measurements of metabolite levels and enzyme activities. The second shows that Arabidopsis maintains remarkably stable levels of sugars and amino acids across a wide range of photoperiod treatments, and that adjustment of starch turnover and the leaf protein content contribute to this metabolic homeostasis.

  1. Machine terms dictionary

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1979-04-15

    This book gives descriptions of machine terms which includes machine design, drawing, the method of machine, machine tools, machine materials, automobile, measuring and controlling, electricity, basic of electron, information technology, quality assurance, Auto CAD and FA terms and important formula of mechanical engineering.

  2. Improving the human readability of Arden Syntax medical logic modules using a concept-oriented terminology and object-oriented programming expressions.

    Science.gov (United States)

    Choi, Jeeyae; Bakken, Suzanne; Lussier, Yves A; Mendonça, Eneida A

    2006-01-01

    Medical logic modules are a procedural representation for sharing task-specific knowledge for decision support systems. Based on the premise that clinicians may perceive object-oriented expressions as easier to read than procedural rules in Arden Syntax-based medical logic modules, we developed a method for improving the readability of medical logic modules. Two approaches were applied: exploiting the concept-oriented features of the Medical Entities Dictionary and building an executable Java program to replace Arden Syntax procedural expressions. The usability evaluation showed that 66% of participants successfully mapped all Arden Syntax rules to Java methods. These findings suggest that these approaches can play an essential role in the creation of human readable medical logic modules and can potentially increase the number of clinical experts who are able to participate in the creation of medical logic modules. Although our approaches are broadly applicable, we specifically discuss the relevance to concept-oriented nursing terminologies and automated processing of task-specific nursing knowledge.

  3. Readability and comprehensibility of informed consent forms for clinical trials

    Directory of Open Access Journals (Sweden)

    Anvita Pandiya

    2010-01-01

    A shortened Informed Consent Form, with information that a reasonable person would want to understand along with specific information that the person wants in particular would be a good option to improve understanding or comprehensibility. Additional informational meetings with a qualified person like a counselor could help in comprehension. Questionnaires designed to test comprehension of patient, peer review, patient writing the salient features could help evaluate the comprehensibility of the Informed Consent Form.

  4. Accuracy and readability of cardiovascular entries on Wikipedia: are they reliable learning resources for medical students?

    Science.gov (United States)

    Azer, Samy A; AlSwaidan, Nourah M; Alshwairikh, Lama A; AlShammari, Jumana M

    2015-10-06

    To evaluate accuracy of content and readability level of English Wikipedia articles on cardiovascular diseases, using quality and readability tools. Wikipedia was searched on the 6 October 2013 for articles on cardiovascular diseases. Using a modified DISCERN (DISCERN is an instrument widely used in assessing online resources), articles were independently scored by three assessors. The readability was calculated using Flesch-Kincaid Grade Level. The inter-rater agreement between evaluators was calculated using the Fleiss κ scale. This study was based on 47 English Wikipedia entries on cardiovascular diseases. The DISCERN scores had a median=33 (IQR=6). Four articles (8.5%) were of good quality (DISCERN score 40-50), 39 (83%) moderate (DISCERN 30-39) and 4 (8.5%) were poor (DISCERN 10-29). Although the entries covered the aetiology and the clinical picture, there were deficiencies in the pathophysiology of diseases, signs and symptoms, diagnostic approaches and treatment. The number of references varied from 1 to 127 references; 25.9±29.4 (mean±SD). Several problems were identified in the list of references and citations made in the articles. The readability of articles was 14.3±1.7 (mean±SD); consistent with the readability level for college students. In comparison, Harrison's Principles of Internal Medicine 18th edition had more tables, less references and no significant difference in number of graphs, images, illustrations or readability level. The overall agreement between the evaluators was good (Fleiss κ 0.718 (95% CI 0.57 to 0.83). The Wikipedia entries are not aimed at a medical audience and should not be used as a substitute to recommended medical resources. Course designers and students should be aware that Wikipedia entries on cardiovascular diseases lack accuracy, predominantly due to errors of omission. Further improvement of the Wikipedia content of cardiovascular entries would be needed before they could be considered a supplementary resource

  5. Readability Formulas and User Perceptions of Electronic Health Records Difficulty: A Corpus Study.

    Science.gov (United States)

    Zheng, Jiaping; Yu, Hong

    2017-03-02

    Electronic health records (EHRs) are a rich resource for developing applications to engage patients and foster patient activation, thus holding a strong potential to enhance patient-centered care. Studies have shown that providing patients with access to their own EHR notes may improve the understanding of their own clinical conditions and treatments, leading to improved health care outcomes. However, the highly technical language in EHR notes impedes patients' comprehension. Numerous studies have evaluated the difficulty of health-related text using readability formulas such as Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning-Fog Index (GFI). They conclude that the materials are often written at a grade level higher than common recommendations. The objective of our study was to explore the relationship between the aforementioned readability formulas and the laypeople's perceived difficulty on 2 genres of text: general health information and EHR notes. We also validated the formulas' appropriateness and generalizability on predicting difficulty levels of highly complex technical documents. We collected 140 Wikipedia articles on diabetes and 242 EHR notes with diabetes International Classification of Diseases, Ninth Revision code. We recruited 15 Amazon Mechanical Turk (AMT) users to rate difficulty levels of the documents. Correlations between laypeople's perceived difficulty levels and readability formula scores were measured, and their difference was tested. We also compared word usage and the impact of medical concepts of the 2 genres of text. The distributions of both readability formulas' scores (Preadability predictions and laypeople's perceptions were weak. Furthermore, despite being graded at similar levels, documents of different genres were still perceived with different difficulty (Preadability formulas' predictions did not align with perceived difficulty in either text genre. The widely used readability formulas were

  6. Addiction Machines

    Directory of Open Access Journals (Sweden)

    James Godley

    2011-10-01

    Full Text Available Entry into the crypt William Burroughs shared with his mother opened and shut around a failed re-enactment of William Tell’s shot through the prop placed upon a loved one’s head. The accidental killing of his wife Joan completed the installation of the addictation machine that spun melancholia as manic dissemination. An early encryptment to which was added the audio portion of abuse deposited an undeliverable message in WB. Wil- liam could never tell, although his corpus bears the in- scription of this impossibility as another form of pos- sibility. James Godley is currently a doctoral candidate in Eng- lish at SUNY Buffalo, where he studies psychoanalysis, Continental philosophy, and nineteenth-century litera- ture and poetry (British and American. His work on the concept of mourning and “the dead” in Freudian and Lacanian approaches to psychoanalytic thought and in Gothic literature has also spawned an essay on zombie porn. Since entering the Academy of Fine Arts Karlsruhe in 2007, Valentin Hennig has studied in the classes of Sil- via Bächli, Claudio Moser, and Corinne Wasmuht. In 2010 he spent a semester at the Dresden Academy of Fine Arts. His work has been shown in group exhibi- tions in Freiburg and Karlsruhe.

  7. Machine musicianship

    Science.gov (United States)

    Rowe, Robert

    2002-05-01

    The training of musicians begins by teaching basic musical concepts, a collection of knowledge commonly known as musicianship. Computer programs designed to implement musical skills (e.g., to make sense of what they hear, perform music expressively, or compose convincing pieces) can similarly benefit from access to a fundamental level of musicianship. Recent research in music cognition, artificial intelligence, and music theory has produced a repertoire of techniques that can make the behavior of computer programs more musical. Many of these were presented in a recently published book/CD-ROM entitled Machine Musicianship. For use in interactive music systems, we are interested in those which are fast enough to run in real time and that need only make reference to the material as it appears in sequence. This talk will review several applications that are able to identify the tonal center of musical material during performance. Beyond this specific task, the design of real-time algorithmic listening through the concurrent operation of several connected analyzers is examined. The presentation includes discussion of a library of C++ objects that can be combined to perform interactive listening and a demonstration of their capability.

