Injuries from intimate partner and sexual violence: Significance and classification systems.

PubMed

Sommers, Marilyn S; Brown, Kathleen M; Buschur, Carole; Everett, Janine S; Fargo, Jamison D; Fisher, Bonnie S; Hinkle, Christina; Zink, Therese M

2012-07-01

While intimate partner violence (IPV) and sexual violence (SV) are highly associated with injury, the healthcare and legal significance of these injuries is controversial. Herein we propose to explore the significance of injury in IPV and SV and examine the current status of injury classification systems from the perspectives of the healthcare and criminal justice systems. We will review current injury classification systems and suggest a typology of injury that could be tested empirically. Within the published literature, we found that no commonly accepted injury typology exists. While nuanced and controversial issues surround the role of injury detection in the sexual assault forensic examination, enough evidence exists to support the continued pursuance of a scientific approach to injury classification. We propose an injury typology that is measurable, is applicable to the healthcare setting and criminal justice system, and allows us to use uses a matrix approach that includes a severity score, anatomic location, and injury type. We suggest a typology that might be used for further empirical testing on the validity and reliability of IPV and SV injury data. We recommend that the community of scientists concerned about IPV and SV develop a more rigorous injury classification system that will improve the quality of forensic evidence proffered and decisions made throughout the criminal justice process. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Classification systems in nursing: formalizing nursing knowledge and implications for nursing information systems.

PubMed

Goossen, W T; Epping, P J; Abraham, I L

1996-03-01

The development of nursing information systems (NIS) is often hampered by the fact that nursing lacks a unified nursing terminology and classification system. Currently there exist various initiatives in this area. We address the question as to how current initiatives in the development of nursing terminology and classification systems can contribute towards the development of NIS. First, the rationale behind the formalization of nursing knowledge is discussed. Next, using a framework for nursing information processing, the most important developments in the field of nursing on formalization, terminology and classification are critically reviewed. The initiatives discussed include nursing terminology projects in several countries, and the International Classification of Nursing Practice. Suggestions for further developments in the area are discussed. Finally, implications for NIS are presented, as well as the relationships of these components to other sections of an integrated computerized patient record.

A systematic literature review of automated clinical coding and classification systems

PubMed Central

Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome. PMID:20962126

A systematic literature review of automated clinical coding and classification systems.

PubMed

Stanfill, Mary H; Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.

The groningen laryngomalacia classification system--based on systematic review and dynamic airway changes.

PubMed

van der Heijden, Martijn; Dikkers, Frederik G; Halmos, Gyorgy B

2015-12-01

Laryngomalacia is the most common cause of dyspnea and stridor in newborn infants. Laryngomalacia is a dynamic change of the upper airway based on abnormally pliable supraglottic structures, which causes upper airway obstruction. In the past, different classification systems have been introduced. Until now no classification system is widely accepted and applied. Our goal is to provide a simple and complete classification system based on systematic literature search and our experiences. Retrospective cohort study with literature review. All patients with laryngomalacia under the age of 5 at time of diagnosis were included. Photo and video documentation was used to confirm diagnosis and characteristics of dynamic airway change. Outcome was compared with available classification systems in literature. Eighty-five patients were included. In contrast to other classification systems, only three typical different dynamic changes have been identified in our series. Two existing classification systems covered 100% of our findings, but there was an unnecessary overlap between different types in most of the systems. Based on our finding, we propose a new a classification system for laryngomalacia, which is purely based on dynamic airway changes. The groningen laryngomalacia classification is a new, simplified classification system with three types, based on purely dynamic laryngeal changes, tested in a tertiary referral center: Type 1: inward collapse of arytenoids cartilages, Type 2: medial displacement of aryepiglottic folds, and Type 3: posterocaudal displacement of epiglottis against the posterior pharyngeal wall. © 2015 Wiley Periodicals, Inc.

Building a Multi-Discipline Digital Library Through Extending the Dienst Protocol

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.

1997-01-01

The purpose of this project is to establish multi-discipline capability for a unified, canonical digital library service for scientific and technical information (STI). This is accomplished by extending the Dienst Protocol to be aware of subject classification of a servers holdings. We propose a hierarchical, general, and extendible subject classification that can encapsulate existing classification systems.

Classification of parotidectomy: a proposed modification to the European Salivary Gland Society classification system.

PubMed

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

Incorporating Learning Theory into Existing Systems Engineering Models

DTIC Science & Technology

2013-09-01

3. Social  Cognition 22 Table 1. Classification of learning theories Behaviorism Cognitivism Constructivism Connectivism...Introdution to design of large scale systems. New York: Mcgraw-Hill. Grusec. J. (1992). Social learning theory and development psychology: The... LEARNING THEORY INTO EXISTING SYSTEMS ENGINEERING MODELS by Valentine Leo September 2013 Thesis Advisor: Gary O. Langford Co-Advisor

Gender classification under extended operating conditions

NASA Astrophysics Data System (ADS)

Rude, Howard N.; Rizki, Mateen

2014-06-01

Gender classification is a critical component of a robust image security system. Many techniques exist to perform gender classification using facial features. In contrast, this paper explores gender classification using body features extracted from clothed subjects. Several of the most effective types of features for gender classification identified in literature were implemented and applied to the newly developed Seasonal Weather And Gender (SWAG) dataset. SWAG contains video clips of approximately 2000 samples of human subjects captured over a period of several months. The subjects are wearing casual business attire and outer garments appropriate for the specific weather conditions observed in the Midwest. The results from a series of experiments are presented that compare the classification accuracy of systems that incorporate various types and combinations of features applied to multiple looks at subjects at different image resolutions to determine a baseline performance for gender classification.

On the nature of global classification

NASA Technical Reports Server (NTRS)

Wheelis, M. L.; Kandler, O.; Woese, C. R.

1992-01-01

Molecular sequencing technology has brought biology into the era of global (universal) classification. Methodologically and philosophically, global classification differs significantly from traditional, local classification. The need for uniformity requires that higher level taxa be defined on the molecular level in terms of universally homologous functions. A global classification should reflect both principal dimensions of the evolutionary process: genealogical relationship and quality and extent of divergence within a group. The ultimate purpose of a global classification is not simply information storage and retrieval; such a system should also function as an heuristic representation of the evolutionary paradigm that exerts a directing influence on the course of biology. The global system envisioned allows paraphyletic taxa. To retain maximal phylogenetic information in these cases, minor notational amendments in existing taxonomic conventions should be adopted.

Knowledge categorization affects popularity and quality of Wikipedia articles

PubMed Central

Lomi, Alessandro

2018-01-01

The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia—an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system. PMID:29293627

Knowledge categorization affects popularity and quality of Wikipedia articles.

PubMed

Lerner, Jürgen; Lomi, Alessandro

2018-01-01

The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia-an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system.

Maxillectomy defects: a suggested classification scheme.

PubMed

Akinmoladun, V I; Dosumu, O O; Olusanya, A A; Ikusika, O F

2013-06-01

The term "maxillectomy" has been used to describe a variety of surgical procedures for a spectrum of diseases involving a diverse anatomical site. Hence, classifications of maxillectomy defects have often made communication difficult. This article highlights this problem, emphasises the need for a uniform system of classification and suggests a classification system which is simple and comprehensive. Articles related to this subject, especially those with specified classifications of maxillary surgical defects were sourced from the internet through Google, Scopus and PubMed using the search terms maxillectomy defects classification. A manual search through available literature was also done. The review of the materials revealed many classifications and modifications of classifications from the descriptive, reconstructive and prosthodontic perspectives. No globally acceptable classification exists among practitioners involved in the management of diseases in the mid-facial region. There were over 14 classifications of maxillary defects found in the English literature. Attempts made to address the inadequacies of previous classifications have tended to result in cumbersome and relatively complex classifications. A single classification that is based on both surgical and prosthetic considerations is most desirable and is hereby proposed.

Classification of polytype structures of zinc sulfide

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

Laptev, V.I.

1994-12-31

It is suggested that the existing classification of polytype structures of zinc sulfide be supplemented with an additional criterion: the characteristic of regular point systems (Wyckoff positions) including their type, number, and multiplicity. The consideration of the Wyckoff positions allowed the establishment of construction principles of known polytype series of different symmetries and the systematization (for the first time) of the polytypes with the same number of differently packed layers. the classification suggested for polytype structures of zinc sulfide is compact and provides a basis for creating search systems. The classification table obtained can also be used for numerous siliconmore » carbide polytypes. 8 refs., 4 tabs.« less

Validation of a new classification for periprosthetic shoulder fractures.

PubMed

Kirchhoff, Chlodwig; Beirer, Marc; Brunner, Ulrich; Buchholz, Arne; Biberthaler, Peter; Crönlein, Moritz

2018-06-01

Successful treatment of periprosthetic shoulder fractures depends on the right strategy, starting with a well-structured classification of the fracture. Unfortunately, clinically relevant factors for treatment planning are missing in the pre-existing classifications. Therefore, the aim of the present study was to describe a new specific classification system for periprosthetic shoulder fractures including a structured treatment algorithm for this important fragility fracture issue. The classification was established, focussing on five relevant items, naming the prosthesis type, the fracture localisation, the rotator cuff status, the anatomical fracture region and the stability of the implant. After considering each single item, the individual treatment concept can be assessed in one last step. To evaluate the introduced classification, a retrospective analysis of pre- and post-operative data of patients, treated with periprosthetic shoulder fractures, was conducted by two board certified trauma surgery consultants. The data of 19 patients (8 male, 11 female) with a mean age of 74 ± five years have been analysed in our study. The suggested treatment algorithm was proven to be reliable, detected by good clinical outcome in 15 of 16 (94%) cases, where the suggested treatment was maintained. Only one case resulted in poor outcome due to post-operative wound infection and had to be revised. The newly developed six-step classification is easy to utilise and extends the pre-existing classification systems in terms of clinically-relevant information. This classification should serve as a simple tool for the surgeon to consider the optimal treatment for his patients.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

The history of female genital tract malformation classifications and proposal of an updated system.

PubMed

Acién, Pedro; Acién, Maribel I

2011-01-01

A correct classification of malformations of the female genital tract is essential to prevent unnecessary and inadequate surgical operations and to compare reproductive results. An ideal classification system should be based on aetiopathogenesis and should suggest the appropriate therapeutic strategy. We conducted a systematic review of relevant articles found in PubMed, Scopus, Scirus and ISI webknowledge, and analysis of historical collections of 'female genital malformations' and 'classifications'. Of 124 full-text articles assessed for eligibility, 64 were included because they contained original general, partial or modified classifications. All the existing classifications were analysed and grouped. The unification of terms and concepts was also analysed. Traditionally, malformations of the female genital tract have been catalogued and classified as Müllerian malformations due to agenesis, lack of fusion, the absence of resorption and lack of posterior development of the Müllerian ducts. The American Fertility Society classification of the late 1980s included seven basic groups of malformations also considering the Müllerian development and the relationship of the malformations to fertility. Other classifications are based on different aspects: functional, defects in vertical fusion, embryological or anatomical (Vagina, Cervix, Uterus, Adnex and Associated Malformation: VCUAM classification). However, an embryological-clinical classification system seems to be the most appropriate. Accepting the need for a new classification system of genitourinary malformations that considers the experience gained from the application of the current classification systems, the aetiopathogenesis and that also suggests the appropriate treatment, we proposed an update of our embryological-clinical classification as a new system with six groups of female genitourinary anomalies.

A Three-Phase Decision Model of Computer-Aided Coding for the Iranian Classification of Health Interventions (IRCHI)

PubMed Central

Azadmanjir, Zahra; Safdari, Reza; Ghazisaeedi, Marjan; Mokhtaran, Mehrshad; Kameli, Mohammad Esmail

2017-01-01

Introduction: Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. Aim: The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. Methods: first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. Results: There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. Conclusion: The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research. PMID:28883671

Risk-informed radioactive waste classification and reclassification.

PubMed

Croff, Allen G

2006-11-01

Radioactive waste classification systems have been developed to allow wastes having similar hazards to be grouped for purposes of storage, treatment, packaging, transportation, and/or disposal. As recommended in the National Council on Radiation Protection and Measurements' Report No. 139, Risk-Based Classification of Radioactive and Hazardous Chemical Wastes, a preferred classification system would be based primarily on the health risks to the public that arise from waste disposal and secondarily on other attributes such as the near-term practicalities of managing a waste, i.e., the waste classification system would be risk informed. The current U.S. radioactive waste classification system is not risk informed because key definitions--especially that of high-level waste--are based on the source of the waste instead of its inherent characteristics related to risk. A second important reason for concluding the existing U.S. radioactive waste classification system is not risk informed is there are no general principles or provisions for exempting materials from being classified as radioactive waste which would then allow management without regard to its radioactivity. This paper elaborates the current system for classifying and reclassifying radioactive wastes in the United States, analyzes the extent to which the system is risk informed and the ramifications of its not being so, and provides observations on potential future direction of efforts to address shortcomings in the U.S. radioactive waste classification system as of 2004.

Evaluation and integration of disparate classification systems for clefts of the lip

PubMed Central

Wang, Kathie H.; Heike, Carrie L.; Clarkson, Melissa D.; Mejino, Jose L. V.; Brinkley, James F.; Tse, Raymond W.; Birgfeld, Craig B.; Fitzsimons, David A.; Cox, Timothy C.

2014-01-01

Orofacial clefting is a common birth defect with wide phenotypic variability. Many systems have been developed to classify cleft patterns to facilitate diagnosis, management, surgical treatment, and research. In this review, we examine the rationale for different existing classification schemes and determine their inter-relationships, as well as strengths and deficiencies for subclassification of clefts of the lip. The various systems differ in how they describe and define attributes of cleft lip (CL) phenotypes. Application and analysis of the CL classifications reveal discrepancies that may result in errors when comparing studies that use different systems. These inconsistencies in terminology, variable levels of subclassification, and ambiguity in some descriptions may confound analyses and impede further research aimed at understanding the genetics and etiology of clefts, development of effective treatment options for patients, as well as cross-institutional comparisons of outcome measures. Identification and reconciliation of discrepancies among existing systems is the first step toward creating a common standard to allow for a more explicit interpretation that will ultimately lead to a better understanding of the causes and manifestations of phenotypic variations in clefting. PMID:24860508

Classification of Dark Modified KdV Equation

NASA Astrophysics Data System (ADS)

Xiong, Na; Lou, Sen-Yue; Li, Biao; Chen, Yong

2017-07-01

The dark Korteweg-de Vries (KdV) systems are defined and classified by Kupershmidt sixteen years ago. However, there is no other classifications for other kinds of nonlinear systems. In this paper, a complete scalar classification for dark modified KdV (MKdV) systems is obtained by requiring the existence of higher order differential polynomial symmetries. Different to the nine classes of the dark KdV case, there exist twelve independent classes of the dark MKdV equations. Furthermore, for the every class of dark MKdV system, there is a free parameter. Only for a fixed parameter, the dark MKdV can be related to dark KdV via suitable Miura transformation. The recursion operators of two classes of dark MKdV systems are also given. Supported by the Global Change Research Program of China under Grant No. 2015Cb953904, National Natural Science Foundation of China under Grant Nos. 11675054, 11435005, 11175092, and 11205092 and Shanghai Knowledge Service Platform for Trustworthy Internet of Things (No. ZF1213) and K. C. Wong Magna Fund in Ningbo University

Assessment of fatty degeneration of the gluteal muscles in patients with THA using MRI: reliability and accuracy of the Goutallier and quartile classification systems.