  8. Identifying product order with restricted Boltzmann machines

    Science.gov (United States)

    Rao, Wen-Jia; Li, Zhenyu; Zhu, Qiong; Luo, Mingxing; Wan, Xin

    2018-03-01

    Unsupervised machine learning via a restricted Boltzmann machine is a useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the two-dimensional Ashkin-Teller model, which features a partially ordered product phase. We train the neural network with spin configuration data generated by Monte Carlo simulations and show that distinct features of the product phase can be learned from nonergodic samples resulting from symmetry breaking. Careful analysis of the weight matrices inspires us to define a nontrivial machine-learning motivated quantity of the product form, which resembles the conventional product order parameter.

  9. Logic without unique readability - a study of semantic and syntactic ambiguity

    DEFF Research Database (Denmark)

    Bentzen, Martin Mose

    One of the main reasons for introducing a formal language is to remove ambiguity, the possibility of assigning several meanings to a linguistic expression. Typically, this is achieved through ensuring unique readability of formulas by using brackets (or another convention, such as Polish notation...... not hold true universally. Whereas e.g. scope ambiguities in natural languages have been studied extensively, ambiguous formal languages have not been the focus of in depth research. Here, we lift the assumption of unique readability by omitting the brackets from propositional logic, making it possible...... to formally distinguish between syntactic and semantic ambiguity. A valuation then amounts to a semantic disambiguation, and rather than a unique valuation (truth value), there is a set of valuations corresponding to ways a formula could have been constructed. We show what happens to familiar concepts...

  10. Machine drawing

    CERN Document Server

    Narayana, KL; Reddy, K Venkata

    2006-01-01

    About the Book: Written by three distinguished authors with ample academic and teaching experience, this textbook, meant for diploma and degree students of Mechanical Engineering as well as those preparing for AMIE examination, incorporates the latest standards. The new edition includes the features of assembly drawings, part drawings and computer-aided drawings to cater to the needs of students pursuing various courses. The text of the new edition has been thoroughly revised to include new concepts and practices in the subject. It should prove an ideal textbook. Contents: Introduction

  11. Data Encoding using Periodic Nano-Optical Features

    Science.gov (United States)

    Vosoogh-Grayli, Siamack

    Successful trials have been made through a designed algorithm to quantize, compress and optically encode unsigned 8 bit integer values in the form of images using Nano optical features. The periodicity of the Nano-scale features (Nano-gratings) have been designed and investigated both theoretically and experimentally to create distinct states of variation (three on states and one off state). The use of easy to manufacture and machine readable encoded data in secured authentication media has been employed previously in bar-codes for bi-state (binary) models and in color barcodes for multiple state models. This work has focused on implementing 4 states of variation for unit information through periodic Nano-optical structures that separate an incident wavelength into distinct colors (variation states) in order to create an encoding system. Compared to barcodes and magnetic stripes in secured finite length storage media the proposed system encodes and stores more data. The benefits of multiple states of variation in an encoding unit are 1) increased numerically representable range 2) increased storage density and 3) decreased number of typical set elements for any ergodic or semi-ergodic source that emits these encoding units. A thorough investigation has targeted the effects of the use of multi-varied state Nano-optical features on data storage density and consequent data transmission rates. The results show that use of Nano-optical features for encoding data yields a data storage density of circa 800 Kbits/in2 via the implementation of commercially available high resolution flatbed scanner systems for readout. Such storage density is far greater than commercial finite length secured storage media such as Barcode family with maximum practical density of 1kbits/in2 and highest density magnetic stripe cards with maximum density circa 3 Kbits/in2. The numerically representable range of the proposed encoding unit for 4 states of variation is [0 255]. The number of

  12. Comparative Readability of Shoulder and Elbow Patient Education Materials within Orthopaedic Websites.

    Science.gov (United States)

    Beutel, Bryan G; Danna, Natalie R; Melamed, Eitan; Capo, John T

    2015-12-01

    There is growing concern that the readability of online orthopaedic patient education materials are too difficult for the general public to fully understand. It is recommended that this information be at the sixth grade reading level or lower. This study compared the readability of shoulder and elbow education articles from the American Academy of Orthopaedic Surgeons (AAOS) and American Society for Surgery of the Hand (ASSH) websites. Seventy-six patient education articles from the AAOS and ASSH concerning shoulder and elbow disorders were evaluated. Each article was assessed for the number of years since its last update, word count, percentage of passive sentences, Flesch Reading Ease score, Flesch-Kincaid grade level, Simple Measure of Gobbledygook (SMOG) grade, and New Dale-Chall grade level. Only one article was at or below the sixth grade reading level. The AAOS and ASSH articles had the following respective scores: a mean Flesch Reading Ease score of 54.3 and 51.8, Flesch-Kincaid grade level of 9.4 and 10.3, SMOG grade of 8.5 and 9.4, and New Dale-Chall grade of 10.4 and 11.0. Articles from the AAOS were longer (p education materials regarding the shoulder and elbow on the AAOS and ASSH websites have readability scores above the recommended reading level. These may be too challenging for the majority of patients to read and consequently serve as a barrier to proper patient education. Reducing the percentage of passive sentences may serve as a novel target for improving readability.

  13. A Practical Method to Increase the Frequency Readability for Vibration Signals

    Directory of Open Access Journals (Sweden)

    Jean Loius Ntakpe

    2016-10-01

    Full Text Available Damage detection and nondestructive evaluation of mechanical and civil engineering structures are nowadays very important to assess the integrity and ensure the reliability of structures. Thus, frequency evaluation becomes a crucial issue, since this modal parameter is mainly used in structural integrity assessment. The herein presented study highligts the possibility of increasing the frequency readability by involving a simple and cost-effective method.

  14. Quality and readability of websites for patient information on tonsillectomy and sleep apnea.

    Science.gov (United States)

    Chi, Ethan; Jabbour, Noel; Aaronson, Nicole Leigh

    2017-07-01

    Tonsillectomy is a common treatment for obstructive sleep apnea (OSA). The Internet allows patients direct access to medical information. Since information on the Internet is largely unregulated, quality and readability are variable. This study evaluates the quality and readability of the most likely visited websites presenting information on sleep apnea and tonsillectomy. The three most popular search engines (Google, Bing, Yahoo) were queried with the phrase "sleep apnea AND tonsillectomy." The DISCERN instrument was used to assess quality of information. Readability was evaluated using the Flesch-Kincaid Reading Grade Level (FKGL) and Flesch Reading Ease Score (FRES). Out of the maximum of 80, the average DISCERN quality score for the websites was 55.1 (SD- 12.3, Median- 60.5). The mean score for FRES was 42.3 (SD- 15.9, Median- 45.5), which falls in the range defined as difficult. No website was above the optimal score of 65. The mean score for the FKGL was US grade-level of 10.7 (SD- 1.6, Median- 11.6). Only 4(27%) websites were in the optimal range of 6-8. There was very weak correlation between FRES and DISCERN (r = 0.07) and FKGL and DISCERN (r = 0.21). Tonsillectomy is one of the most common surgeries in the US. However, the internet information readily available to patients varies in quality. Additionally, much of the information is above the recommended grade level for comprehension by the public. By being aware of what information patients are reading online, physicians can better explain treatments and address misunderstandings. Physicians may consider using similar methods to test the readability for their own resources for patient education. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Availability and Readability of Online Patient Education Materials Regarding Regional Anesthesia Techniques for Perioperative Pain Management.

    Science.gov (United States)

    Kumar, Gunjan; Howard, Steven K; Kou, Alex; Kim, T Edward; Butwick, Alexander J; Mariano, Edward R

    2017-10-01

    Patient education materials (PEM) should be written at a sixth-grade reading level or lower. We evaluated the availability and readability of online PEM related to regional anesthesia and compared the readability and content of online PEM produced by fellowship and nonfellowship institutions. With IRB exemption, we constructed a cohort of online regional anesthesia PEM by searching Websites from North American academic medical centers supporting a regional anesthesiology and acute pain medicine fellowships and used a standardized Internet search engine protocol to identify additional nonfellowship Websites with regional anesthesia PEM based on relevant keywords. Readability metrics were calculated from PEM using the TextStat 0.1.4 textual analysis package for Python 2.7 and compared between institutions with and without a fellowship program. The presence of specific descriptive PEM elements related to regional anesthesia was also compared between groups. PEM from 17 fellowship and 15 nonfellowship institutions were included in analyses. The mean (SD) Flesch-Kincaid Grade Level for PEM from the fellowship group was 13.8 (2.9) vs 10.8 (2.0) for the nonfellowship group (p = 0.002). We observed no other differences in readability metrics between fellowship and nonfellowship institutions. Fellowship-based PEM less commonly included descriptions of the following risks: local anesthetic systemic toxicity (p = 0.033) and injury due to an insensate extremity (p = 0.003). Available online PEM related to regional anesthesia are well above the recommended reading level. Further, fellowship-based PEM posted are at a higher reading level than PEM posted by nonfellowship institutions and are more likely to omit certain risk descriptions. 2016 American Academy of Pain Medicine. This work is written by US Government employees and is in the public domain in the US.

  16. A technique for improving readability of Forrester diagram in system dynamics

    Directory of Open Access Journals (Sweden)

    Yang Wei-Tzen

    2003-01-01

    Full Text Available We describe a three-pass algorithm for improving the readability of Forrester Diagram in system dynamics. The first pass converts Forrester Diagram to recurrent hierarchy. The second pass sorts the vertices on each level, with the goal of minimizing crossings. The third pass is a finite tuning of the layout that determines the horizontal positions of vertices. An illustrative example is given to verify the result. .

  17. Augmented reality with image registration, vision correction and sunlight readability via liquid crystal devices

    OpenAIRE

    Wang, Yu-Jen; Chen, Po-Ju; Liang, Xiao; Lin, Yi-Hsin

    2017-01-01

    Augmented reality (AR), which use computer-aided projected information to augment our sense, has important impact on human life, especially for the elder people. However, there are three major challenges regarding the optical system in the AR system, which are registration, vision correction, and readability under strong ambient light. Here, we solve three challenges simultaneously for the first time using two liquid crystal (LC) lenses and polarizer-free attenuator integrated in optical-see-...

  18. Readability and Content Assessment of Informed Consent Forms for Phase II-IV Clinical Trials in China.

    Science.gov (United States)

    Wen, Gaiyan; Liu, Xinchun; Huang, Lihua; Shu, Jingxian; Xu, Nana; Chen, Ruifang; Huang, Zhijun; Yang, Guoping; Wang, Xiaomin; Xiang, Yuxia; Lu, Yao; Yuan, Hong

    2016-01-01

    To explore the readability and content integrity of informed consent forms (ICFs) used in China and to compare the quality of Chinese local ICFs with that of international ICFs. The length, readability and content of 155 consent documents from phase II-IV drug clinical trials from the Third Xiangya Hospital Ethics Committee from November 2009 to January 2015 were evaluated. Reading difficulty was tested using a readability formula adapted for the Chinese language. An ICF checklist containing 27 required elements was successfully constructed to evaluate content integrity. The description of alternatives to participation was assessed. The quality of ICFs from different sponsorships were also compared. Among the 155 evaluable trials, the ICFs had a median length of 5286 words, corresponding to 7 pages. The median readability score was 4.31 (4.02-4.41), with 63.9% at the 2nd level and 36.1% at the 3rd level. Five of the 27 elements were frequently neglected. The average score for the description of alternatives to participation was 1.06, and 27.7% of the ICFs did not mention any alternatives. Compared with Chinese local ICFs, international ICFs were longer, more readable and contained more of the required elements (P readability and content integrity than Chinese local ICFs. More efforts should thus be made to improve the quality of consent documents in China.

  19. An experimental study on the readability of digital images in the furcal bone defects

    International Nuclear Information System (INIS)

    Kang, Hyung Wuk; Hwang, Eui Hwan; Lee, Sang Rae

    2003-01-01

    To evaluate and compare the efficacy of digital radiographic images in the detection of bone loss at the bifurcation area of the mandibular first molar with traditional film-based periapical radiographs. One dried human mandible with minimal periodontal bone loss around the first molar was selected and an artificial alveolar bone defect at the bifurcation area was serially prepared over 18 steps. Images were taken using a direct CCD-based system and with F-speed periapical films. The images were evaluated by seven interpreters (3 radiologists, 3 periodontologists, and 1 general dentist) using a 5-point confidence rating scale. The readability of both periapical radiographs and digital image increased as the size of the artificial lesion and exposure time increased (p<0.05). Periapical radiographs offered greater readability of smaller bone defects than digital images, and the coefficient of variation of mean score between periapical radiographs and digital images showed a significant difference. The experimental results indicate that a significant difference in the coefficient of variation of mean score exists between periapical radiographs and digital images, and that traditional film-based periapical images offer greater readability of smaller bone defects than digital images can presently offer.

  20. Readability and quality assessment of websites related to microtia and aural atresia.

    Science.gov (United States)

    Alamoudi, Uthman; Hong, Paul

    2015-02-01

    Many parents and children utilize the Internet for health-related information, but the quality of these websites can vary. The objective of this study was to assess the quality and readability of microtia and aural atresia related websites. The search engine Google was queried with the terms 'microtia' and 'aural atresia.' The first 30 results were evaluated, and those websites containing original information written in English were reviewed. Quality of content was assessed with the DISCERN instrument, and readability was assessed with the Flesch-Kincaid Reading Grade Level (FKGL) and the Flesch Reading Ease Score (FRES) tests. Each website was also reviewed for ownership and the date of last update. Sixteen microtia and 14 aural atresia websites were included for full review. The mean DISCERN score for microtia websites was 54.4 (SD=8.3), and for aural atresia websites it was 47.6 (SD=10.7), which indicates 'good' and 'fair' quality of content, respectively. Readability assessments showed an average reading level requiring a grade 10 education on FKGL, and only one microtia (6.3%) and one aural atresia (7.1%) websites were deemed to be at 'reasonable' reading level on FRES. High-quality websites that are considered easily comprehensible to the general public were lacking. Since parents and children may use websites when making treatment decisions, physicians should be aware of the quality of health information pertaining to their area of expertise available on the Internet. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Third Molars on the Internet: A Guide for Assessing Information Quality and Readability

    Science.gov (United States)