PubMed

Engelken, Florian; Wassilew, Georgi I; Köhlitz, Torsten; Brockhaus, Sebastian; Hamm, Bernd; Perka, Carsten; Diederichs, und Gerd

2014-01-01

The purpose of this study was to quantify the performance of the Goutallier classification for assessing fatty degeneration of the gluteus muscles from magnetic resonance (MR) images and to compare its performance to a newly proposed system. Eighty-four hips with clinical signs of gluteal insufficiency and 50 hips from asymptomatic controls were analyzed using a standard classification system (Goutallier) and a new scoring system (Quartile). Interobserver reliability and intraobserver repeatability were determined, and accuracy was assessed by comparing readers' scores with quantitative estimates of the proportion of intramuscular fat based on MR signal intensities (gold standard). The existing Goutallier classification system and the new Quartile system performed equally well in assessing fatty degeneration of the gluteus muscles, both showing excellent levels of interrater and intrarater agreement. While the Goutallier classification system has the advantage of being widely known, the benefit of the Quartile system is that it is based on more clearly defined grades of fatty degeneration. Copyright © 2014 Elsevier Inc. All rights reserved.

Survey on large scale system control methods

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1987-01-01

The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

Patient characteristics in low back pain subgroups based on an existing classification system. A descriptive cohort study in chiropractic practice.

PubMed

Eirikstoft, Heidi; Kongsted, Alice

2014-02-01

Sub-grouping of low back pain (LBP) is believed to improve prediction of prognosis and treatment effects. The objectives of this study were: (1) to examine whether chiropractic patients could be sub-grouped according to an existing pathoanatomically-based classification system, (2) to describe patient characteristics within each subgroup, and (3) to determine the proportion of patients in whom clinicians considered the classification to be unchanged after approximately 10 days. A cohort of 923 LBP patients was included during their first consultation. Patients completed an extensive questionnaire and were examined according to a standardised protocol. Based on the clinical examination, patients were classified into diagnostic subgroups. After approximately 10 days, chiropractors reported whether they considered the subgroup had changed. The most frequent subgroups were reducible and partly reducible disc syndromes followed by facet joint pain, dysfunction and sacroiliac (SI)-joint pain. Classification was inconclusive in 5% of the patients. Differences in pain, activity limitation, and psychological factors were small across subgroups. Within 10 days, 82% were reported to belong to the same subgroup as at the first visit. In conclusion, LBP patients could be classified according to a standardised protocol, and chiropractors considered most patient classifications to be unchanged within 10 days. Differences in patient characteristics between subgroups were very small, and the clinical relevance of the classification system should be investigated by testing its value as a prognostic factor or a treatment effect modifier. It is recommended that this classification system be combined with psychological and social factors if it is to be useful. Copyright © 2013 Elsevier Ltd. All rights reserved.

A land use and land cover classification system for use with remote sensor data

USGS Publications Warehouse

Anderson, James R.; Hardy, Ernest E.; Roach, John T.; Witmer, Richard E.

1976-01-01

The framework of a national land use and land cover classification system is presented for use with remote sensor data. The classification system has been developed to meet the needs of Federal and State agencies for an up-to-date overview of land use and land cover throughout the country on a basis that is uniform in categorization at the more generalized first and second levels and that will be receptive to data from satellite and aircraft remote sensors. The proposed system uses the features of existing widely used classification systems that are amenable to data derived from remote sensing sources. It is intentionally left open-ended so that Federal, regional, State, and local agencies can have flexibility in developing more detailed land use classifications at the third and fourth levels in order to meet their particular needs and at the same time remain compatible with each other and the national system. Revision of the land use classification system as presented in U.S. Geological Survey Circular 671 was undertaken in order to incorporate the results of extensive testing and review of the categorization and definitions.

Environmental classification scheme for Pontis.

DOT National Transportation Integrated Search

1994-01-01

In an effort to comply with the federal mandate for bridge management systems, many states have chosen to implement an existing system rather than develop their own. One such system is Pontis, the network-level bridge management system developed thro...

Cancer classification in the genomic era: five contemporary problems.

PubMed

Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

2015-10-19

Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification and the successful application of these concepts in precision medicine.

Development of municipal solid waste classification in Korea based on fossil carbon fraction.

PubMed

Lee, Jeongwoo; Kang, Seongmin; Kim, Seungjin; Kim, Ki-Hyun; Jeon, Eui-Chan

2015-10-01

Environmental problems and climate change arising from waste incineration are taken quite seriously in the world. In Korea, the waste disposal methods are largely classified into landfill, incineration, recycling, etc. and the amount of incinerated waste has risen by 24.5% from 2002. In the analysis of CO₂emissions estimations of waste incinerators fossil carbon content are main factor by the IPCC. FCF differs depending on the characteristics of waste in each country, and a wide range of default values are proposed by the IPCC. This study conducted research on the existing classifications of the IPCC and Korean waste classification systems based on FCF for accurate greenhouse gas emissions estimation of waste incineration. The characteristics possible for sorting were classified according to FCF and form. The characteristics sorted according to fossil carbon fraction were paper, textiles, rubber, and leather. Paper was classified into pure paper and processed paper; textiles were classified into cotton and synthetic fibers; and rubber and leather were classified into artificial and natural. The analysis of FCF was implemented by collecting representative samples from each classification group, by applying the 14C method, and using AMS equipment. And the analysis values were compared with the default values proposed by the IPCC. In this study of garden and park waste and plastics, the differences were within the range of the IPCC default values or the differences were negligible. However, coated paper, synthetic textiles, natural rubber, synthetic rubber, artificial leather, and other wastes showed differences of over 10% in FCF content. IPCC is comprised of largely 9 types of qualitative classifications, in emissions estimation a great difference can occur from the combined characteristics according with the existing IPCC classification system by using the minutely classified waste characteristics as in this study. Fossil carbon fraction (FCF) differs depending on the characteristics of waste in each country; and a wide range of default values are proposed by the IPCC. This study conducted research on the existing classifications of the IPCC and Korean waste classification systems based on FCF for accurate greenhouse gas emissions estimation of waste incineration.

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Framework for evaluating disease severity measures in older adults with comorbidity.

PubMed

Boyd, Cynthia M; Weiss, Carlos O; Halter, Jeff; Han, K Carol; Ershler, William B; Fried, Linda P

2007-03-01

Accounting for the influence of concurrent conditions on health and functional status for both research and clinical decision-making purposes is especially important in older adults. Although approaches to classifying severity of individual diseases and conditions have been developed, the utility of these classification systems has not been evaluated in the presence of multiple conditions. We present a framework for evaluating severity classification systems for common chronic diseases. The framework evaluates the: (a) goal or purpose of the classification system; (b) physiological and/or functional criteria for severity graduation; and (c) potential reliability and validity of the system balanced against burden and costs associated with classification. Approaches to severity classification of individual diseases were not originally conceived for the study of comorbidity. Therefore, they vary greatly in terms of objectives, physiological systems covered, level of severity characterization, reliability and validity, and costs and burdens. Using different severity classification systems to account for differing levels of disease severity in a patient with multiple diseases, or, assessing global disease burden may be challenging. Most approaches to severity classification are not adequate to address comorbidity. Nevertheless, thoughtful use of some existing approaches and refinement of others may advance the study of comorbidity and diagnostic and therapeutic approaches to patients with multimorbidity.

A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals

PubMed Central

2014-01-01

Background The inter-patient classification schema and the Association for the Advancement of Medical Instrumentation (AAMI) standards are important to the construction and evaluation of automated heartbeat classification systems. The majority of previously proposed methods that take the above two aspects into consideration use the same features and classification method to classify different classes of heartbeats. The performance of the classification system is often unsatisfactory with respect to the ventricular ectopic beat (VEB) and supraventricular ectopic beat (SVEB). Methods Based on the different characteristics of VEB and SVEB, a novel hierarchical heartbeat classification system was constructed. This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods. First, random projection and support vector machine (SVM) ensemble were used to detect VEB. Then, the ratio of the RR interval was compared to a predetermined threshold to detect SVEB. The optimal parameters for the classification models were selected on the training set and used in the independent testing set to assess the final performance of the classification system. Meanwhile, the effect of different lead configurations on the classification results was evaluated. Results Results showed that the performance of this classification system was notably superior to that of other methods. The VEB detection sensitivity was 93.9% with a positive predictive value of 90.9%, and the SVEB detection sensitivity was 91.1% with a positive predictive value of 42.2%. In addition, this classification process was relatively fast. Conclusions A hierarchical heartbeat classification system was proposed based on the inter-patient data division to detect VEB and SVEB. It demonstrated better classification performance than existing methods. It can be regarded as a promising system for detecting VEB and SVEB of unknown patients in clinical practice. PMID:24981916

[Management of chemical products and European standards: new classification criteria according to the 1272/2008 (CLP) regulation].

PubMed

Fanghella, Paola Di Prospero; Aliberti, Ludovica Malaguti

2013-01-01

The European Union adopted regulations (EC) 1907/2006 REACH e (EC)1272/2008 CLP, to manage chemicals. REACH requires for evaluation and management of risks connected to the use of chemical substances, while o CLP provides for the classification, labelling and packagings of dangerous substances and mixtures by implementing in the EU the UN Globally Harmonised System of Classification and Labelling applying the building block approach, that is taking on board the hazard classes and categories which are close to the existing EU system in order to maintain the level of protection of human health and environment. This regulation provides also for the notification of the classification and labelling of substances to the Classification & Labelling Inventory established by the European Chemicals Agency (ECHA). Some european downstream regulations making reference to the classification criteria, as the health and safety laws at workplace, need to be adapted to these regulations.

Ototoxicity (cochleotoxicity) classifications: A review.

PubMed

Crundwell, Gemma; Gomersall, Phil; Baguley, David M

2016-01-01

Drug-mediated ototoxicity, specifically cochleotoxicity, is a concern for patients receiving medications for the treatment of serious illness. A number of classification schemes exist, most of which are based on pure-tone audiometry, in order to assist non-audiological/non-otological specialists in the identification and monitoring of iatrogenic hearing loss. This review identifies the primary classification systems used in cochleototoxicity monitoring. By bringing together classifications published in discipline-specific literature, the paper aims to increase awareness of their relative strengths and limitations in the assessment and monitoring of ototoxic hearing loss and to indicate how future classification systems may improve upon the status-quo. Literature review. PubMed identified 4878 articles containing the search term ototox*. A systematic search identified 13 key classification systems. Cochleotoxicity classification systems can be divided into those which focus on hearing change from a baseline audiogram and those that focus on the functional impact of the hearing loss. Common weaknesses of these grading scales included a lack of sensitivity to small adverse changes in hearing thresholds, a lack of high-frequency audiometry (>8 kHz), and lack of indication of which changes are likely to be clinically significant for communication and quality of life.

Modeling and performance of HF/OTH (High-Frequency/Over-the-Horizon) radar target identification systems

NASA Astrophysics Data System (ADS)

Strausberger, Donald J.

Several Radar Target Identification (RTI) techniques have been developed at The Ohio State University in recent years. Using the ElectroScience Laboratory compact range a large database of coherent RCS measurement has been constructed for several types of targets (aircraft, ships, and ground vehicles) at a variety of polarizations, aspect angles, and frequency bands. This extensive database has been used to analyze the performance of several different classification algorithms through the use of computer simulations. In order to optimize classification performance, it was concluded that the radar frequency range should lie in the Rayleigh-resonance frequency range, where the wavelength is on the order of or larger than the target size. For aircraft and ships with general dimensions on the order of 10 meters to 100 meters it is apparent that the High Frequency (HF) band provides optimal classification performance. Since existing HF radars are currently being used for detection and tracking or aircraft and ships of these dimensions, it is natural to further investigate the possibility of using these existing radars as the measurement devices in a radar target classification system.

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

Approach for a Clinically Useful Comprehensive Classification of Vascular and Neural Aspects of Diabetic Retinal Disease

PubMed Central

Abramoff, Michael D.; Fort, Patrice E.; Han, Ian C.; Jayasundera, K. Thiran; Sohn, Elliott H.; Gardner, Thomas W.

2018-01-01

The Early Treatment Diabetic Retinopathy Study (ETDRS) and other standardized classification schemes have laid a foundation for tremendous advances in the understanding and management of diabetic retinopathy (DR). However, technological advances in optics and image analysis, especially optical coherence tomography (OCT), OCT angiography (OCTa), and ultra-widefield imaging, as well as new discoveries in diabetic retinal neuropathy (DRN), are exposing the limitations of ETDRS and other classification systems to completely characterize retinal changes in diabetes, which we term diabetic retinal disease (DRD). While it may be most straightforward to add axes to existing classification schemes, as diabetic macular edema (DME) was added as an axis to earlier DR classifications, doing so may make these classifications increasingly complicated and thus clinically intractable. Therefore, we propose future research efforts to develop a new, comprehensive, and clinically useful classification system that will identify multimodal biomarkers to reflect the complex pathophysiology of DRD and accelerate the development of therapies to prevent vision-threatening DRD. PMID:29372250

Approach for a Clinically Useful Comprehensive Classification of Vascular and Neural Aspects of Diabetic Retinal Disease.

PubMed

Abramoff, Michael D; Fort, Patrice E; Han, Ian C; Jayasundera, K Thiran; Sohn, Elliott H; Gardner, Thomas W

2018-01-01

The Early Treatment Diabetic Retinopathy Study (ETDRS) and other standardized classification schemes have laid a foundation for tremendous advances in the understanding and management of diabetic retinopathy (DR). However, technological advances in optics and image analysis, especially optical coherence tomography (OCT), OCT angiography (OCTa), and ultra-widefield imaging, as well as new discoveries in diabetic retinal neuropathy (DRN), are exposing the limitations of ETDRS and other classification systems to completely characterize retinal changes in diabetes, which we term diabetic retinal disease (DRD). While it may be most straightforward to add axes to existing classification schemes, as diabetic macular edema (DME) was added as an axis to earlier DR classifications, doing so may make these classifications increasingly complicated and thus clinically intractable. Therefore, we propose future research efforts to develop a new, comprehensive, and clinically useful classification system that will identify multimodal biomarkers to reflect the complex pathophysiology of DRD and accelerate the development of therapies to prevent vision-threatening DRD.

An updated evolutionary classification of CRISPR–Cas systems

PubMed Central

Makarova, Kira S.; Wolf, Yuri I.; Alkhnbashi, Omer S.; Costa, Fabrizio; Shah, Shiraz A.; Saunders, Sita J.; Barrangou, Rodolphe; Brouns, Stan J. J.; Charpentier, Emmanuelle; Haft, Daniel H.; Horvath, Philippe; Moineau, Sylvain; Mojica, Francisco J. M.; Terns, Rebecca M.; Terns, Michael P.; White, Malcolm F.; Yakunin, Alexander F.; Garrett, Roger A.; van der Oost, John; Backofen, Rolf; Koonin, Eugene V.