    Brennan, David; Sambrook, Paul; Armfield, Jason

    2015-01-01

    Background Directing patients suffering from third molars (TMs) problems to high-quality online information is not only medically important, but also could enable better engagement in shared decision making. Objectives This study aimed to develop a scale that measures the scientific information quality (SIQ) for online information concerning wisdom tooth problems and to conduct a quality evaluation for online TMs resources. In addition, the study evaluated whether a specific piece of readability software (Readability Studio Professional 2012) might be reliable in measuring information comprehension, and explored predictors for the SIQ Scale. Methods A cross-sectional sample of websites was retrieved using certain keywords and phrases such as “impacted wisdom tooth problems” using 3 popular search engines. The retrieved websites (n=150) were filtered. The retained 50 websites were evaluated to assess their characteristics, usability, accessibility, trust, readability, SIQ, and their credibility using DISCERN and Health on the Net Code (HoNCode). Results Websites’ mean scale scores varied significantly across website affiliation groups such as governmental, commercial, and treatment provider bodies. The SIQ Scale had a good internal consistency (alpha=.85) and was significantly correlated with DISCERN (r=.82, Preadability grade (10.3, SD 1.9) was above the recommended level, and was significantly correlated with the Scientific Information Comprehension Scale (r=.45. PReadability Studio software estimates were associated with scientific information comprehensiveness measures. PMID:26443470

  2. An experimental study on the readability of digital images in the furcal bone defects

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Hyung Wuk; Hwang, Eui Hwan; Lee, Sang Rae [Kyunghee University College of Medicine, Seoul (Korea, Republic of)

    2003-06-15

    To evaluate and compare the efficacy of digital radiographic images in the detection of bone loss at the bifurcation area of the mandibular first molar with traditional film-based periapical radiographs. One dried human mandible with minimal periodontal bone loss around the first molar was selected and an artificial alveolar bone defect at the bifurcation area was serially prepared over 18 steps. Images were taken using a direct CCD-based system and with F-speed periapical films. The images were evaluated by seven interpreters (3 radiologists, 3 periodontologists, and 1 general dentist) using a 5-point confidence rating scale. The readability of both periapical radiographs and digital image increased as the size of the artificial lesion and exposure time increased (p<0.05). Periapical radiographs offered greater readability of smaller bone defects than digital images, and the coefficient of variation of mean score between periapical radiographs and digital images showed a significant difference. The experimental results indicate that a significant difference in the coefficient of variation of mean score exists between periapical radiographs and digital images, and that traditional film-based periapical images offer greater readability of smaller bone defects than digital images can presently offer.

  3. Readability of written medicine information materials in Arabic language: expert and consumer evaluation.

    Science.gov (United States)

    Al Aqeel, Sinaa; Abanmy, Norah; Aldayel, Abeer; Al-Khalifa, Hend; Al-Yahya, Maha; Diab, Mona

    2018-02-27

    Written Medicine Information (WMI) is one of the sources that patients use to obtain information concerning medicine. This paper aims to assess the readability of two types of WMIs in Arabic language based on vocabulary use and sentence structure using a panel of experts and consumers. This is a descriptive study. Two different types of materials, including the online text from King Abdullah Bin Abdulaziz Arabic Health Encyclopaedia (KAAHE) and medication leaflets submitted by the manufacturers to the Saudi Food and Drug Authority (SFDA) were evaluated. We selected a group of sentences from each WMI. The readability was assessed by experts (n = 5) and consumers (n = 5). The sentence readability of each measured using a specific criteria and rated as 1 = easy, 2 = intermediate, or 3 = difficult. A total of 4476 sentences (SFDA 2231; KAHEE 2245) extracted from websites or patient information leaflets on 50 medications and evaluated. The majority of the vocabulary and sentence structure was considered easy by both expert (SFDA: 68%; KAAHE: 76%) and consumer (SFDA: 76%; KAAHE: 84%) groups. The sentences with difficult or intermediate vocabulary and sentence structure are derived primarily from the precautions and side effects sections. The SFDA and KAAHE WMIs are easy to read and understand as judged by our study sample. However; there is room for improvement, especially in sections related to the side effects and precautions.

  4. Readability and Content Assessment of Informed Consent Forms for Medical Procedures in Croatia.

    Science.gov (United States)

    Vučemilo, Luka; Borovečki, Ana

    2015-01-01

    High quality of informed consent form is essential for adequate information transfer between physicians and patients. Current status of medical procedure consent forms in clinical practice in Croatia specifically in terms of the readability and the content is unknown. The aim of this study was to assess the readability and the content of informed consent forms for diagnostic and therapeutic procedures used with patients in Croatia. 52 informed consent forms from six Croatian hospitals on the secondary and tertiary health-care level were tested for reading difficulty using Simple Measure of Gobbledygook (SMOG) formula adjusted for Croatian language and for qualitative analysis of the content. The averaged SMOG grade of analyzed informed consent forms was 13.25 (SD 1.59, range 10-19). Content analysis revealed that informed consent forms included description of risks in 96% of the cases, benefits in 81%, description of procedures in 78%, alternatives in 52%, risks and benefits of alternatives in 17% and risks and benefits of not receiving treatment or undergoing procedures in 13%. Readability of evaluated informed consent forms is not appropriate for the general population in Croatia. The content of the forms failed to include in high proportion of the cases description of alternatives, risks and benefits of alternatives, as well as risks and benefits of not receiving treatments or undergoing procedures. Data obtained from this research could help in development and improvement of informed consent forms in Croatia especially now when Croatian hospitals are undergoing the process of accreditation.

  5. A quantitative readability analysis of patient education resources from gastroenterology society websites.

    Science.gov (United States)

    Hansberry, David R; Patel, Sahil R; Agarwal, Prateek; Agarwal, Nitin; John, Elizabeth S; John, Ann M; Reynolds, James C

    2017-06-01

    The lay public frequently access and rely on online information as a source of their medical knowledge. Many medical societies are unaware of national patient education material guidelines and subsequently fail to meet them. The goal of the present study was to evaluate the readability of patient education materials within the medical field of gastroenterology. Two hundred fourteen articles pertaining to patient education materials were evaluated with ten well-established readability scales. The articles were available on the websites for the American College of Gastroenterology (ACG), the American Gastroenterological Association (AGA), the American Society of Gastrointestinal Endoscopy (ASGE), the British Society of Gastroenterology (BSG), and the NIH section National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). One-way analysis of variance (ANOVA) and Tukey's honest significant difference (HSD) post hoc analysis were conducted to determine any differences in level of readability between websites. The 214 articles were written at an 11.8 ± 2.1 grade level with a range of 8.0 to 16.0 grade level. A one-way ANOVA and Tukey's HSD post hoc analysis determined the ACG was written at a significantly (p gastroenterology content.

  6. Readability of Educational Materials to Support Parent Sexual Communication With Their Children and Adolescents.

    Science.gov (United States)

    Ballonoff Suleiman, Ahna; Lin, Jessica S; Constantine, Norman A

    2016-05-01

    Sexual communication is a principal means of transmitting sexual values, expectations, and knowledge from parents to their children and adolescents. Many parents seek information and guidance to support talking with their children about sex and sexuality. Parent education materials can deliver this guidance but must use appropriate readability levels to facilitate comprehension and motivation. This study appraised the readability of educational materials to support parent sexual communication with their children. Fifty brochures, pamphlets, and booklets were analyzed using the Flesch-Kincaid, Gunning Fog, and Simple Measure of Gobbledygook (SMOG) index methods. Mean readability grade-level scores were 8.3 (range = 4.5-12.8), 9.7 (range = 5.5-14.9), and 10.1 (range = 6.7-13.9), respectively. Informed by National Institutes of Health-recommended 6th to 7th grade levels and American Medical Association-recommended 5th to 6th grade levels, percentages falling at or below the 7.0 grade level were calculated as 38%, 12%, and 2% and those falling at or below the 6.0 grade level were calculated as 12%, 2%, and 0% based on the Flesch-Kincaid, Gunning Fog, and SMOG methods, respectively. These analyses indicate that the majority of educational materials available online to support parents' communication with their children about sex and sexuality do not meet the needs of many or most parents. Efforts to improve the accessibility of these materials are warranted.