2017-01-01

The evolution of CRISPR–cas loci, which encode adaptive immune systems in archaea and bacteria, involves rapid changes, in particular numerous rearrangements of the locus architecture and horizontal transfer of complete loci or individual modules. These dynamics complicate straightforward phylogenetic classification, but here we present an approach combining the analysis of signature protein families and features of the architecture of cas loci that unambiguously partitions most CRISPR–cas loci into distinct classes, types and subtypes. The new classification retains the overall structure of the previous version but is expanded to now encompass two classes, five types and 16 subtypes. The relative stability of the classification suggests that the most prevalent variants of CRISPR–Cas systems are already known. However, the existence of rare, currently unclassifiable variants implies that additional types and subtypes remain to be characterized. PMID:26411297

Medical equipment classification: method and decision-making support based on paraconsistent annotated logic.

PubMed

Oshiyama, Natália F; Bassani, Rosana A; D'Ottaviano, Itala M L; Bassani, José W M

2012-04-01

As technology evolves, the role of medical equipment in the healthcare system, as well as technology management, becomes more important. Although the existence of large databases containing management information is currently common, extracting useful information from them is still difficult. A useful tool for identification of frequently failing equipment, which increases maintenance cost and downtime, would be the classification according to the corrective maintenance data. Nevertheless, establishment of classes may create inconsistencies, since an item may be close to two classes by the same extent. Paraconsistent logic might help solve this problem, as it allows the existence of inconsistent (contradictory) information without trivialization. In this paper, a methodology for medical equipment classification based on the ABC analysis of corrective maintenance data is presented, and complemented with a paraconsistent annotated logic analysis, which may enable the decision maker to take into consideration alerts created by the identification of inconsistencies and indeterminacies in the classification.

The Adam Walsh Act: An Examination of Sex Offender Risk Classification Systems.

PubMed

Zgoba, Kristen M; Miner, Michael; Levenson, Jill; Knight, Raymond; Letourneau, Elizabeth; Thornton, David

2016-12-01

This study was designed to compare the Adam Walsh Act (AWA) classification tiers with actuarial risk assessment instruments and existing state classification schemes in their respective abilities to identify sex offenders at high risk to re-offend. Data from 1,789 adult sex offenders released from prison in four states were collected (Minnesota, New Jersey, Florida, and South Carolina). On average, the sexual recidivism rate was approximately 5% at 5 years and 10% at 10 years. AWA Tier 2 offenders had higher Static-99R scores and higher recidivism rates than Tier 3 offenders, and in Florida, these inverse correlations were statistically significant. Actuarial measures and existing state tier systems, in contrast, did a better job of identifying high-risk offenders and recidivists. As well, we examined the distribution of risk assessment scores within and across tier categories, finding that a majority of sex offenders fall into AWA Tier 3, but more than half score low or moderately low on the Static-99R. The results indicate that the AWA sex offender classification scheme is a poor indicator of relative risk and is likely to result in a system that is less effective in protecting the public than those currently implemented in the states studied. © The Author(s) 2015.

Compensatory neurofuzzy model for discrete data classification in biomedical

NASA Astrophysics Data System (ADS)

Ceylan, Rahime

2015-03-01

Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

A Global Classification System for Catchment Hydrology

NASA Astrophysics Data System (ADS)

Woods, R. A.

2004-05-01

It is a shocking state of affairs - there is no underpinning scientific taxonomy of catchments. There are widely used global classification systems for climate, river morphology, lakes and wetlands, but for river catchments there exists only a plethora of inconsistent, incomplete regional schemes. By proceeding without a common taxonomy for catchments, freshwater science has missed one of its key developmental stages, and has leapt from definition of phenomena to experiments, theories and models, without the theoretical framework of a classification. I propose the development of a global hierarchical classification system for physical aspects of river catchments, to help underpin physical science in the freshwater environment and provide a solid foundation for classification of river ecosystems. Such a classification scheme can open completely new vistas in hydrology: for example it will be possible to (i) rationally transfer experimental knowledge of hydrological processes between basins anywhere in the world, provided they belong to the same class; (ii) perform meaningful meta-analyses in order to reconcile studies that show inconsistent results (iii) generate new testable hypotheses which involve locations worldwide.

Keratoconus: The ABCD Grading System.

PubMed

Belin, M W; Duncan, J K

2016-06-01

To propose a new keratoconus classification/staging system that utilises current tomographic data and better reflects the anatomical and functional changes seen in keratoconus. A previously published normative database was reanalysed to generate both anterior and posterior average radii of curvature (ARC and PRC) taken from a 3.0 mm optical zone centred on the thinnest point of the cornea. Mean and standard deviations were recorded and anterior data were compared to the existing Amsler-Krumeich (AK) Classification. ARC, PRC, thinnest pachymetry and distance visual acuity were then used to construct a keratoconus classification. 672 eyes of 336 patients were analysed. Anterior and posterior values were 7.65 ± 0.236 mm and 6.26 ± 0.214 mm, respectively, and thinnest pachymetry values were 534.2 ± 30.36 µm. The ARC values were 2.63, 5.47 and 6.44 standard deviations from the mean values of stages 1-3 in the AK classification, respectively. PRC staging uses the same standard deviation gates. The pachymetric values differed by 4.42 and 7.72 standard deviations for stages 2 and 3, respectively. A new keratoconus staging incorporates anterior and posterior curvature, thinnest pachymetric values, and distance visual acuity and consists of stages 0-4 (5 stages). The proposed system closely matches the existing AK classification stages 1-4 on anterior curvature. As it incorporates posterior curvature and thickness measurements based on the thinnest point, rather than apical measurements, the new staging system better reflects the anatomical changes seen in keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

Stroke subtyping for genetic association studies? A comparison of the CCS and TOAST classifications.

PubMed

Lanfranconi, Silvia; Markus, Hugh S

2013-12-01

A reliable and reproducible classification system of stroke subtype is essential for epidemiological and genetic studies. The Causative Classification of Stroke system is an evidence-based computerized algorithm with excellent inter-rater reliability. It has been suggested that, compared to the Trial of ORG 10172 in Acute Stroke Treatment classification, it increases the proportion of cases with defined subtype that may increase power in genetic association studies. We compared Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications in a large cohort of well-phenotyped stroke patients. Six hundred ninety consecutively recruited patients with first-ever ischemic stroke were classified, using review of clinical data and original imaging, according to the Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications. There was excellent agreement subtype assigned by between Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system (kappa = 0·85). The agreement was excellent for the major individual subtypes: large artery atherosclerosis kappa = 0·888, small-artery occlusion kappa = 0·869, cardiac embolism kappa = 0·89, and undetermined category kappa = 0·884. There was only moderate agreement (kappa = 0·41) for the subjects with at least two competing underlying mechanism. Thirty-five (5·8%) patients classified as undetermined by Trial of ORG 10172 in Acute Stroke Treatment were assigned to a definite subtype by Causative Classification of Stroke system. Thirty-two subjects assigned to a definite subtype by Trial of ORG 10172 in Acute Stroke Treatment were classified as undetermined by Causative Classification of Stroke system. There is excellent agreement between classification using Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke systems but no evidence that Causative Classification of Stroke system reduced the proportion of patients classified to undetermined subtypes. The excellent inter-rater reproducibility and web-based semiautomated nature make Causative Classification of Stroke system suitable for multicenter studies, but the benefit of reclassifying cases already classified using the Trial of ORG 10172 in Acute Stroke Treatment system on existing databases is likely to be small. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.

Stygoregions – a promising approach to a bioregional classification of groundwater systems

PubMed Central

Stein, Heide; Griebler, Christian; Berkhoff, Sven; Matzke, Dirk; Fuchs, Andreas; Hahn, Hans Jürgen

2012-01-01

Linked to diverse biological processes, groundwater ecosystems deliver essential services to mankind, the most important of which is the provision of drinking water. In contrast to surface waters, ecological aspects of groundwater systems are ignored by the current European Union and national legislation. Groundwater management and protection measures refer exclusively to its good physicochemical and quantitative status. Current initiatives in developing ecologically sound integrative assessment schemes by taking groundwater fauna into account depend on the initial classification of subsurface bioregions. In a large scale survey, the regional and biogeographical distribution patterns of groundwater dwelling invertebrates were examined for many parts of Germany. Following an exploratory approach, our results underline that the distribution patterns of invertebrates in groundwater are not in accordance with any existing bioregional classification system established for surface habitats. In consequence, we propose to develope a new classification scheme for groundwater ecosystems based on stygoregions. PMID:22993698

Three approaches to the classification of inland wetlands. [Dismal Swamp, Tennessee, and Florida

NASA Technical Reports Server (NTRS)

Gammon, P. T.; Malone, D.; Brooks, P. D.; Carter, V.

1977-01-01

In the Dismal Swamp project, seasonal, color-infrared aerial photographs and LANDSAT digital data were interpreted for a detailed analysis of the vegetative communities in a large, highly altered wetland. In Western Tennessee, seasonal high altitude color-infrared aerial photographs provided the hydrologic and vegetative information needed to map inland wetlands, using a classification system developed for the Tennessee Valley Region. In Florida, color-infrared aerial photographs were analyzed to produce wetland maps using three existing classification systems to evaluate the information content and mappability of each system. The methods used in each of the three projects can be extended or modified for use in the mapping of inland wetlands in other parts of the United States.

Poisoning by Herbs and Plants: Rapid Toxidromic Classification and Diagnosis.

PubMed

Diaz, James H

2016-03-01

The American Association of Poison Control Centers has continued to report approximately 50,000 telephone calls or 8% of incoming calls annually related to plant exposures, mostly in children. Although the frequency of plant ingestions in children is related to the presence of popular species in households, adolescents may experiment with hallucinogenic plants; and trekkers and foragers may misidentify poisonous plants as edible. Since plant exposures have continued at a constant rate, the objectives of this review were (1) to review the epidemiology of plant poisonings; and (2) to propose a rapid toxidromic classification system for highly toxic plant ingestions for field use by first responders in comparison to current classification systems. Internet search engines were queried to identify and select peer-reviewed articles on plant poisonings using the key words in order to classify plant poisonings into four specific toxidromes: cardiotoxic, neurotoxic, cytotoxic, and gastrointestinal-hepatotoxic. A simple toxidromic classification system of plant poisonings may permit rapid diagnoses of highly toxic versus less toxic and nontoxic plant ingestions both in households and outdoors; direct earlier management of potentially serious poisonings; and reduce costly inpatient evaluations for inconsequential plant ingestions. The current textbook classification schemes for plant poisonings were complex in comparison to the rapid classification system; and were based on chemical nomenclatures and pharmacological effects, and not on clearly presenting toxidromes. Validation of the rapid toxidromic classification system as compared to existing chemical classification systems for plant poisonings will require future adoption and implementation of the toxidromic system by its intended users. Copyright © 2016 Wilderness Medical Society. Published by Elsevier Inc. All rights reserved.

Property Specification Patterns for intelligence building software

NASA Astrophysics Data System (ADS)

Chun, Seungsu

2018-03-01

In this paper, through the property specification pattern research for Modal MU(μ) logical aspects present a single framework based on the pattern of intelligence building software. In this study, broken down by state property specification pattern classification of Dwyer (S) and action (A) and was subdivided into it again strong (A) and weaknesses (E). Through these means based on a hierarchical pattern classification of the property specification pattern analysis of logical aspects Mu(μ) was applied to the pattern classification of the examples used in the actual model checker. As a result, not only can a more accurate classification than the existing classification systems were easy to create and understand the attributes specified.

Oregon ground-water quality and its relation to hydrogeological factors; a statistical approach

USGS Publications Warehouse

Miller, T.L.; Gonthier, J.B.

1984-01-01

An appraisal of Oregon ground-water quality was made using existing data accessible through the U.S. Geological Survey computer system. The data available for about 1,000 sites were separated by aquifer units and hydrologic units. Selected statistical moments were described for 19 constituents including major ions. About 96 percent of all sites in the data base were sampled only once. The sample data were classified by aquifer unit and hydrologic unit and analysis of variance was run to determine if significant differences exist between the units within each of these two classifications for the same 19 constituents on which statistical moments were determined. Results of the analysis of variance indicated both classification variables performed about the same, but aquifer unit did provide more separation for some constituents. Samples from the Rogue River basin were classified by location within the flow system and type of flow system. The samples were then analyzed using analysis of variance on 14 constituents to determine if there were significant differences between subsets classified by flow path. Results of this analysis were not definitive, but classification as to the type of flow system did indicate potential for segregating water-quality data into distinct subsets. (USGS)

[Classification of memory systems: a revision].

PubMed

Agrest, M

2001-12-01

The present paper exposes the arguments against considering memory as a monolytic entity and how is it to be divided into several systems in order to understand its operation. Historically this division was acknowledge by different authors but in the last few decades it received the confirmation from the scientific research. The most accepted taxonomy establishes the existence of two major memory systems: declarative and non declarative memory. The article also presents the arguments for and against this kind of division, as well as an alternative classification in five major systems: procedural, perceptual representation, semantic, primary and episodic.

Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor

NASA Astrophysics Data System (ADS)

Rahman, Husna Abdul; Harun, Sulaiman Wadi; Arof, Hamzah; Irawati, Ninik; Musirin, Ismail; Ibrahim, Fatimah; Ahmad, Harith

2014-05-01

An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.

Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor.

PubMed

Rahman, Husna Abdul; Harun, Sulaiman Wadi; Arof, Hamzah; Irawati, Ninik; Musirin, Ismail; Ibrahim, Fatimah; Ahmad, Harith

2014-05-01

An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.

Interrater reliability of a Pilates movement-based classification system.

PubMed

Yu, Kwan Kenny; Tulloch, Evelyn; Hendrick, Paul

2015-01-01

To determine the interrater reliability for identification of a specific movement pattern using a Pilates Classification system. Videos of 5 subjects performing specific movement tasks were sent to raters trained in the DMA-CP classification system. Ninety-six raters completed the survey. Interrater reliability for the detection of a directional bias was excellent (Pi = 0.92, and K(free) = 0.89). Interrater reliability for classifying an individual into a specific subgroup was moderate (Pi = 0.64, K(free) = 0.55) however raters who had completed levels 1-4 of the DMA-CP training and reported using the assessment daily demonstrated excellent reliability (Pi = 0.89 and K(free) = 0.87). The reliability of the classification system demonstrated almost perfect agreement in determining the existence of a specific movement pattern and classifying into a subgroup for experienced raters. There was a trend for greater reliability associated with increased levels of training and experience of the raters. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Classification of Hysteria and Related Disorders: Historical and Phenomenological Considerations

PubMed Central

North, Carol S.