  7. Third Molars on the Internet: A Guide for Assessing Information Quality and Readability.

    Science.gov (United States)

    Hanna, Kamal; Brennan, David; Sambrook, Paul; Armfield, Jason

    2015-10-06

    Directing patients suffering from third molars (TMs) problems to high-quality online information is not only medically important, but also could enable better engagement in shared decision making. This study aimed to develop a scale that measures the scientific information quality (SIQ) for online information concerning wisdom tooth problems and to conduct a quality evaluation for online TMs resources. In addition, the study evaluated whether a specific piece of readability software (Readability Studio Professional 2012) might be reliable in measuring information comprehension, and explored predictors for the SIQ Scale. A cross-sectional sample of websites was retrieved using certain keywords and phrases such as "impacted wisdom tooth problems" using 3 popular search engines. The retrieved websites (n=150) were filtered. The retained 50 websites were evaluated to assess their characteristics, usability, accessibility, trust, readability, SIQ, and their credibility using DISCERN and Health on the Net Code (HoNCode). Websites' mean scale scores varied significantly across website affiliation groups such as governmental, commercial, and treatment provider bodies. The SIQ Scale had a good internal consistency (alpha=.85) and was significantly correlated with DISCERN (r=.82, Psoftware estimates were associated with scientific information comprehensiveness measures.

  8. Polyadenylated Sequencing Primers Enable Complete Readability of PCR Amplicons Analyzed by Dideoxynucleotide Sequencing

    Directory of Open Access Journals (Sweden)

    Martin Beránek

    2012-01-01

    Full Text Available Dideoxynucleotide DNA sequencing is one of the principal procedures in molecular biology. Loss of an initial part of nucleotides behind the 3' end of the sequencing primer limits the readability of sequenced amplicons. We present a method which extends the readability by using sequencing primers modified by polyadenylated tails attached to their 5' ends. Performing a polymerase chain reaction, we amplified eight amplicons of six human genes (AMELX, APOE, HFE, MBL2, SERPINA1 and TGFB1 ranging from 106 bp to 680 bp. Polyadenylation of the sequencing primers minimized the loss of bases in all amplicons. Complete sequences of shorter products (AMELX 106 bp, SERPINA1 121 bp, HFE 208 bp, APOE 244 bp, MBL2 317 bp were obtained. In addition, in the case of TGFB1 products (366 bp, 432 bp, and 680 bp, respectively, the lengths of sequencing readings were significantly longer if adenylated primers were used. Thus, single strand dideoxynucleotide sequencing with adenylated primers enables complete or near complete readability of short PCR amplicons.

  9. Readability and quality assessment of internet-based patient education materials related to laryngeal cancer.

    Science.gov (United States)

    Narwani, Vishal; Nalamada, Keerthana; Lee, Michael; Kothari, Prasad; Lakhani, Raj

    2016-04-01

    Patients are increasingly using the internet to access health-related information. The purpose of this study was to assess the readability and quality of laryngeal cancer-related websites. Patient education materials were identified by performing an internet search using 3 search engines. Readability was assessed using Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), and Gunning Fog Index (GFI). The DISCERN instrument was utilized to assess quality of health information. A total of 54 websites were included in the analysis. The mean readability scores were as follows: FRES, 48.2 (95% confidence interval [CI] = 44.8-51.6); FKGL, 10.9 (95% CI = 10.3-11.5); and GFI, 13.8 (95% CI = 11.3-16.3). These scores suggest that, on average, online information about patients with laryngeal cancer is written at an advanced level. The mean DISCERN score was 49.8 (95% CI = 45.4-54.2), suggesting that online information is of variable quality. Our study suggests much of the laryngeal cancer information available online is of suboptimal quality and written at a level too difficult for the average adult to read comfortably. © 2015 Wiley Periodicals, Inc.

  10. Readability of Spanish language online information for the initial treatment of burns.

    Science.gov (United States)

    Votta, Kaitlyn; Metivier, Meghan; Romo, Stephanie; Garrigan, Hannah; Drexler, Alana; Nodoushani, Ariana; Sheridan, Robert

    2018-06-01

    This study's aim is to identify the most popular online resources for burn treatment information available in the Spanish language, and to evaluate the readability of this information. The phrase "tratamiento de quemaduras" (burn treatment) was entered into search engines Google and Bing on 9/15/2014 and 9/13/2017. The top 12 Spanish web results on each site were identified and analyzed using Readability Studio Professional Edition v2012.1. The software generated a "mean grade reading level" for each article, or the grade of students that could be expected to understand the article's language. 21 distinct articles were identified at T1 and 17 at T2, with seven overlapping between T1 and T2. The average grade reading level of all the websites ranged from 7.8 to 13.8 at T1 (approximately 8th grade to sophomore year of college) and 7.8 to 12.2 at T2. No websites were within 1 standard deviation of the American Medical Association recommended 6th grade reading level. With readability showing little improvement during the past three years, providers should be aware of the complexity of online literature, and the potential complications this presents to patients. Additionally, burn centers should prioritize generating more accessible information for the Spanish speaking public. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

  11. INVESTIGATION OF MAGNESIUM ALLOYS MACHINABILITY

    Directory of Open Access Journals (Sweden)

    Berat Barıs BULDUM

    2013-01-01

    Full Text Available Magnesium is the lightest structural metal. Magnesium alloys have a hexagonal lattice structure, which affects the fundamental properties of these alloys. Plastic deformation of the hexagonal lattice is more complicated than in cubic latticed metals like aluminum, copper and steel. Magnesium alloy developments have traditionally been driven by industry requirements for lightweight materials to operate under increasingly demanding conditions. Magnesium alloys have always been attractive to designers due to their low density, only two thirds that of aluminium and its alloys [1]. The element and its alloys take a big part of modern industry needs. Especially nowadays magnesium alloys are used in automotive and mechanical (trains and wagons manufacture, because of its lightness and other features. Magnesium and magnesium alloys are the easiest of all metals to machine, allowing machining operations at extremely high speed. All standard machining operations such as turning, drilling, milling, are commonly performed on magnesium parts.

  12. Mineral mining machines

    Energy Technology Data Exchange (ETDEWEB)

    Mc Gaw, B H

    1984-01-01

    A machine for mining minerals is patented. It is a cutter loader with a drum actuating element of the worm type equipped with a multitude of cutting teeth reinforced with tungsten carbide. A feature of the patented machine is that all of the cutting teeth and holders on the drum have the identical design. This is achieved through selecting a slant angle for the cutting teeth which is the mean between the slant angle of the conventional radial teeth and the slant angle of the advance teeth. This, in turn, is provided thanks to the corresponding slant of the holders relative to the drum and (or) the slant of the cutting part of the teeth relative to their stems. Thus, the advance teeth projecting beyond the surface of the drum on the face side and providing upper and lateral clearances have the same angle of attack as the radial teeth, that is, from 20 to 35 degrees. A series of modifications of the cutting teeth is patented. One of the designs allows the cutting tooth to occupy a varying position relative to the drum, from the conventional vertical to an inverted, axially projecting position. In the last case the tooth in the extraction process provides the upper and lateral clearances for the drum on the face side. Among the different modifications of the cutting teeth, a design is proposed which provides for the presence of a stem which is shaped like a truncated cone. This particular stem is designed for use jointly with a wedge which unfastens the teeth and is placed in a holder. The latter is completed in a transverse slot thanks to which the rear end of the stem is compressed, which simplifies replacement of a tooth. Channels are provided in the patented machine for feeding water to the worm spiral, the holders and the cutting teeth themselves in order to deal with dust.