2015-01-01

This article examines the history of the conceptualization of dissociative, conversion, and somatoform syndromes in relation to one another, chronicles efforts to classify these and other phenomenologically-related psychopathology in the American diagnostic system for mental disorders, and traces the subsequent divergence in opinions of dissenting sectors on classification of these disorders. This article then considers the extensive phenomenological overlap across these disorders in empirical research, and from this foundation presents a new model for the conceptualization of these disorders. The classification of disorders formerly known as hysteria and phenomenologically-related syndromes has long been contentious and unsettled. Examination of the long history of the conceptual difficulties, which remain inherent in existing classification schemes for these disorders, can help to address the continuing controversy. This review clarifies the need for a major conceptual revision of the current classification of these disorders. A new phenomenologically-based classification scheme for these disorders is proposed that is more compatible with the agnostic and atheoretical approach to diagnosis of mental disorders used by the current classification system. PMID:26561836

A structural classification for inland northwest forest vegetation.

Treesearch

Kevin L. O' Hara; Penelope A. Latham; Paul Hessburg; Bradley G. Smith

1996-01-01

Existing approaches to vegetation classification range from those bassed on potential vegetation to others based on existing vegetation composition, or existing structural or physiognomic characteristics. Examples of these classifications are numerous, and in some cases, date back hundreds of years (Mueller-Dumbois and Ellenberg 1974). Small-scale or stand level...

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

TNM-O: ontology support for staging of malignant tumours.

PubMed

Boeker, Martin; França, Fábio; Bronsert, Peter; Schulz, Stefan

2016-11-14

Objectives of this work are to (1) present an ontological framework for the TNM classification system, (2) exemplify this framework by an ontology for colon and rectum tumours, and (3) evaluate this ontology by assigning TNM classes to real world pathology data. The TNM ontology uses the Foundational Model of Anatomy for anatomical entities and BioTopLite 2 as a domain top-level ontology. General rules for the TNM classification system and the specific TNM classification for colorectal tumours were axiomatised in description logic. Case-based information was collected from tumour documentation practice in the Comprehensive Cancer Centre of a large university hospital. Based on the ontology, a module was developed that classifies pathology data. TNM was represented as an information artefact, which consists of single representational units. Corresponding to every representational unit, tumours and tumour aggregates were defined. Tumour aggregates consist of the primary tumour and, if existing, of infiltrated regional lymph nodes and distant metastases. TNM codes depend on the location and certain qualities of the primary tumour (T), the infiltrated regional lymph nodes (N) and the existence of distant metastases (M). Tumour data from clinical and pathological documentation were successfully classified with the ontology. A first version of the TNM Ontology represents the TNM system for the description of the anatomical extent of malignant tumours. The present work demonstrates its representational power and completeness as well as its applicability for classification of instance data.

UAS-SfM for coastal research: Geomorphic feature extraction and land cover classification from high-resolution elevation and optical imagery

USGS Publications Warehouse

Sturdivant, Emily; Lentz, Erika; Thieler, E. Robert; Farris, Amy; Weber, Kathryn; Remsen, David P.; Miner, Simon; Henderson, Rachel

2017-01-01

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.

A practicable approach for periodontal classification

PubMed Central

Mittal, Vishnu; Bhullar, Raman Preet K.; Bansal, Rachita; Singh, Karanprakash; Bhalodi, Anand; Khinda, Paramjit K.

2013-01-01

The Diagnosis and classification of periodontal diseases has remained a dilemma since long. Two distinct concepts have been used to define diseases: Essentialism and Nominalism. Essentialistic concept implies the real existence of disease whereas; nominalistic concept states that the names of diseases are the convenient way of stating concisely the endpoint of a diagnostic process. It generally advances from assessment of symptoms and signs toward knowledge of causation and gives a feasible option to name the disease for which etiology is either unknown or it is too complex to access in routine clinical practice. Various classifications have been proposed by the American Academy of Periodontology (AAP) in 1986, 1989 and 1999. The AAP 1999 classification is among the most widely used classification. But this classification also has demerits which provide impediment for its use in day to day practice. Hence a classification and diagnostic system is required which can help the clinician to access the patient's need and provide a suitable treatment which is in harmony with the diagnosis for that particular case. Here is an attempt to propose a practicable classification and diagnostic system of periodontal diseases for better treatment outcome. PMID:24379855

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

PubMed

Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

2018-04-01

Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic, prosthetic, and industrial applications.

Classifier dependent feature preprocessing methods

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M., II; Peterson, Gilbert L.

2008-04-01

In mobile applications, computational complexity is an issue that limits sophisticated algorithms from being implemented on these devices. This paper provides an initial solution to applying pattern recognition systems on mobile devices by combining existing preprocessing algorithms for recognition. In pattern recognition systems, it is essential to properly apply feature preprocessing tools prior to training classification models in an attempt to reduce computational complexity and improve the overall classification accuracy. The feature preprocessing tools extended for the mobile environment are feature ranking, feature extraction, data preparation and outlier removal. Most desktop systems today are capable of processing a majority of the available classification algorithms without concern of processing while the same is not true on mobile platforms. As an application of pattern recognition for mobile devices, the recognition system targets the problem of steganalysis, determining if an image contains hidden information. The measure of performance shows that feature preprocessing increases the overall steganalysis classification accuracy by an average of 22%. The methods in this paper are tested on a workstation and a Nokia 6620 (Symbian operating system) camera phone with similar results.

Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

PubMed

Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

2017-06-01

Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

Comments on the 2001 WHO proposal for the classification of haematopoietic neoplasms.

PubMed

Paietta, Elisabeth

2003-12-01

In the preface, the World Health Organization (WHO) classification vows to offer pathologists, oncologists and geneticists worldwide a system of classification for human neoplasms based on histopathological and genetic features. Standardization of nomenclature and agreed-upon criteria for definition of the various types of cancer are felt to be a prerequisite for progress in clinical oncology, multicentre therapy trials and comparative studies in different countries. In fact, the WHO effort represents the first worldwide comprehensive consensus classification of the haematological malignancies. Consensus was reached among a subgroup of investigators, carefully selected for their experience and contributions to existing classifications. In the present climate of daily new discoveries that yield a constant stream of fascinating insights into the biology of leukaemias and lymphomas and, above all, resulting in an explosion of potential therapeutic targets, the WHO system has taken the stand of compiling established classification approaches and providing order to known facts. This furnishes an essential skeleton upon which to build in the future. The WHO committee decided that sorting neoplasms according to prognosis was neither practical nor necessary and could be misleading. While justifiable at the present time, it is important to realize that the classifications of the haematological malignancies are a moving target and that the trend is to move away from currently accepted gold standards, such as morphological evaluations, in favour of genetic characterizations, especially those with therapeutic relevance. The goal of this chapter is to fill in some gaps that, as per the author's opinion, exist in the WHO classification, predominantly, where it concerns the role of immunophenotyping as a complementary discipline for genotyping through its potential to generate surrogate marker profiles for molecular lesions. By introducing some state-of-the-art classification modalities, some of which are still awaiting confirmation, this chapter also aims to spark excitement and provide a glimpse at the future.

75 FR 53339 - Notice of Realty Action; Recreation and Public Purposes Act Classification for Conveyance of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-31

... existing landfill. DATES: Interested parties may submit written comments regarding this classification for... . Please reference ``Conveyance of Federal Land to Emery County for Expansion of an Existing Landfill'' on... suitability of the land for the expansion of the existing county landfill. Comments on the classification are...

A Spiking Neural Network in sEMG Feature Extraction.

PubMed

Lobov, Sergey; Mironov, Vasiliy; Kastalskiy, Innokentiy; Kazantsev, Victor

2015-11-03

We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control.

The Advantages and Limitations of International Classification of Diseases, Injuries and Causes of Death from Aspect of Existing Health Care System of Bosnia and Herzegovina

PubMed Central

Kurbasic, Izeta; Pandza, Haris; Masic, Izet; Huseinagic, Senad; Tandir, Salih; Alicajic, Fredi; Toromanovic, Selim

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Introduction The International classification of diseases (ICD) is the most important classification in medicine. It is used by all medical professionals. Concept The basic concept of ICD is founded on the standardization of the nomenclature for the names of diseases and their basic systematization in the hierarchically structured category. Advantages and disadvantages The health care provider institutions such as hospitals are subjects that should facilitate implementation of medical applications that follows the patient medical condition and facts connected with him. The definitive diagnosis that can be coded using ICD can be achieved after several visits of patient and rarely during the first visit. Conclusion The ICD classification is one of the oldest and most important classifications in medicine. In the scope of ICD are all fields of medicine. It is used in statistical purpose and as a coding system in medical databases. PMID:24109155

Classification of Unmanned Aircraft Systems. UAS Classification/Categorization for Certification

NASA Technical Reports Server (NTRS)

2004-01-01

Category, class, and type designations are primary means to identify appropriate aircraft certification basis, operating rules/limitations, and pilot qualifications to operate in the National Airspace System (NAS). The question is whether UAS fit into existing aircraft categories or classes, or are unique enough to justify the creation of a new category/class. In addition, the characteristics or capabilities, which define when an UAS becomes a regulated aircraft, must also be decided. This issue focuses on UAS classification for certification purposes. Several approaches have been considered for classifying UAS. They basically group into either using a weight/mass basis, or a safety risk basis, factoring in the performance of the UAS, including where the UAS would operate. Under existing standards, aircraft must have a Type Certificate and Certificate of Airworthiness, in order to be used for "compensation or hire", a major difference from model aircraft. Newer technologies may make it possible for very small UAS to conduct commercial services, but that is left for a future discussion to extend the regulated aircraft to a lower level. The Access 5 position is that UAS are aircraft and should be regulated above the weight threshold differentiating them from model airplanes. The recommended classification grouping is summarized in a chart.

Increasing CAD system efficacy for lung texture analysis using a convolutional network

NASA Astrophysics Data System (ADS)

Tarando, Sebastian Roberto; Fetita, Catalin; Faccinetto, Alex; Brillet, Pierre-Yves

2016-03-01

The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. For the large majority of CAD systems, such classification relies on a two-dimensional analysis of axial CT images. In a previously developed CAD system, we proposed a fully-3D approach exploiting a multi-scale morphological analysis which showed good performance in detecting diseased areas, but with a major drawback consisting of sometimes overestimating the pathological areas and mixing different type of lung patterns. This paper proposes a combination of the existing CAD system with the classification outcome provided by a convolutional network, specifically tuned-up, in order to increase the specificity of the classification and the confidence to diagnosis. The advantage of using a deep learning approach is a better regularization of the classification output (because of a deeper insight into a given pathological class over a large series of samples) where the previous system is extra-sensitive due to the multi-scale response on patient-specific, localized patterns. In a preliminary evaluation, the combined approach was tested on a 10 patient database of various lung pathologies, showing a sharp increase of true detections.

IRIS COLOUR CLASSIFICATION SCALES – THEN AND NOW

PubMed Central

Grigore, Mariana; Avram, Alina

2015-01-01

Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual’s eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale. PMID:27373112

IRIS COLOUR CLASSIFICATION SCALES--THEN AND NOW.

PubMed

Grigore, Mariana; Avram, Alina

2015-01-01

Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual's eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale.

Cue-based assertion classification for Swedish clinical text – developing a lexicon for pyConTextSwe

PubMed Central

Velupillai, Sumithra; Skeppstedt, Maria; Kvist, Maria; Mowery, Danielle; Chapman, Brian E.; Dalianis, Hercules; Chapman, Wendy W.

2014-01-01

Objective The ability of a cue-based system to accurately assert whether a disorder is affirmed, negated, or uncertain is dependent, in part, on its cue lexicon. In this paper, we continue our study of porting an assertion system (pyConTextNLP) from English to Swedish (pyConTextSwe) by creating an optimized assertion lexicon for clinical Swedish. Methods and material We integrated cues from four external lexicons, along with generated inflections and combinations. We used subsets of a clinical corpus in Swedish. We applied four assertion classes (definite existence, probable existence, probable negated existence and definite negated existence) and two binary classes (existence yes/no and uncertainty yes/no) to pyConTextSwe. We compared pyConTextSwe’s performance with and without the added cues on a development set, and improved the lexicon further after an error analysis. On a separate evaluation set, we calculated the system’s final performance. Results Following integration steps, we added 454 cues to pyConTextSwe. The optimized lexicon developed after an error analysis resulted in statistically significant improvements on the development set (83% F-score, overall). The system’s final F-scores on an evaluation set were 81% (overall). For the individual assertion classes, F-score results were 88% (definite existence), 81% (probable existence), 55% (probable negated existence), and 63% (definite negated existence). For the binary classifications existence yes/no and uncertainty yes/no, final system performance was 97%/87% and 78%/86% F-score, respectively. Conclusions We have successfully ported pyConTextNLP to Swedish (pyConTextSwe). We have created an extensive and useful assertion lexicon for Swedish clinical text, which could form a valuable resource for similar studies, and which is publicly available. PMID:24556644

An incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

Considerations of Unmanned Aircraft Classification for Civil Airworthiness Standards

NASA Technical Reports Server (NTRS)

Maddalon, Jeffrey M.; Hayhurst, Kelly J.; Morris, A. Terry; Verstynen, Harry A.

2013-01-01

The use of unmanned aircraft in the National Airspace System (NAS) has been characterized as the next great step forward in the evolution of civil aviation. Although use of unmanned aircraft systems (UAS) in military and public service operations is proliferating, civil use of UAS remains limited in the United States today. This report focuses on one particular regulatory challenge: classifying UAS to assign airworthiness standards. Classification is useful for ensuring that meaningful differences in design are accommodated by certification to different standards, and that aircraft with similar risk profiles are held to similar standards. This paper provides observations related to how the current regulations for classifying manned aircraft, based on dimensions of aircraft class and operational aircraft categories, could apply to UAS. This report finds that existing aircraft classes are well aligned with the types of UAS that currently exist; however, the operational categories are more difficult to align to proposed UAS use in the NAS. Specifically, the factors used to group manned aircraft into similar risk profiles do not necessarily capture all relevant UAS risks. UAS classification is investigated through gathering approaches to classification from a broad spectrum of organizations, and then identifying and evaluating the classification factors from these approaches. This initial investigation concludes that factors in addition to those currently used today to group manned aircraft for the purpose of assigning airworthiness standards will be needed to adequately capture risks associated with UAS and their operations.

[Reproducibility of the use of classifications of causes of death in the context of inquiries in perinatal mortality].

PubMed

Rajmil, L; Plasencia, A; Borrell, C

1993-11-01

The objective of this study was to verify the reliability of the classifications of perinatal mortality causes. An independent observer coded the cases of perinatal death (n = 152) collected in the Encuesta Confidencial de Mortalidad Perinatal de Barcelona (ECMP, Confidential Perinatal Mortality Inquiry of Barcelona), by using both the Aberdeen classification system (regarding obstetric factors) and the Wigglesworth classification system (according to the initial pathological cause), with the same information used previously by the ECMP Commission. For the Aberdeen classification, the observed concordance index (Po) was 86% and the Kappa coefficient (K) 0.77 (95% CI: 0.68-0.86). For the Wigglesworth classification, the figures were 89% and 0.82 (95% CI: 0.74-0.90), respectively. The disagreement was mainly due to differences in the interpretation of the sequence of death, minimal information available in order to classify the cause of death, and misunderstanding of the existing information. To a lesser extent, the disagreement was caused by a failure to comply with the rules laid down for classifications. The assessment of the causes of death was not significantly influenced by birth weight, gestational age, time of death or the presence of necropsy. These results support the use of classifications of perinatal mortality causes in the context of confidential inquiries.

Seeking order amidst chaos: a systematic review of classification systems for causes of stillbirth and neonatal death, 2009-2014.

PubMed

Leisher, Susannah Hopkins; Teoh, Zheyi; Reinebrant, Hanna; Allanson, Emma; Blencowe, Hannah; Erwich, Jan Jaap; Frøen, J Frederik; Gardosi, Jason; Gordijn, Sanne; Gülmezoglu, A Metin; Heazell, Alexander E P; Korteweg, Fleurisca; Lawn, Joy; McClure, Elizabeth M; Pattinson, Robert; Smith, Gordon C S; Tunçalp, Ӧzge; Wojcieszek, Aleena M; Flenady, Vicki

2016-10-05

Each year, about 5.3 million babies die in the perinatal period. Understanding of causes of death is critical for prevention, yet there is no globally acceptable classification system. Instead, many disparate systems have been developed and used. We aimed to identify all systems used or created between 2009 and 2014, with their key features, including extent of alignment with the International Classification of Diseases (ICD) and variation in features by region, to inform the World Health Organization's development of a new global approach to classifying perinatal deaths. A systematic literature review (CINAHL, EMBASE, Medline, Global Health, and PubMed) identified published and unpublished studies and national reports describing new classification systems or modifications of existing systems for causes of perinatal death, or that used or tested such systems, between 2009 and 2014. Studies reporting ICD use only were excluded. Data were independently double-extracted (except from non-English publications). Subgroup analyses explored variation by extent and region. Eighty-one systems were identified as new, modifications of existing systems, or having been used between 2009 and 2014, with an average of ten systems created/modified each year. Systems had widely varying characteristics: (i) comprehensiveness (40 systems classified both stillbirths and neonatal deaths); (ii) extent of use (systems were created in 28 countries and used in 40; 17 were created for national use; 27 were widely used); (iii) accessibility (three systems available in e-format); (iv) underlying cause of death (64 systems required a single cause of death); (v) reliability (10 systems tested for reliability, with overall Kappa scores ranging from .35-.93); and (vi) ICD alignment (17 systems used ICD codes). Regional databases were not searched, so system numbers may be underestimated. Some non-differential misclassification of systems was possible. The plethora of systems in use, and continuing system development, hamper international efforts to improve understanding of causes of death. Recognition of the features of currently used systems, combined with a better understanding of the drivers of continued system creation, may help the development of a truly effective global system.

Classifying breast cancer surgery: a novel, complexity-based system for oncological, oncoplastic and reconstructive procedures, and proof of principle by analysis of 1225 operations in 1166 patients.

PubMed

Hoffmann, Jürgen; Wallwiener, Diethelm

2009-04-08

One of the basic prerequisites for generating evidence-based data is the availability of classification systems. Attempts to date to classify breast cancer operations have focussed on specific problems, e.g. the avoidance of secondary corrective surgery for surgical defects, rather than taking a generic approach. Starting from an existing, simpler empirical scheme based on the complexity of breast surgical procedures, which was used in-house primarily in operative report-writing, a novel classification of ablative and breast-conserving procedures initially needed to be developed and elaborated systematically. To obtain proof of principle, a prospectively planned analysis of patient records for all major breast cancer-related operations performed at our breast centre in 2005 and 2006 was conducted using the new classification. Data were analysed using basic descriptive statistics such as frequency tables. A novel two-type, six-tier classification system comprising 12 main categories, 13 subcategories and 39 sub-subcategories of oncological, oncoplastic and reconstructive breast cancer-related surgery was successfully developed. Our system permitted unequivocal classification, without exception, of all 1225 procedures performed in 1166 breast cancer patients in 2005 and 2006. Breast cancer-related surgical procedures can be generically classified according to their surgical complexity. Analysis of all major procedures performed at our breast centre during the study period provides proof of principle for this novel classification system. We envisage various applications for this classification, including uses in randomised clinical trials, guideline development, specialist surgical training, continuing professional development as well as quality of care and public health research.

Improving the Selection, Classification, and Utilization of Army Enlisted Personnel: Final Report on Project A

DTIC Science & Technology

1991-08-01

being used in both current and long-range research programs that are expected to make the Army more effective in matching the requirements for first- and... make substantial improvements to the existing selection and classifi- cation system. xi IMPROVING THE SELECTION, CLASSIFICATION, AND UTILIZATION OF...basis for new methods of allocating personnel, and making near-real-time decisions on the best match between characteristics of an individual enlistee

A Study of MX Environmental Management Information System (MXEMIS) Needs.

DTIC Science & Technology

1983-12-01

ENVIRONMENTAL MANAGEMENT INFORMATION SYSTEM (MXEMIS) NEEDS by Ronald Webster Ralph Mitchell Valorie Young -J : 2 34 LA--. Approved for public release...System (SAIFS) The MX Management Information System (MX MIS) The Mobilization Early Warning System (MEWS) The Computer-Aided Environmental Baseline...26 REFERENCES DISTRIBUTION I5 S’ t A STUDY OF MX ENVIRONMENTAL 2 EXISTING SYSTEMS CLASSIFICATION MANAGEMENT INFORMATION SYSTEM (MXEMIS

Development and initial validation of the Classification of Early-Onset Scoliosis (C-EOS).

PubMed

Williams, Brendan A; Matsumoto, Hiroko; McCalla, Daren J; Akbarnia, Behrooz A; Blakemore, Laurel C; Betz, Randal R; Flynn, John M; Johnston, Charles E; McCarthy, Richard E; Roye, David P; Skaggs, David L; Smith, John T; Snyder, Brian D; Sponseller, Paul D; Sturm, Peter F; Thompson, George H; Yazici, Muharrem; Vitale, Michael G

2014-08-20

Early-onset scoliosis is a heterogeneous condition, with highly variable manifestations and natural history. No standardized classification system exists to describe and group patients, to guide optimal care, or to prognosticate outcomes within this population. A classification system for early-onset scoliosis is thus a necessary prerequisite to the timely evolution of care of these patients. Fifteen experienced surgeons participated in a nominal group technique designed to achieve a consensus-based classification system for early-onset scoliosis. A comprehensive list of factors important in managing early-onset scoliosis was generated using a standardized literature review, semi-structured interviews, and open forum discussion. Three group meetings and two rounds of surveying guided the selection of classification components, subgroupings, and cut-points. Initial validation of the system was conducted using an interobserver reliability assessment based on the classification of a series of thirty cases. Nominal group technique was used to identify three core variables (major curve angle, etiology, and kyphosis) with high group content validity scores. Age and curve progression ranked slightly lower. Participants evaluated the cases of thirty patients with early-onset scoliosis for reliability testing. The mean kappa value for etiology (0.64) was substantial, while the mean kappa values for major curve angle (0.95) and kyphosis (0.93) indicated almost perfect agreement. The final classification consisted of a continuous age prefix, etiology (congenital or structural, neuromuscular, syndromic, and idiopathic), major curve angle (1, 2, 3, or 4), and kyphosis (-, N, or +) variables, and an optional progression modifier (P0, P1, or P2). Utilizing formal consensus-building methods in a large group of surgeons experienced in treating early-onset scoliosis, a novel classification system for early-onset scoliosis was developed with all core components demonstrating substantial to excellent interobserver reliability. This classification system will serve as a foundation to guide ongoing research efforts and standardize communication in the clinical setting. Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

PubMed

Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

2018-04-01

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Cascade of convolutional neural networks for lung texture classification: overcoming ontological overlapping

NASA Astrophysics Data System (ADS)

Tarando, Sebastian Roberto; Fetita, Catalin; Brillet, Pierre-Yves

2017-03-01

The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. Traditionally, such classification relies on a two-dimensional analysis of axial CT images. This paper proposes a cascade of the existing CNN based CAD system, specifically tuned-up. The advantage of using a deep learning approach is a better regularization of the classification output. In a preliminary evaluation, the combined approach was tested on a 13 patient database of various lung pathologies, showing an increase of 10% in True Positive Rate (TPR) with respect to the best suited state of the art CNN for this task.

Analysis of DSN software anomalies

NASA Technical Reports Server (NTRS)

Galorath, D. D.; Hecht, H.; Hecht, M.; Reifer, D. J.

1981-01-01

A categorized data base of software errors which were discovered during the various stages of development and operational use of the Deep Space Network DSN/Mark 3 System was developed. A study team identified several existing error classification schemes (taxonomies), prepared a detailed annotated bibliography of the error taxonomy literature, and produced a new classification scheme which was tuned to the DSN anomaly reporting system and encapsulated the work of others. Based upon the DSN/RCI error taxonomy, error data on approximately 1000 reported DSN/Mark 3 anomalies were analyzed, interpreted and classified. Next, error data are summarized and histograms were produced highlighting key tendencies.

Model-based object classification using unification grammars and abstract representations

NASA Astrophysics Data System (ADS)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

Towards an International Classification for Patient Safety: the conceptual framework.

PubMed

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-02-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose.

Towards an International Classification for Patient Safety: the conceptual framework

PubMed Central

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-01-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose. PMID:19147595

Site classification of ponderosa pine stands under stocking control in California

Treesearch

Robert F. Powers; William W. Oliver

1978-01-01

Existing systems for estimating site index of ponderosa pine (Pinus ponderosa Laws.) do not apply well to California stands where stocking is controlled. A more suitable system has been developed using trends in natural height growth, derived from stem analysis of dominant trees in California. This site index system produces polymorphic patterns of...

Automatic plankton image classification combining multiple view features via multiple kernel learning.

PubMed

Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

2017-12-28

Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system outperforms state-of-the-art plankton image classification systems in terms of accuracy and robustness. This study demonstrated automatic plankton image classification system combining multiple view features using multiple kernel learning. The results indicated that multiple view features combined by NLMKL using three kernel functions (linear, polynomial and Gaussian kernel functions) can describe and use information of features better so that achieve a higher classification accuracy.

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

Classifying psychosis--challenges and opportunities.

PubMed

Gaebel, Wolfgang; Zielasek, Jürgen; Cleveland, Helen-Rose

2012-12-01

Within the efforts to revise ICD-10 and DSM-IV-TR, work groups on the classification of psychotic disorders appointed by the World Health Organization (WHO) and the American Psychiatric Association (APA) have proposed several changes to the corresponding classification criteria of schizophrenia and other psychotic disorders in order to increase the clinical utility, reliability and validity of these diagnoses. These proposed revisions are subject to field trials with the objective of studying whether they will lead to an improvement of the classification systems in comparison to their previous versions. Both a challenge and an opportunity, the APA and WHO have also considered harmonizing between the two classifications. The current status of both suggests that this goal can only be met in part. The main proposed revisions include changes to the number and types of symptoms of schizophrenia, the replacement of existing schizophrenia subtypes with dimensional assessments or symptom specifiers, different modifications of the criteria for schizoaffective disorder, a reorganization of the delusional disorders and the acute and transient psychotic disorders in ICD-11, as well as the revision of course and psychomotor symptoms/catatonia specifiers in both classification systems.

A survey to identify the clinical coding and classification systems currently in use across Europe.

PubMed

de Lusignan, S; Minmagh, C; Kennedy, J; Zeimet, M; Bommezijn, H; Bryant, J

2001-01-01

This is a survey to identify what clinical coding systems are currently in use across the European Union, and the states seeking membership to it. We sought to identify what systems are currently used and to what extent they were subject to local adaptation. Clinical coding should facilitate identifying key medical events in a computerised medical record, and aggregating information across groups of records. The emerging new driver is as the enabler of the life-long computerised medical record. A prerequisite for this level of functionality is the transfer of information between different computer systems. This transfer can be facilitated either by working on the interoperability problems between disparate systems or by harmonising the underlying data. This paper examines the extent to which the latter has occurred across Europe. Literature and Internet search. Requests for information via electronic mail to pan-European mailing lists of health informatics professionals. Coding systems are now a de facto part of health information systems across Europe. There are relatively few coding systems in existence across Europe. ICD9 and ICD 10, ICPC and Read were the most established. However the local adaptation of these classification systems either on a by country or by computer software manufacturer basis; significantly reduces the ability for the meaning coded with patients computer records to be easily transferred from one medical record system to another. There is no longer any debate as to whether a coding or classification system should be used. Convergence of different classifications systems should be encouraged. Countries and computer manufacturers within the EU should be encouraged to stop making local modifications to coding and classification systems, as this practice risks significantly slowing progress towards easy transfer of records between computer systems.

Classifying diseases and remedies in ethnomedicine and ethnopharmacology.

PubMed

Staub, Peter O; Geck, Matthias S; Weckerle, Caroline S; Casu, Laura; Leonti, Marco

2015-11-04

Ethnopharmacology focuses on the understanding of local and indigenous use of medicines and therefore an emic approach is inevitable. Often, however, standard biomedical disease classifications are used to describe and analyse local diseases and remedies. Standard classifications might be a valid tool for cross-cultural comparisons and bioprospecting purposes but are not suitable to understand the local perception of disease and use of remedies. Different standard disease classification systems exist but their suitability for cross-cultural comparisons of ethnomedical data has never been assessed. Depending on the research focus, (I) ethnomedical, (II) cross-cultural, and (III) bioprospecting, we provide suggestions for the use of specific classification systems. We analyse three different standard biomedical classification systems (the International Classification of Diseases (ICD); the Economic Botany Data Collection Standard (EBDCS); and the International Classification of Primary Care (ICPC)), and discuss their value for categorizing diseases of ethnomedical systems and their suitability for cross-cultural research in ethnopharmacology. Moreover, based on the biomedical uses of all approved plant derived biomedical drugs, we propose a biomedical therapy-based classification system as a guide for the discovery of drugs from ethnopharmacological sources. Widely used standards, such as the International Classification of Diseases (ICD) by the WHO and the Economic Botany Data Collection Standard (EBDCS) are either technically challenging due to a categorisation system based on clinical examinations, which are usually not possible during field research (ICD) or lack clear biomedical criteria combining disorders and medical effects in an imprecise and confusing way (EBDCS). The International Classification of Primary Care (ICPC), also accepted by the WHO, has more in common with ethnomedical reality than the ICD or the EBDCS, as the categories are designed according to patient's perceptions and are less influenced by clinical medicine. Since diagnostic tools are not required, medical ethnobotanists and ethnopharmacologists can easily classify reported symptoms and complaints with the ICPC in one of the "chapters" based on 17 body systems, psychological and social problems. Also the biomedical uses of plant-derived drugs are classifiable into 17 broad organ- and therapy-based use-categories but can easily be divided into more specific subcategories. Depending on the research focus (I-III) we propose the following classification systems: I. Ethnomedicine: Ethnomedicine is culture-bound and local classifications have to be understood from an emic perspective. Consequently, the application of prefabricated, "one-size fits all" biomedical classification schemes is of limited value. II. Cross-cultural analysis: The ICPC is a suitable standard that can be applied but modified as required. III. Bioprospecting: We suggest a biomedical therapy-driven classification system with currently 17 use-categories based on biomedical uses of all approved plant derived natural product drugs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Systematic Model-in-the-Loop Test of Embedded Control Systems

NASA Astrophysics Data System (ADS)

Krupp, Alexander; Müller, Wolfgang

Current model-based development processes offer new opportunities for verification automation, e.g., in automotive development. The duty of functional verification is the detection of design flaws. Current functional verification approaches exhibit a major gap between requirement definition and formal property definition, especially when analog signals are involved. Besides lack of methodical support for natural language formalization, there does not exist a standardized and accepted means for formal property definition as a target for verification planning. This article addresses several shortcomings of embedded system verification. An Enhanced Classification Tree Method is developed based on the established Classification Tree Method for Embeded Systems CTM/ES which applies a hardware verification language to define a verification environment.