  13. Machine technology: a survey

    International Nuclear Information System (INIS)

    Barbier, M.M.

    1981-01-01

    An attempt was made to find existing machines that have been upgraded and that could be used for large-scale decontamination operations outdoors. Such machines are in the building industry, the mining industry, and the road construction industry. The road construction industry has yielded the machines in this presentation. A review is given of operations that can be done with the machines available

  14. Machine Shop Lathes.

    Science.gov (United States)

    Dunn, James

    This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

  15. Superconducting rotating machines

    International Nuclear Information System (INIS)

    Smith, J.L. Jr.; Kirtley, J.L. Jr.; Thullen, P.

    1975-01-01

    The opportunities and limitations of the applications of superconductors in rotating electric machines are given. The relevant properties of superconductors and the fundamental requirements for rotating electric machines are discussed. The current state-of-the-art of superconducting machines is reviewed. Key problems, future developments and the long range potential of superconducting machines are assessed

  16. Giro form reading machine

    Science.gov (United States)

    Minh Ha, Thien; Niggeler, Dieter; Bunke, Horst; Clarinval, Jose

    1995-08-01

    Although giro forms are used by many people in daily life for money remittance in Switzerland, the processing of these forms at banks and post offices is only partly automated. We describe an ongoing project for building an automatic system that is able to recognize various items printed or written on a giro form. The system comprises three main components, namely, an automatic form feeder, a camera system, and a computer. These components are connected in such a way that the system is able to process a bunch of forms without any human interactions. We present two real applications of our system in the field of payment services, which require the reading of both machine printed and handwritten information that may appear on a giro form. One particular feature of giro forms is their flexible layout, i.e., information items are located differently from one form to another, thus requiring an additional analysis step to localize them before recognition. A commercial optical character recognition software package is used for recognition of machine-printed information, whereas handwritten information is read by our own algorithms, the details of which are presented. The system is implemented by using a client/server architecture providing a high degree of flexibility to change. Preliminary results are reported supporting our claim that the system is usable in practice.

  17. Risk estimation using probability machines

    Science.gov (United States)

    2014-01-01

    Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306

  18. The Improved Relevance Voxel Machine

    DEFF Research Database (Denmark)

    Ganz, Melanie; Sabuncu, Mert; Van Leemput, Koen

    The concept of sparse Bayesian learning has received much attention in the machine learning literature as a means of achieving parsimonious representations of features used in regression and classification. It is an important family of algorithms for sparse signal recovery and compressed sensing....... Hence in its current form it is reminiscent of a greedy forward feature selection algorithm. In this report, we aim to solve the problems of the original RVoxM algorithm in the spirit of [7] (FastRVM).We call the new algorithm Improved Relevance Voxel Machine (IRVoxM). Our contributions...... and enables basis selection from overcomplete dictionaries. One of the trailblazers of Bayesian learning is MacKay who already worked on the topic in his PhD thesis in 1992 [1]. Later on Tipping and Bishop developed the concept of sparse Bayesian learning [2, 3] and Tipping published the Relevance Vector...

  19. Managing virtual machines with Vac and Vcycle

    Science.gov (United States)

    McNab, A.; Love, P.; MacMahon, E.

    2015-12-01

    We compare the Vac and Vcycle virtual machine lifecycle managers and our experiences in providing production job execution services for ATLAS, CMS, LHCb, and the GridPP VO at sites in the UK, France and at CERN. In both the Vac and Vcycle systems, the virtual machines are created outside of the experiment's job submission and pilot framework. In the case of Vac, a daemon runs on each physical host which manages a pool of virtual machines on that host, and a peer-to-peer UDP protocol is used to achieve the desired target shares between experiments across the site. In the case of Vcycle, a daemon manages a pool of virtual machines on an Infrastructure-as-a-Service cloud system such as OpenStack, and has within itself enough information to create the types of virtual machines to achieve the desired target shares. Both systems allow unused shares for one experiment to temporarily taken up by other experiements with work to be done. The virtual machine lifecycle is managed with a minimum of information, gathered from the virtual machine creation mechanism (such as libvirt or OpenStack) and using the proposed Machine/Job Features API from WLCG. We demonstrate that the same virtual machine designs can be used to run production jobs on Vac and Vcycle/OpenStack sites for ATLAS, CMS, LHCb, and GridPP, and that these technologies allow sites to be operated in a reliable and robust way.

  20. Archetypal Analysis for Machine Learning

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    2010-01-01

    Archetypal analysis (AA) proposed by Cutler and Breiman in [1] estimates the principal convex hull of a data set. As such AA favors features that constitute representative ’corners’ of the data, i.e. distinct aspects or archetypes. We will show that AA enjoys the interpretability of clustering - ...... for K-means [2]. We demonstrate that the AA model is relevant for feature extraction and dimensional reduction for a large variety of machine learning problems taken from computer vision, neuroimaging, text mining and collaborative filtering....

  1. Adaptive machine and its thermodynamic costs

    Science.gov (United States)

    Allahverdyan, Armen E.; Wang, Q. A.

    2013-03-01

    We study the minimal thermodynamically consistent model for an adaptive machine that transfers particles from a higher chemical potential reservoir to a lower one. This model describes essentials of the inhomogeneous catalysis. It is supposed to function with the maximal current under uncertain chemical potentials: if they change, the machine tunes its own structure fitting it to the maximal current under new conditions. This adaptation is possible under two limitations: (i) The degree of freedom that controls the machine's structure has to have a stored energy (described via a negative temperature). The origin of this result is traced back to the Le Chatelier principle. (ii) The machine has to malfunction at a constant environment due to structural fluctuations, whose relative magnitude is controlled solely by the stored energy. We argue that several features of the adaptive machine are similar to those of living organisms (energy storage, aging).

  2. Machine tool structures

    CERN Document Server

    Koenigsberger, F

    1970-01-01

    Machine Tool Structures, Volume 1 deals with fundamental theories and calculation methods for machine tool structures. Experimental investigations into stiffness are discussed, along with the application of the results to the design of machine tool structures. Topics covered range from static and dynamic stiffness to chatter in metal cutting, stability in machine tools, and deformations of machine tool structures. This volume is divided into three sections and opens with a discussion on stiffness specifications and the effect of stiffness on the behavior of the machine under forced vibration c

  3. Model-Agnostic Interpretability of Machine Learning

    OpenAIRE

    Ribeiro, Marco Tulio; Singh, Sameer; Guestrin, Carlos

    2016-01-01

    Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to trust and act upon the predictions, and in more intuitive user interfaces. Thus, interpretability has become a vital concern in machine learning, and work in the area of interpretable models has found renewed interest. In some applications, such models are as accurate as non-interpretable ones, and thus are preferred f...

  4. How well are health information websites displayed on mobile phones? Implications for the readability of health information.

    Science.gov (United States)

    Cheng, Christina; Dunn, Matthew

    2017-03-01

    Issue addressed More than 87% of Australians own a mobile phone with Internet access and 82% of phone owners use their smartphones to search for health information, indicating that mobile phones may be a powerful tool for building health literacy. Yet, online health information has been found to be above the reading ability of the general population. As reading on a smaller screen may further complicate the readability of information, this study aimed to examine how health information is displayed on mobile phones and its implications for readability. Methods Using a cross-sectional design with convenience sampling, a sample of 270 mobile webpages with information on 12 common health conditions was generated for analysis, they were categorised based on design and position of information display. Results The results showed that 71.48% of webpages were mobile-friendly but only 15.93% were mobile-friendly webpages designed in a way to optimise readability, with a paging format and queried information displayed for immediate viewing. Conclusion With inadequate evidence and lack of consensus on how webpage design can best promote reading and comprehension, it is difficult to draw a conclusion on the effect of current mobile health information presentation on readability. So what? Building mobile-responsive websites should be a priority for health information providers and policy-makers. Research efforts are urgently required to identify how best to enhance readability of mobile health information and fully capture the capabilities of mobile phones as a useful device to increase health literacy.