A new classification system for all-ceramic and ceramic-like restorative materials.

PubMed

Gracis, Stefano; Thompson, Van P; Ferencz, Jonathan L; Silva, Nelson R F A; Bonfante, Estevam A

2015-01-01

Classification systems for all-ceramic materials are useful for communication and educational purposes and warrant continuous revisions and updates to incorporate new materials. This article proposes a classification system for ceramic and ceramic-like restorative materials in an attempt to systematize and include a new class of materials. This new classification system categorizes ceramic restorative materials into three families: (1) glass-matrix ceramics, (2) polycrystalline ceramics, and (3) resin-matrix ceramics. Subfamilies are described in each group along with their composition, allowing for newly developed materials to be placed into the already existing main families. The criteria used to differentiate ceramic materials are based on the phase or phases present in their chemical composition. Thus, an all-ceramic material is classified according to whether a glass-matrix phase is present (glass-matrix ceramics) or absent (polycrystalline ceramics) or whether the material contains an organic matrix highly filled with ceramic particles (resin-matrix ceramics). Also presented are the manufacturers' clinical indications for the different materials and an overview of the different fabrication methods and whether they are used as framework materials or monolithic solutions. Current developments in ceramic materials not yet available to the dental market are discussed.

Bridging the Gap in Military Robotics (Combler le Fosse Existant dans le Domaine de la Robotique Militaire)

DTIC Science & Technology

2008-11-01

systems must be evaluated at the platform level as well ( regenerative braking and similar systems). 4.4.4 The Important Gaps Several gaps on robot...in three main categories : • Mobility function: • Obstacle avoidance and negotiation; • Terrain modelling and classification; and • Transport in

White Paper: Movement System Diagnoses in Neurologic Physical Therapy.

PubMed

Hedman, Lois D; Quinn, Lori; Gill-Body, Kathleen; Brown, David A; Quiben, Myla; Riley, Nora; Scheets, Patricia L

2018-04-01

The APTA recently established a vision for physical therapists to transform society by optimizing movement to promote health and wellness, mitigate impairments, and prevent disability. An important element of this vision entails the integration of the movement system into the profession, and necessitates the development of movement system diagnoses by physical therapists. At this point in time, the profession as a whole has not agreed upon diagnostic classifications or guidelines to assist in developing movement system diagnoses that will consistently capture an individual's movement problems. We propose that, going forward, diagnostic classifications of movement system problems need to be developed, tested, and validated. The Academy of Neurologic Physical Therapy's Movement System Task Force was convened to address these issues with respect to management of movement system problems in patients with neurologic conditions. The purpose of this article is to report on the work and recommendations of the Task Force. The Task Force identified 4 essential elements necessary to develop and implement movement system diagnoses for patients with primarily neurologic involvement from existing movement system classifications. The Task Force considered the potential impact of using movement system diagnoses on clinical practice, education and, research. Recommendations were developed and provided recommendations for potential next steps to broaden this discussion and foster the development of movement system diagnostic classifications. The Task Force proposes that diagnostic classifications of movement system problems need to be developed, tested, and validated with the long-range goal to reach consensus on and adoption of a movement system diagnostic framework for clients with neurologic injury or disease states.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A198).

A Unified Classification of Alien Species Based on the Magnitude of their Environmental Impacts

PubMed Central

Blackburn, Tim M.; Essl, Franz; Evans, Thomas; Hulme, Philip E.; Jeschke, Jonathan M.; Kühn, Ingolf; Kumschick, Sabrina; Marková, Zuzana; Mrugała, Agata; Nentwig, Wolfgang; Pergl, Jan; Pyšek, Petr; Rabitsch, Wolfgang; Ricciardi, Anthony; Richardson, David M.; Sendek, Agnieszka; Vilà, Montserrat; Wilson, John R. U.; Winter, Marten; Genovesi, Piero; Bacher, Sven

2014-01-01

Species moved by human activities beyond the limits of their native geographic ranges into areas in which they do not naturally occur (termed aliens) can cause a broad range of significant changes to recipient ecosystems; however, their impacts vary greatly across species and the ecosystems into which they are introduced. There is therefore a critical need for a standardised method to evaluate, compare, and eventually predict the magnitudes of these different impacts. Here, we propose a straightforward system for classifying alien species according to the magnitude of their environmental impacts, based on the mechanisms of impact used to code species in the International Union for Conservation of Nature (IUCN) Global Invasive Species Database, which are presented here for the first time. The classification system uses five semi-quantitative scenarios describing impacts under each mechanism to assign species to different levels of impact—ranging from Minimal to Massive—with assignment corresponding to the highest level of deleterious impact associated with any of the mechanisms. The scheme also includes categories for species that are Not Evaluated, have No Alien Population, or are Data Deficient, and a method for assigning uncertainty to all the classifications. We show how this classification system is applicable at different levels of ecological complexity and different spatial and temporal scales, and embraces existing impact metrics. In fact, the scheme is analogous to the already widely adopted and accepted Red List approach to categorising extinction risk, and so could conceivably be readily integrated with existing practices and policies in many regions. PMID:24802715

Classifying Adverse Events in the Dental Office.

PubMed

Kalenderian, Elsbeth; Obadan-Udoh, Enihomo; Maramaldi, Peter; Etolue, Jini; Yansane, Alfa; Stewart, Denice; White, Joel; Vaderhobli, Ram; Kent, Karla; Hebballi, Nutan B; Delattre, Veronique; Kahn, Maria; Tokede, Oluwabunmi; Ramoni, Rachel B; Walji, Muhammad F

2017-06-30

Dentists strive to provide safe and effective oral healthcare. However, some patients may encounter an adverse event (AE) defined as "unnecessary harm due to dental treatment." In this research, we propose and evaluate two systems for categorizing the type and severity of AEs encountered at the dental office. Several existing medical AE type and severity classification systems were reviewed and adapted for dentistry. Using data collected in previous work, two initial dental AE type and severity classification systems were developed. Eight independent reviewers performed focused chart reviews, and AEs identified were used to evaluate and modify these newly developed classifications. A total of 958 charts were independently reviewed. Among the reviewed charts, 118 prospective AEs were found and 101 (85.6%) were verified as AEs through a consensus process. At the end of the study, a final AE type classification comprising 12 categories, and an AE severity classification comprising 7 categories emerged. Pain and infection were the most common AE types representing 73% of the cases reviewed (56% and 17%, respectively) and 88% were found to cause temporary, moderate to severe harm to the patient. Adverse events found during the chart review process were successfully classified using the novel dental AE type and severity classifications. Understanding the type of AEs and their severity are important steps if we are to learn from and prevent patient harm in the dental office.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, George

1993-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, Stanislav

1992-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

An updated phylogenetic analysis of vertebrate melatonin receptor sequences: reflection on the melatonin receptor nomenclature by the Nomenclature Subcommittee of the International Union of Pharmacology.

PubMed

Shiu, S Y; Pang, S F

1998-01-01

In the past few years, significant progress on melatonin receptor research has led to the discovery of a family of genetically related but pharmacologically distinctive G-protein-coupled receptors in the vertebrates. With increasing number of receptor clones being identified, there is a need for a system of classification and nomenclature for these receptor subtypes. Recently, an updated nomenclature system, which has renamed the existing mammalian melatonin receptor clones, has been proposed by the relevant subcommittee of the International Union of Pharmacology (NC-IUPHAR). However, the majority of receptor clones which have been identified in non-mammalian vertebrates are not clearly defined by this system. By performing phylogenetic analysis of both mammalian and non-mammalian melatonin receptor clones, we would like to propose a classification-nomenclature system for vertebrate melatonin receptors. Hopefully, our system, which incorporates genetic data as well as the pharmacological criteria that have been adopted by the NC-IUPHAR nomenclature system, will provide the framework for future development of a unified scheme of classification and nomenclature for melatonin receptors.

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

Hussain, Hameed; Malik, Saif Ur Rehman; Hameed, Abdul

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement ofmore » all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.« less

The Landscape of long non-coding RNA classification

PubMed Central

St Laurent, Georges; Wahlestedt, Claes; Kapranov, Philipp

2015-01-01

Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. PMID:25869999

Molecular Classification and Correlates in Colorectal Cancer

PubMed Central

Ogino, Shuji; Goel, Ajay

2008-01-01

Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In this review, we discuss molecular classification and molecular correlates based on MSI status and CIMP status in colorectal cancer. Studying molecular correlates is important in cancer research because it can 1) provide clues to pathogenesis, 2) propose or support the existence of a new molecular subtype, 3) alert investigators to be aware of potential confounding factors in association studies, and 4) suggest surrogate markers in clinical or research settings. PMID:18165277

A drone detection with aircraft classification based on a camera array

NASA Astrophysics Data System (ADS)

Liu, Hao; Qu, Fangchao; Liu, Yingjian; Zhao, Wei; Chen, Yitong

2018-03-01

In recent years, because of the rapid popularity of drones, many people have begun to operate drones, bringing a range of security issues to sensitive areas such as airports and military locus. It is one of the important ways to solve these problems by realizing fine-grained classification and providing the fast and accurate detection of different models of drone. The main challenges of fine-grained classification are that: (1) there are various types of drones, and the models are more complex and diverse. (2) the recognition test is fast and accurate, in addition, the existing methods are not efficient. In this paper, we propose a fine-grained drone detection system based on the high resolution camera array. The system can quickly and accurately recognize the detection of fine grained drone based on hd camera.

CNN universal machine as classificaton platform: an art-like clustering algorithm.

PubMed

Bálya, David

2003-12-01

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be very efficient as a feature detector. The next step is to post-process the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can be mapped to the CNN-UM. Moreover, this mapping is general enough to include different types of feed-forward neural networks. The designed analogic CNN algorithm is capable of classifying the extracted feature vectors keeping the advantages of the ART networks, such as robust, plastic and fault-tolerant behaviors. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. The algorithm is extended for supervised classification. The presented binary feature vector classification is implemented on the existing standard CNN-UM chips for fast classification. The experimental evaluation shows promising performance after 100% accuracy on the training set.

Toward an endovascular internal carotid artery classification system.

PubMed

Shapiro, M; Becske, T; Riina, H A; Raz, E; Zumofen, D; Jafar, J J; Huang, P P; Nelson, P K

2014-02-01

Does the world need another ICA classification scheme? We believe so. The purpose of proposed angiography-driven classification is to optimize description of the carotid artery from the endovascular perspective. A review of existing, predominantly surgically-driven classifications is performed, and a new scheme, based on the study of NYU aneurysm angiographic and cross-sectional databases is proposed. Seven segments - cervical, petrous, cavernous, paraophthlamic, posterior communicating, choroidal, and terminus - are named. This nomenclature recognizes intrinsic uncertainty in precise angiographic and cross-sectional localization of aneurysms adjacent to the dural rings, regarding all lesions distal to the cavernous segment as potentially intradural. Rather than subdividing various transitional, ophthalmic, and hypophyseal aneurysm subtypes, as necessitated by their varied surgical approaches and risks, the proposed classification emphasizes their common endovascular treatment features, while recognizing that many complex, trans-segmental, and fusiform aneurysms not readily classifiable into presently available, saccular aneurysm-driven schemes, are being increasingly addressed by endovascular means. We believe this classification may find utility in standardizing nomenclature for outcome tracking, treatment trials and physician communication.

Structural Validation of Nursing Terminologies

PubMed Central

Hardiker, Nicholas R.; Rector, Alan L.

2001-01-01

Objective: The purpose of the study is twofold: 1) to explore the applicability of combinatorial terminologies as the basis for building enumerated classifications, and 2) to investigate the usefulness of formal terminological systems for performing such classification and for assisting in the refinement of both combinatorial terminologies and enumerated classifications. Design: A formal model of the beta version of the International Classification for Nursing Practice (ICNP) was constructed in the compositional terminological language GRAIL (GALEN Representation and Integration Language). Terms drawn from the North American Nursing Diagnosis Association Taxonomy I (NANDA taxonomy) were mapped into the model and classified automatically using GALEN technology. Measurements: The resulting generated hierarchy was compared with the NANDA taxonomy to assess coverage and accuracy of classification. Results: In terms of coverage, in this study ICNP was able to capture 77 percent of NANDA terms using concepts drawn from five of its eight axes. Three axes—Body Site, Topology, and Frequency—were not needed. In terms of accuracy, where hierarchic relationships existed in the generated hierarchy or the NANDA taxonomy, or both, 6 were identical, 19 existed in the generated hierarchy alone (2 of these were considered suitable for incorporation into the NANDA taxonomy and 17 were considered inaccurate), and 23 appeared in the NANDA taxonomy alone (8 of these were considered suitable for incorporation into ICNP, 9 were considered inaccurate, and 6 reflected different, equally valid perspectives). Sixty terms appeared at the top level, with no indenting, in both the generated hierarchy and the NANDA taxonomy. Conclusions: With appropriate refinement, combinatorial terminologies such as ICNP have the potential to provide a useful foundation for representing enumerated classifications such as NANDA. Technologies such as GALEN make possible the process of building automatically enumerated classifications while providing a useful means of validating and refining both combinatorial terminologies and enumerated classifications. PMID:11320066

[Questions of terminology, systematization and grading of complications of contact ureteral lithotripsy].

PubMed

Dutov, V V; Bazaev, V V; Mamedov, E A; Urenkov, S B; Podoinitsyn, A A

2017-07-01

To investigate the advantages and disadvantages of the current variants of systematization and grading of complications of contact ureteral lithotripsy (CULT) and develop a working classification of CULT complications. The study analyzed results of 545 fluoroscopy-guided endoscopic procedures performed at the MRRCI Clinic of Urology from 2008 to 2015 in 506 patients with ureterolithiasis. The proposed and implemented classification and terminology of CULT complications unifies the diagnostic and management algorithm. This tool is more systematic and structured than the classical classification and universal methods of systematization and grading of CULT complications (classifying CULT complications in "major" and "minor", PULS scale, Satava and Clavien-Dindo grading systems). Given the lack of clear grading of ureteral rupture, it was divided into amputation (two-level rupture) and avulsion (one-level rupture). Using such term as extravasation of the contrast media and/or migration of the stone outside of the ureter is groundless because these complications occur only after the perforation of the ureteral wall. Therefore, these conditions are complications not of CULT, but of the ureteral wall perforation. The ureteral perforation was classified into macro- and micro-perforation. The existing terminology, classification and grading of the CULT complications should undergo a more detailed analysis. None of the existing classifications of CULT complications afford them to be fully staged and systematized. The working classification of complications of CULT developed at the M.F. Vladimirsky MRRCI Clinic of Urology warrants a multi-center prospective study to validate it and investigate its effectiveness.