  5. The method and efficacy of support vector machine classifiers based on texture features and multi-resolution histogram from 18F-FDG PET-CT images for the evaluation of mediastinal lymph nodes in patients with lung cancer

    International Nuclear Information System (INIS)

    Gao, Xuan; Chu, Chunyu; Li, Yingci; Lu, Peiou; Wang, Wenzhi; Liu, Wanyu; Yu, Lijuan

    2015-01-01

    Highlights: • Three support vector machine classifiers were constructed from PET-CT images. • The areas under the ROC curve for SVM1, SVM2, and SVM3 were 0.689, 0.579, and 0.685, respectively. • The areas under curves for maximum short diameter and SUV max were 0.684 and 0.652, respectively. • The algorithm based on SVM was potential in the diagnosis of mediastinal lymph nodes. - Abstract: Objectives: In clinical practice, image analysis is dependent on simply visual perception and the diagnostic efficacy of this analysis pattern is limited for mediastinal lymph nodes in patients with lung cancer. In order to improve diagnostic efficacy, we developed a new computer-based algorithm and tested its diagnostic efficacy. Methods: 132 consecutive patients with lung cancer underwent 18 F-FDG PET/CT examination before treatment. After all data were imported into the database of an on-line medical image analysis platform, the diagnostic efficacy of visual analysis was first evaluated without knowing pathological results, and the maximum short diameter and maximum standardized uptake value (SUV max ) were measured. Then lymph nodes were segmented manually. Three classifiers based on support vector machine (SVM) were constructed from CT, PET, and combined PET-CT images, respectively. The diagnostic efficacy of SVM classifiers was obtained and evaluated. Results: According to ROC curves, the areas under curves for maximum short diameter and SUV max were 0.684 and 0.652, respectively. The areas under the ROC curve for SVM1, SVM2, and SVM3 were 0.689, 0.579, and 0.685, respectively. Conclusion: The algorithm based on SVM was potential in the diagnosis of mediastinal lymph nodes

  6. Quantitative analysis of the level of readability of online emergency radiology-based patient education resources.

    Science.gov (United States)

    Hansberry, David R; D'Angelo, Michael; White, Michael D; Prabhu, Arpan V; Cox, Mougnyan; Agarwal, Nitin; Deshmukh, Sandeep

    2018-04-01

    The vast amount of information found on the internet, combined with its accessibility, makes it a widely utilized resource for Americans to find information pertaining to medical information. The field of radiology is no exception. In this paper, we assess the readability level of websites pertaining specifically to emergency radiology. Using Google, 23 terms were searched, and the top 10 results were recorded. Each link was evaluated for its readability level using a set of ten reputable readability scales. The search terms included the following: abdominal ultrasound, abdominal aortic aneurysm, aortic dissection, appendicitis, cord compression, CT abdomen, cholecystitis, CT chest, diverticulitis, ectopic pregnancy, epidural hematoma, dural venous thrombosis, head CT, MRI brain, MR angiography, MRI spine, ovarian torsion, pancreatitis, pelvic ultrasound, pneumoperitoneum, pulmonary embolism, subarachnoid hemorrhage, and subdural hematoma. Any content that was not written for patients was excluded. The 230 articles that were assessed were written, on average, at a 12.1 grade level. Only 2 of the 230 articles (1%) were written at the third to seventh grade recommended reading level set forth by the National Institutes of Health (NIH) and American Medical Association (AMA). Fifty-two percent of the 230 articles were written so as to require a minimum of a high school education (at least a 12th grade level). Additionally, 17 of the 230 articles (7.3%) were written at a level that exceeded an undergraduate education (at least a 16th grade level). The majority of websites with emergency radiology-related patient education materials are not adhering to the NIH and AMA's recommended reading levels, and it is likely that the average reader is not benefiting fully from these information outlets. With the link between health literacy and poor health outcomes, it is important to address the online content in this area of radiology, allowing for patient to more fully benefit

  7. A Systematic Assessment of Google Search Queries and Readability of Online Gynecologic Oncology Patient Education Materials.

    Science.gov (United States)

    Martin, Alexandra; Stewart, J Ryan; Gaskins, Jeremy; Medlin, Erin

    2018-01-20

    The Internet is a major source of health information for gynecologic cancer patients. In this study, we systematically explore common Google search terms related to gynecologic cancer and calculate readability of top resulting websites. We used Google AdWords Keyword Planner to generate a list of commonly searched keywords related to gynecologic oncology, which were sorted into five groups (cervical cancer, ovarian cancer, uterine cancer, vulvar cancer, vaginal cancer) using five patient education websites from sgo.org . Each keyword was Google searched to create a list of top websites. The Python programming language (version 3.5.1) was used to describe frequencies of keywords, top-level domains (TLDs), domains, and readability of top websites using four validated formulae. Of the estimated 1,846,950 monthly searches resulting in 62,227 websites, the most common was cancer.org . The most common TLD was *.com. Most websites were above the eighth-grade reading level recommended by the American Medical Association (AMA) and the National Institute of Health (NIH). The SMOG Index was the most reliable formula. The mean grade level readability for all sites using SMOG was 9.4 ± 2.3, with 23.9% of sites falling at or below the eighth-grade reading level. The first ten results for each Google keyword were easiest to read with results beyond the first page of Google being consistently more difficult. Keywords related to gynecologic malignancies are Google-searched frequently. Most websites are difficult to read without a high school education. This knowledge may help gynecologic oncology providers adequately meet the needs of their patients.

  8. GCP compliance and readability of informed consent forms from an emerging hub for clinical trials

    Directory of Open Access Journals (Sweden)

    Satish Chandrasekhar Nair

    2015-01-01

    Full Text Available Background: The rapid expansion of trials in emerging regions has raised valid concerns about research subject protection, particularly related to informed consent. The purpose of this study is to assess informed consent form (ICF compliance with Good Clinical Practice (GCP guidelines and the readability easeof the ICFs in Abu Dhabi, a potential destination for clinical trials in the UAE. Materials and Methods: A multicenter retrospective cross-sectional analysis of 140 ICFs from industry sponsored and non-sponsored studies was conducted by comparing against a local standard ICF. Flesch-Kincaid Reading Scale was used to assess the readability ease of the forms. Results: Non-sponsored studies had signifi cantly lower overall GCP compliance of 55.8% when compared to 79.5% for industry sponsored studies. Only 33% of sponsored and 16% of non-sponsored studies included basic information on the participants′ rights and responsibilities. Flesch-Kincaid Reading ease score for the informed consent forms from industry sponsored studies was signifi cantly higher 48.9 ± 4.8 as compared to 38.5 ± 8.0 for non-sponsored studies, though both were more complex than recommended. Reading Grade Level score was also higher than expected, but scores for the ICFs from the industry sponsored studies were 9.7 ± 0.7, signifi cantly lower as compared to 12.2 ± 1.3 for non-sponsored studies. Conclusion: In spite of the undisputed benefits of conducting research in emerging markets readability, comprehension issues and the lack of basic essential information call for improvements in the ICFs to protect the rights of future research subjects enrolled in clinical trials in the UAE.

  9. Readability and Content Assessment of Informed Consent Forms for Medical Procedures in Croatia

    Science.gov (United States)

    Vučemilo, Luka; Borovečki, Ana

    2015-01-01

    Background High quality of informed consent form is essential for adequate information transfer between physicians and patients. Current status of medical procedure consent forms in clinical practice in Croatia specifically in terms of the readability and the content is unknown. The aim of this study was to assess the readability and the content of informed consent forms for diagnostic and therapeutic procedures used with patients in Croatia. Methods 52 informed consent forms from six Croatian hospitals on the secondary and tertiary health-care level were tested for reading difficulty using Simple Measure of Gobbledygook (SMOG) formula adjusted for Croatian language and for qualitative analysis of the content. Results The averaged SMOG grade of analyzed informed consent forms was 13.25 (SD 1.59, range 10–19). Content analysis revealed that informed consent forms included description of risks in 96% of the cases, benefits in 81%, description of procedures in 78%, alternatives in 52%, risks and benefits of alternatives in 17% and risks and benefits of not receiving treatment or undergoing procedures in 13%. Conclusions Readability of evaluated informed consent forms is not appropriate for the general population in Croatia. The content of the forms failed to include in high proportion of the cases description of alternatives, risks and benefits of alternatives, as well as risks and benefits of not receiving treatments or undergoing procedures. Data obtained from this research could help in development and improvement of informed consent forms in Croatia especially now when Croatian hospitals are undergoing the process of accreditation. PMID:26376183

  10. Readability, complexity, and suitability of online resources for mastectomy and lumpectomy.

    Science.gov (United States)

    Tran, Bao Ngoc N; Singh, Mansher; Singhal, Dhruv; Rudd, Rima; Lee, Bernard T

    2017-05-15

    Nearly half of American adults have low or marginal health literacy. This negatively affects patients' participation, decision-making, satisfaction, and overall outcomes especially when there is a mismatch between information provided and the skills of the intended audience. Recommendations that patient information be written below the sixth grade level have been made for over three decades. This study compares online resources for mastectomy versus lumpectomy using expanded metrics including readability level, complexity, and density of data and overall suitability for public consumption. The 10 highest ranked Web sites for mastectomy and lumpectomy were identified using the largest Internet engine (Google). Each Web site was assessed for readability (Simple Measure of Gobbledygook), complexity (PMOSE/iKIRSCH), and suitability (Suitability Assessment of Materials). Scores were analyzed by each Web site and overall. Readability analysis showed a significant reading grade level difference between mastectomy and lumpectomy online information (15.4 and 13.9, P = 0.04, respectively). Complexity analysis via PMOSE/iKIRSCH revealed a mean score of 6.5 for mastectomy materials corresponding to "low" complexity and eighth to 12 th grade education. Lumpectomy literature had a lower PMOSE/iKIRSCH score of 5.8 corresponding to a "very low" complexity and fourth to eighth grade education (P = 0.05). Suitability assessment showed mean values of 41% and 46% (P = 0.83) labeled as the lowest level of "adequacy" for mastectomy and lumpectomy materials, respectively. Inter-rater reliability was high for both complexity and suitability analysis. Online resources for the surgical treatment of breast cancer are above the recommended reading grade level. The suitability level is barely adequate indicating a need for revision. Online resources for mastectomy have a higher reading grade level than do materials for lumpectomy and tend to be more complex. Copyright © 2017 Elsevier

  11. Quality and readability of online patient information regarding sclerotherapy for venous malformations.

    Science.gov (United States)

    Pass, Jonathan H; Patel, Amani H; Stuart, Sam; Barnacle, Alex M; Patel, Premal A

    2018-05-01

    Patients often use the internet as a source of information about their condition and treatments. However, this information is unregulated and varies in quality. To evaluate the readability and quality of online information for pediatric and adult patients and caregivers regarding sclerotherapy for venous malformations. "Venous malformation sclerotherapy" was entered into Google, and results were reviewed until 20 sites that satisfied predefined inclusion criteria were identified. Scientific and non-patient-focused web pages were excluded. Readability was assessed using the Flesch Reading Ease Score and American Medical Association reading difficulty recommendations and quality was assessed using Journal of the American Medical Association standards and assessing if the site displayed HONcode (Health on the Net Code) certification. Assessment of the breadth of relevant information was made using a predefined checklist. Forty-nine search engine results were reviewed before 20 sites were identified for analysis. Average Flesch Reading Ease Score was 44 (range: 24.2-70.1), representing a "fairly difficult" reading level. None of the sites had a Flesch Reading Ease Score meeting the American Medical Association recommendation of 80-90. Only one site met all four Journal of the American Medical Association quality criteria (average: 2.1). None of the sites displayed a HONcode seal. The information most frequently found was: sclerotherapy is performed by radiologists, multiple treatments may be needed and surgery is an alternative treatment. Online information regarding sclerotherapy for venous malformations is heterogeneous in quality and breadth of information, and does not meet readability recommendations for patient information. Radiologists should be aware of and account for this when meeting patients.

  12. An Individual Claims History Simulation Machine

    Directory of Open Access Journals (Sweden)

    Andrea Gabrielli

    2018-03-01

    Full Text Available The aim of this project is to develop a stochastic simulation machine that generates individual claims histories of non-life insurance claims. This simulation machine is based on neural networks to incorporate individual claims feature information. We provide a fully calibrated stochastic scenario generator that is based on real non-life insurance data. This stochastic simulation machine allows everyone to simulate their own synthetic insurance portfolio of individual claims histories and back-test thier preferred claims reserving method.

  13. Operating System For Numerically Controlled Milling Machine

    Science.gov (United States)

    Ray, R. B.

    1992-01-01

    OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

  14. MITS machine operations

    International Nuclear Information System (INIS)

    Flinchem, J.

    1980-01-01

    This document contains procedures which apply to operations performed on individual P-1c machines in the Machine Interface Test System (MITS) at AiResearch Manufacturing Company's Torrance, California Facility

  15. Brain versus Machine Control.

    Directory of Open Access Journals (Sweden)

    Jose M Carmena

    2004-12-01

    Full Text Available Dr. Octopus, the villain of the movie "Spiderman 2", is a fusion of man and machine. Neuroscientist Jose Carmena examines the facts behind this fictional account of a brain- machine interface

  16. Applied machining technology

    CERN Document Server

    Tschätsch, Heinz

    2010-01-01

    Machining and cutting technologies are still crucial for many manufacturing processes. This reference presents all important machining processes in a comprehensive and coherent way. It includes many examples of concrete calculations, problems and solutions.

  17. Machining with abrasives

    CERN Document Server

    Jackson, Mark J

    2011-01-01

    Abrasive machining is key to obtaining the desired geometry and surface quality in manufacturing. This book discusses the fundamentals and advances in the abrasive machining processes. It provides a complete overview of developing areas in the field.

  18. Understanding Legacy Features with Featureous

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2011-01-01

    Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

  19. Machine protection systems

    CERN Document Server

    Macpherson, A L

    2010-01-01

    A summary of the Machine Protection System of the LHC is given, with particular attention given to the outstanding issues to be addressed, rather than the successes of the machine protection system from the 2009 run. In particular, the issues of Safe Machine Parameter system, collimation and beam cleaning, the beam dump system and abort gap cleaning, injection and dump protection, and the overall machine protection program for the upcoming run are summarised.

  20. Dictionary of machine terms

    International Nuclear Information System (INIS)

    1990-06-01

    This book has introduction of dictionary of machine terms, and a compilation committee and introductory remarks. It gives descriptions of the machine terms in alphabetical order from a to Z and also includes abbreviation of machine terms and symbol table, way to read mathematical symbols and abbreviation and terms of drawings.