ABCD classification system: a novel classification for subaxial cervical spine injuries.

PubMed

Shousha, Mootaz

2014-04-20

The classification system was derived through a retrospective analysis of 73 consecutive cases of subaxial cervical spine injury as well as thorough literature review. To define a new classification system for subaxial cervical spine injuries. There exist several methods to classify subaxial cervical spine injuries but no single system has emerged as clearly superior to the others. On the basis of a 2-column anatomical model, the first part of the proposed classification is an anatomical description of the injury. It delivers the information whether the injury is bony, ligamentous, or a combined one. The first 4 alphabetical letters have been used for simplicity. Each column is represented by an alphabetical letter from A to D. Each letter has a radiological meaning (A = Absent injury, B = Bony lesion, C = Combined bony and ligamentous, D = Disc or ligamentous injury).The second part of the classification is represented by 3 modifiers. These are the neurological status of the patient (N), the degree of spinal canal stenosis (S), and the degree of instability (I). For simplicity, each modifier was graded in an ascending pattern of severity from zero to 2. The last part is optional and denotes which radiological examination has been used to define the injury type. The new ABCD classification was applicable for all patients. The most common type was anterior ligamentous and posterior combined injury "DC" (37.9%), followed by "DD" injury in 12% of the cases. Through this work a new classification for cervical spine injuries is proposed. The aim is to establish criteria for a common language in description of cervical injuries aiming for simplification, especially for junior residents. Each letter and each sign has a meaning to deliver the largest amount of information. Both the radiological as well as the clinical data are represented in this scheme. However, further evaluation of this classification is needed. 3.

"Your Model Is Predictive-- but Is It Useful?" Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation

ERIC Educational Resources Information Center

González-Brenes, José P.; Huang, Yun

2015-01-01

Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…

Lissencephaly: expanded imaging and clinical classification

PubMed Central

Di Donato, Nataliya; Chiari, Sara; Mirzaa, Ghayda M.; Aldinger, Kimberly; Parrini, Elena; Olds, Carissa; Barkovich, A. James; Guerrini, Renzo; Dobyns, William B.

2017-01-01

Lissencephaly (“smooth brain”, LIS) is a malformation of cortical development associated with deficient neuronal migration and abnormal formation of cerebral convolutions or gyri. The LIS spectrum includes agyria, pachygyria, and subcortical band heterotopia. Our first classification of LIS and subcortical band heterotopia (SBH) was developed to distinguish between the first two genetic causes of LIS – LIS1 (PAFAH1B1) and DCX. However, progress in molecular genetics has led to identification of 19 LIS-associated genes, leaving the existing classification system insufficient to distinguish the increasingly diverse patterns of LIS. To address this challenge, we reviewed clinical, imaging and molecular data on 188 patients with LIS-SBH ascertained during the last five years, and reviewed selected archival data on another ~1,400 patients. Using these data plus published reports, we constructed a new imaging based classification system with 21 recognizable patterns that reliably predict the most likely causative genes. These patterns do not correlate consistently with the clinical outcome, leading us to also develop a new scale useful for predicting clinical severity and outcome. Taken together, our work provides new tools that should prove useful for clinical management and genetic counselling of patients with LIS-SBH (imaging and severity based classifications), and guidance for prioritizing and interpreting genetic testing results (imaging based classification). PMID:28440899

Texture characterization for joint compression and classification based on human perception in the wavelet domain.

PubMed

Fahmy, Gamal; Black, John; Panchanathan, Sethuraman

2006-06-01

Today's multimedia applications demand sophisticated compression and classification techniques in order to store, transmit, and retrieve audio-visual information efficiently. Over the last decade, perceptually based image compression methods have been gaining importance. These methods take into account the abilities (and the limitations) of human visual perception (HVP) when performing compression. The upcoming MPEG 7 standard also addresses the need for succinct classification and indexing of visual content for efficient retrieval. However, there has been no research that has attempted to exploit the characteristics of the human visual system to perform both compression and classification jointly. One area of HVP that has unexplored potential for joint compression and classification is spatial frequency perception. Spatial frequency content that is perceived by humans can be characterized in terms of three parameters, which are: 1) magnitude; 2) phase; and 3) orientation. While the magnitude of spatial frequency content has been exploited in several existing image compression techniques, the novel contribution of this paper is its focus on the use of phase coherence for joint compression and classification in the wavelet domain. Specifically, this paper describes a human visual system-based method for measuring the degree to which an image contains coherent (perceptible) phase information, and then exploits that information to provide joint compression and classification. Simulation results that demonstrate the efficiency of this method are presented.

22 CFR 9.6 - Derivative classification.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating or... with the classification of the source material. Duplication or reproduction of existing classified...

22 CFR 9.6 - Derivative classification.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating or... with the classification of the source material. Duplication or reproduction of existing classified...

22 CFR 9.6 - Derivative classification.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating or... with the classification of the source material. Duplication or reproduction of existing classified...

22 CFR 9.6 - Derivative classification.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Derivative classification. 9.6 Section 9.6... classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating or... with the classification of the source material. Duplication or reproduction of existing classified...

On the SAR derived alert in the detection of oil spills according to the analysis of the EGEMP.

PubMed

Ferraro, Guido; Baschek, Björn; de Montpellier, Geraldine; Njoten, Ove; Perkovic, Marko; Vespe, Michele

2010-01-01

Satellite services that deliver information about possible oil spills at sea currently use different labels of "confidence" to describe the detections based on radar image processing. A common approach is to use a classification differentiating between low, medium and high levels of confidence. There is an ongoing discussion on the suitability of the existing classification systems of possible oil spills detected by radar satellite images with regard to the relevant significance and correspondence to user requirements. This paper contains a basic analysis of user requirements, current technical possibilities of satellite services as well as proposals for a redesign of the classification system as an evolution towards a more structured alert system. This research work offers a first review of implemented methodologies for the categorisation of detected oil spills, together with the proposal of explorative ideas evaluated by the European Group of Experts on satellite Monitoring of sea-based oil Pollution (EGEMP). Copyright 2009 Elsevier Ltd. All rights reserved.

Classification of patients with low back-related leg pain: a systematic review.

PubMed

Stynes, Siobhán; Konstantinou, Kika; Dunn, Kate M

2016-05-23

The identification of clinically relevant subgroups of low back pain (LBP) is considered the number one LBP research priority in primary care. One subgroup of LBP patients are those with back related leg pain. Leg pain frequently accompanies LBP and is associated with increased levels of disability and higher health costs than simple low back pain. Distinguishing between different types of low back-related leg pain (LBLP) is important for clinical management and research applications, but there is currently no clear agreement on how to define and identify LBLP due to nerve root involvement. The aim of this systematic review was to identify, describe and appraise papers that classify or subgroup populations with LBLP, and summarise how leg pain due to nerve root involvement is described and diagnosed in the various systems. The search strategy involved nine electronic databases including Medline and Embase, reference lists of eligible studies and relevant reviews. Selected papers were appraised independently by two reviewers using a standardised scoring tool. Of 13,358 initial potential eligible citations, 50 relevant papers were identified that reported on 22 classification systems. Papers were grouped according to purpose and criteria of the classification systems. Five themes emerged: (i) clinical features (ii) pathoanatomy (iii) treatment-based approach (iv) screening tools and prediction rules and (v) pain mechanisms. Three of the twenty two systems focused specifically on LBLP populations. Systems that scored highest following quality appraisal were ones where authors generally included statistical methods to develop their classifications, and supporting work had been published on the systems' validity, reliability and generalisability. There was lack of consistency in how LBLP due to nerve root involvement was described and diagnosed within the systems. Numerous classification systems exist that include patients with leg pain, a minority of them focus specifically on distinguishing between different presentations of leg pain. Further work is needed to identify clinically meaningful subgroups of LBLP patients, ideally based on large primary care cohort populations and using recommended methods for classification system development.

Impact of Information based Classification on Network Epidemics

PubMed Central

Mishra, Bimal Kumar; Haldar, Kaushik; Sinha, Durgesh Nandini

2016-01-01

Formulating mathematical models for accurate approximation of malicious propagation in a network is a difficult process because of our inherent lack of understanding of several underlying physical processes that intrinsically characterize the broader picture. The aim of this paper is to understand the impact of available information in the control of malicious network epidemics. A 1-n-n-1 type differential epidemic model is proposed, where the differentiality allows a symptom based classification. This is the first such attempt to add such a classification into the existing epidemic framework. The model is incorporated into a five class system called the DifEpGoss architecture. Analysis reveals an epidemic threshold, based on which the long-term behavior of the system is analyzed. In this work three real network datasets with 22002, 22469 and 22607 undirected edges respectively, are used. The datasets show that classification based prevention given in the model can have a good role in containing network epidemics. Further simulation based experiments are used with a three category classification of attack and defense strengths, which allows us to consider 27 different possibilities. These experiments further corroborate the utility of the proposed model. The paper concludes with several interesting results. PMID:27329348

TFOS DEWS II Definition and Classification Report.

PubMed

Craig, Jennifer P; Nichols, Kelly K; Akpek, Esen K; Caffery, Barbara; Dua, Harminder S; Joo, Choun-Ki; Liu, Zuguo; Nelson, J Daniel; Nichols, Jason J; Tsubota, Kazuo; Stapleton, Fiona

2017-07-01

The goals of the TFOS DEWS II Definition and Classification Subcommittee were to create an evidence-based definition and a contemporary classification system for dry eye disease (DED). The new definition recognizes the multifactorial nature of dry eye as a disease where loss of homeostasis of the tear film is the central pathophysiological concept. Ocular symptoms, as a broader term that encompasses reports of discomfort or visual disturbance, feature in the definition and the key etiologies of tear film instability, hyperosmolarity, and ocular surface inflammation and damage were determined to be important for inclusion in the definition. In the light of new data, neurosensory abnormalities were also included in the definition for the first time. In the classification of DED, recent evidence supports a scheme based on the pathophysiology where aqueous deficient and evaporative dry eye exist as a continuum, such that elements of each are considered in diagnosis and management. Central to the scheme is a positive diagnosis of DED with signs and symptoms, and this is directed towards management to restore homeostasis. The scheme also allows consideration of various related manifestations, such as non-obvious disease involving ocular surface signs without related symptoms, including neurotrophic conditions where dysfunctional sensation exists, and cases where symptoms exist without demonstrable ocular surface signs, including neuropathic pain. This approach is not intended to override clinical assessment and judgment but should prove helpful in guiding clinical management and research. Copyright © 2017 Elsevier Inc. All rights reserved.

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Classification of topological phonons in linear mechanical metamaterials

PubMed Central

Süsstrunk, Roman

2016-01-01

Topological phononic crystals, alike their electronic counterparts, are characterized by a bulk–edge correspondence where the interior of a material dictates the existence of stable surface or boundary modes. In the mechanical setup, such surface modes can be used for various applications such as wave guiding, vibration isolation, or the design of static properties such as stable floppy modes where parts of a system move freely. Here, we provide a classification scheme of topological phonons based on local symmetries. We import and adapt the classification of noninteracting electron systems and embed it into the mechanical setup. Moreover, we provide an extensive set of examples that illustrate our scheme and can be used to generate models in unexplored symmetry classes. Our work unifies the vast recent literature on topological phonons and paves the way to future applications of topological surface modes in mechanical metamaterials. PMID:27482105

Yet Another Stream Search Among 2401 Photographic Meteors

NASA Technical Reports Server (NTRS)

Cook, A. F., II; Lindblad, B.; Marsden, B. G.; Mccrosky, R. E.; Posen, A.

1973-01-01

Two streams previously listed (one of them with a classification on Ceplecha's system in terms of beginning height) by Cook are shown probably not to exist, a possibility already pointed out by Cook. One stream that he questioned was revised as to membership and then classified. Four streams are added to the list and one of these is classified. Previous reports exist for three of these streams, while one is new. The two Piscid streams of Lindblad and his alpha Triangulid stream are regrouped into two streams, one already called the Andromedids by Cook and the other still called the Piscids; the alpha Triangulids are absorbed into the Andromedids. The Piscids are classified along with the iota Aquarids. The classifications of the Taurids and the Andromedids remain unchanged.

A Higher Level Classification of All Living Organisms

PubMed Central

Ruggiero, Michael A.; Gordon, Dennis P.; Orrell, Thomas M.; Bailly, Nicolas; Bourgoin, Thierry; Brusca, Richard C.; Cavalier-Smith, Thomas; Guiry, Michael D.; Kirk, Paul M.

2015-01-01

We present a consensus classification of life to embrace the more than 1.6 million species already provided by more than 3,000 taxonomists’ expert opinions in a unified and coherent, hierarchically ranked system known as the Catalogue of Life (CoL). The intent of this collaborative effort is to provide a hierarchical classification serving not only the needs of the CoL’s database providers but also the diverse public-domain user community, most of whom are familiar with the Linnaean conceptual system of ordering taxon relationships. This classification is neither phylogenetic nor evolutionary but instead represents a consensus view that accommodates taxonomic choices and practical compromises among diverse expert opinions, public usages, and conflicting evidence about the boundaries between taxa and the ranks of major taxa, including kingdoms. Certain key issues, some not fully resolved, are addressed in particular. Beyond its immediate use as a management tool for the CoL and ITIS (Integrated Taxonomic Information System), it is immediately valuable as a reference for taxonomic and biodiversity research, as a tool for societal communication, and as a classificatory “backbone” for biodiversity databases, museum collections, libraries, and textbooks. Such a modern comprehensive hierarchy has not previously existed at this level of specificity. PMID:25923521

A systematic review of definitions and classification systems of adjacent segment pathology.

PubMed

Kraemer, Paul; Fehlings, Michael G; Hashimoto, Robin; Lee, Michael J; Anderson, Paul A; Chapman, Jens R; Raich, Annie; Norvell, Daniel C

2012-10-15

Systematic review. To undertake a systematic review to determine how "adjacent segment degeneration," "adjacent segment disease," or clinical pathological processes that serve as surrogates for adjacent segment pathology are classified and defined in the peer-reviewed literature. Adjacent segment degeneration and adjacent segment disease are terms referring to degenerative changes known to occur after reconstructive spine surgery, most commonly at an immediately adjacent functional spinal unit. These can include disc degeneration, instability, spinal stenosis, facet degeneration, and deformity. The true incidence and clinical impact of degenerative changes at the adjacent segment is unclear because there is lack of a universally accepted classification system that rigorously addresses clinical and radiological issues. A systematic review of the English language literature was undertaken and articles were classified using the Grades of Recommendation Assessment, Development, and Evaluation criteria. RESULTS.: Seven classification systems of spinal degeneration, including degeneration at the adjacent segment, were identified. None have been evaluated for reliability or validity specific to patients with degeneration at the adjacent segment. The ways in which terms related to adjacent segment "degeneration" or "disease" are defined in the peer-reviewed literature are highly variable. On the basis of the systematic review presented in this article, no formal classification system for either cervical or thoracolumbar adjacent segment disorders currently exists. No recommendations regarding the use of current classification of degeneration at any segments can be made based on the available literature. A new comprehensive definition for adjacent segment pathology (ASP, the now preferred terminology) has been proposed in this Focus Issue, which reflects the diverse pathology observed at functional spinal units adjacent to previous spinal reconstruction and balances detailed stratification with clinical utility. A comprehensive classification system is being developed through expert opinion and will require validation as well as peer review. Strength of Statement: Strong.

Coupling Self-Organizing Maps with a Naïve Bayesian classifier: A case study for classifying Vermont streams using geomorphic, habitat and biological assessment data

NASA Astrophysics Data System (ADS)

Fytilis, N.; Rizzo, D. M.

2012-12-01

Environmental managers are increasingly required to forecast the long-term effects and the resilience or vulnerability of biophysical systems to human-generated stresses. Mitigation strategies for hydrological and environmental systems need to be assessed in the presence of uncertainty. An important aspect of such complex systems is the assessment of variable uncertainty on the model response outputs. We develop a new classification tool that couples a Naïve Bayesian Classifier with a modified Kohonen Self-Organizing Map to tackle this challenge. For proof-of-concept, we use rapid geomorphic and reach-scale habitat assessments data from over 2500 Vermont stream reaches (~1371 stream miles) assessed by the Vermont Agency of Natural Resources (VTANR). In addition, the Vermont Department of Environmental Conservation (VTDEC) estimates stream habitat biodiversity indices (macro-invertebrates and fish) and a variety of water quality data. Our approach fully utilizes the existing VTANR and VTDEC data sets to improve classification of stream-reach habitat and biological integrity. The combined SOM-Naïve Bayesian architecture is sufficiently flexible to allow for continual updates and increased accuracy associated with acquiring new data. The Kohonen Self-Organizing Map (SOM) is an unsupervised artificial neural network that autonomously analyzes properties inherent in a given a set of data. It is typically used to cluster data vectors into similar categories when a priori classes do not exist. The ability of the SOM to convert nonlinear, high dimensional data to some user-defined lower dimension and mine large amounts of data types (i.e., discrete or continuous, biological or geomorphic data) makes it ideal for characterizing the sensitivity of river networks in a variety of contexts. The procedure is data-driven, and therefore does not require the development of site-specific, process-based classification stream models, or sets of if-then-else rules associated with expert systems. This has the potential to save time and resources, while enabling a truly adaptive management approach using existing knowledge (expressed as prior probabilities) and new information (expressed as likelihood functions) to update estimates (i.e., in this case, improved stream classifications expressed as posterior probabilities). The distribution parameters of these posterior probabilities are used to quantify uncertainty associated with environmental data. Since classification plays a leading role in the future development of data-enabled science and engineering, such a computational tool is applicable to a variety of engineering applications. The ability of the new classification neural network to characterize streams with high environmental risk is essential for a proactive adaptive watershed management approach.

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, G.A.; Echols, D.; Sapkota, S.K.

2002-01-01

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LM-NRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments.

PubMed

Ramsey, Elijah W; Nelson, Gene A; Echols, Darrell; Sapkota, Sijan K

2002-05-01

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LMNRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

Ensemble of classifiers for confidence-rated classification of NDE signal

NASA Astrophysics Data System (ADS)

Banerjee, Portia; Safdarnejad, Seyed; Udpa, Lalita; Udpa, Satish

2016-02-01

Ensemble of classifiers in general, aims to improve classification accuracy by combining results from multiple weak hypotheses into a single strong classifier through weighted majority voting. Improved versions of ensemble of classifiers generate self-rated confidence scores which estimate the reliability of each of its prediction and boost the classifier using these confidence-rated predictions. However, such a confidence metric is based only on the rate of correct classification. In existing works, although ensemble of classifiers has been widely used in computational intelligence, the effect of all factors of unreliability on the confidence of classification is highly overlooked. With relevance to NDE, classification results are affected by inherent ambiguity of classifica-tion, non-discriminative features, inadequate training samples and noise due to measurement. In this paper, we extend the existing ensemble classification by maximizing confidence of every classification decision in addition to minimizing the classification error. Initial results of the approach on data from eddy current inspection show improvement in classification performance of defect and non-defect indications.

Use of information-retrieval languages in automated retrieval of experimental data from long-term storage

NASA Technical Reports Server (NTRS)

Khovanskiy, Y. D.; Kremneva, N. I.

1975-01-01

Problems and methods are discussed of automating information retrieval operations in a data bank used for long term storage and retrieval of data from scientific experiments. Existing information retrieval languages are analyzed along with those being developed. The results of studies discussing the application of the descriptive 'Kristall' language used in the 'ASIOR' automated information retrieval system are presented. The development and use of a specialized language of the classification-descriptive type, using universal decimal classification indices as the main descriptors, is described.

Classification of wetlands vegetation using small scale color infrared imagery

NASA Technical Reports Server (NTRS)

Williamson, F. S. L.

1975-01-01

A classification system for Chesapeake Bay wetlands was derived from the correlation of film density classes and actual vegetation classes. The data processing programs used were developed by the Laboratory for the Applications of Remote Sensing. These programs were tested for their value in classifying natural vegetation, using digitized data from small scale aerial photography. Existing imagery and the vegetation map of Farm Creek Marsh were used to determine the optimal number of classes, and to aid in determining if the computer maps were a believable product.

A survey of transposable element classification systems--a call for a fundamental update to meet the challenge of their diversity and complexity.

PubMed

Piégu, Benoît; Bire, Solenne; Arensburger, Peter; Bigot, Yves

2015-05-01

The increase of publicly available sequencing data has allowed for rapid progress in our understanding of genome composition. As new information becomes available we should constantly be updating and reanalyzing existing and newly acquired data. In this report we focus on transposable elements (TEs) which make up a significant portion of nearly all sequenced genomes. Our ability to accurately identify and classify these sequences is critical to understanding their impact on host genomes. At the same time, as we demonstrate in this report, problems with existing classification schemes have led to significant misunderstandings of the evolution of both TE sequences and their host genomes. In a pioneering publication Finnegan (1989) proposed classifying all TE sequences into two classes based on transposition mechanisms and structural features: the retrotransposons (class I) and the DNA transposons (class II). We have retraced how ideas regarding TE classification and annotation in both prokaryotic and eukaryotic scientific communities have changed over time. This has led us to observe that: (1) a number of TEs have convergent structural features and/or transposition mechanisms that have led to misleading conclusions regarding their classification, (2) the evolution of TEs is similar to that of viruses by having several unrelated origins, (3) there might be at least 8 classes and 12 orders of TEs including 10 novel orders. In an effort to address these classification issues we propose: (1) the outline of a universal TE classification, (2) a set of methods and classification rules that could be used by all scientific communities involved in the study of TEs, and (3) a 5-year schedule for the establishment of an International Committee for Taxonomy of Transposable Elements (ICTTE). Copyright © 2015 Elsevier Inc. All rights reserved.

A classification system for predicting pallet part quality from hardwood cants

Treesearch

E. Paul Craft; Kenneth R., Jr. Whitenack

1982-01-01

Producers who manufacture pallet parts from hardwood cants generally must purchase cants on the basis of existing structural timber grades that do not adequately reflect the quality of pallet parts produced from resawed cants. A system for classifying cants for pallet part production has been developed that more accurately reflects the parts grade mix that can be...

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

[Research progress in molecular classification of gastric cancer].

PubMed

Zhou, Menglong; Li, Guichao; Zhang, Zhen

2016-09-25

Gastric cancer(GC) is a highly heterogeneous malignancy. The present widely used histopathological classifications have gradually failed to meet the needs of individualized diagnosis and treatment. Development of technologies such as microarray and next-generation sequencing (NGS) has allowed GC to be studied at the molecular level. Mechanisms about tumorigenesis and progression of GC can be elucidated in the aspects of gene mutations, chromosomal alterations, transcriptional and epigenetic changes, on the basis of which GC can be divided into several subtypes. The classifications of Tan's, Lei's, TCGA and ACRG are relatively comprehensive. Especially the TCGA and ACRG classifications have large sample size and abundant molecular profiling data, thus, the genomic characteristics of GC can be depicted more accurately. However, significant differences between both classifications still exist so that they cannot be substituted for each other. So far there is no widely accepted molecular classification of GC. Compared with TCGA classification, ACRG system may have more clinical significance in Chinese GC patients since the samples are mostly from Asian population and show better association with prognosis. The molecular classification of GC may provide the theoretical and experimental basis for early diagnosis, therapeutic efficacy prediction and treatment stratification while their clinical application is still limited. Future work should involve the application of molecular classifications in the clinical settings for improving the medical management of GC.

Reliability of intracerebral hemorrhage classification systems: A systematic review.

PubMed

Rannikmäe, Kristiina; Woodfield, Rebecca; Anderson, Craig S; Charidimou, Andreas; Chiewvit, Pipat; Greenberg, Steven M; Jeng, Jiann-Shing; Meretoja, Atte; Palm, Frederic; Putaala, Jukka; Rinkel, Gabriel Je; Rosand, Jonathan; Rost, Natalia S; Strbian, Daniel; Tatlisumak, Turgut; Tsai, Chung-Fen; Wermer, Marieke Jh; Werring, David; Yeh, Shin-Joe; Al-Shahi Salman, Rustam; Sudlow, Cathie Lm

2016-08-01

Accurately distinguishing non-traumatic intracerebral hemorrhage (ICH) subtypes is important since they may have different risk factors, causal pathways, management, and prognosis. We systematically assessed the inter- and intra-rater reliability of ICH classification systems. We sought all available reliability assessments of anatomical and mechanistic ICH classification systems from electronic databases and personal contacts until October 2014. We assessed included studies' characteristics, reporting quality and potential for bias; summarized reliability with kappa value forest plots; and performed meta-analyses of the proportion of cases classified into each subtype. We included 8 of 2152 studies identified. Inter- and intra-rater reliabilities were substantial to perfect for anatomical and mechanistic systems (inter-rater kappa values: anatomical 0.78-0.97 [six studies, 518 cases], mechanistic 0.89-0.93 [three studies, 510 cases]; intra-rater kappas: anatomical 0.80-1 [three studies, 137 cases], mechanistic 0.92-0.93 [two studies, 368 cases]). Reporting quality varied but no study fulfilled all criteria and none was free from potential bias. All reliability studies were performed with experienced raters in specialist centers. Proportions of ICH subtypes were largely consistent with previous reports suggesting that included studies are appropriately representative. Reliability of existing classification systems appears excellent but is unknown outside specialist centers with experienced raters. Future reliability comparisons should be facilitated by studies following recently published reporting guidelines. © 2016 World Stroke Organization.

Development of a Classification Scheme for Examining Adverse Events Associated with Medical Devices, Specifically the DaVinci Surgical System as Reported in the FDA MAUDE Database.

PubMed

Gupta, Priyanka; Schomburg, John; Krishna, Suprita; Adejoro, Oluwakayode; Wang, Qi; Marsh, Benjamin; Nguyen, Andrew; Genere, Juan Reyes; Self, Patrick; Lund, Erik; Konety, Badrinath R

2017-01-01

To examine the Manufacturer and User Facility Device Experience Database (MAUDE) database to capture adverse events experienced with the Da Vinci Surgical System. In addition, to design a standardized classification system to categorize the complications and machine failures associated with the device. Overall, 1,057,000 DaVinci procedures were performed in the United States between 2009 and 2012. Currently, no system exists for classifying and comparing device-related errors and complications with which to evaluate adverse events associated with the Da Vinci Surgical System. The MAUDE database was queried for events reports related to the DaVinci Surgical System between the years 2009 and 2012. A classification system was developed and tested among 14 robotic surgeons to associate a level of severity with each event and its relationship to the DaVinci Surgical System. Events were then classified according to this system and examined by using Chi-square analysis. Two thousand eight hundred thirty-seven events were identified, of which 34% were obstetrics and gynecology (Ob/Gyn); 19%, urology; 11%, other; and 36%, not specified. Our classification system had moderate agreement with a Kappa score of 0.52. Using our classification system, we identified 75% of the events as mild, 18% as moderate, 4% as severe, and 3% as life threatening or resulting in death. Seventy-seven percent were classified as definitely related to the device, 15% as possibly related, and 8% as not related. Urology procedures compared with Ob/Gyn were associated with more severe events (38% vs 26%, p < 0.0001). Energy instruments were associated with less severe events compared with the surgical system (8% vs 87%, p < 0.0001). Events that were definitely associated with the device tended to be less severe (81% vs 19%, p < 0.0001). Our classification system is a valid tool with moderate inter-rater agreement that can be used to better understand device-related adverse events. The majority of robotic related events were mild but associated with the device.

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns

PubMed Central

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning. PMID:29209191

Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

PubMed

Matsubara, Takashi

2017-01-01

Precise spike timing is considered to play a fundamental role in communications and signal processing in biological neural networks. Understanding the mechanism of spike timing adjustment would deepen our understanding of biological systems and enable advanced engineering applications such as efficient computational architectures. However, the biological mechanisms that adjust and maintain spike timing remain unclear. Existing algorithms adopt a supervised approach, which adjusts the axonal conduction delay and synaptic efficacy until the spike timings approximate the desired timings. This study proposes a spike timing-dependent learning model that adjusts the axonal conduction delay and synaptic efficacy in both unsupervised and supervised manners. The proposed learning algorithm approximates the Expectation-Maximization algorithm, and classifies the input data encoded into spatio-temporal spike patterns. Even in the supervised classification, the algorithm requires no external spikes indicating the desired spike timings unlike existing algorithms. Furthermore, because the algorithm is consistent with biological models and hypotheses found in existing biological studies, it could capture the mechanism underlying biological delay learning.

Classifying Black Hole States with Machine Learning

NASA Astrophysics Data System (ADS)

Huppenkothen, Daniela

2018-01-01

Galactic black hole binaries are known to go through different states with apparent signatures in both X-ray light curves and spectra, leading to important implications for accretion physics as well as our knowledge of General Relativity. Existing frameworks of classification are usually based on human interpretation of low-dimensional representations of the data, and generally only apply to fairly small data sets. Machine learning, in contrast, allows for rapid classification of large, high-dimensional data sets. In this talk, I will report on advances made in classification of states observed in Black Hole X-ray Binaries, focusing on the two sources GRS 1915+105 and Cygnus X-1, and show both the successes and limitations of using machine learning to derive physical constraints on these systems.

Significance of perceptually relevant image decolorization for scene classification

NASA Astrophysics Data System (ADS)

Viswanathan, Sowmya; Divakaran, Govind; Soman, Kutti Padanyl

2017-11-01

Color images contain luminance and chrominance components representing the intensity and color information, respectively. The objective of this paper is to show the significance of incorporating chrominance information to the task of scene classification. An improved color-to-grayscale image conversion algorithm that effectively incorporates chrominance information is proposed using the color-to-gray structure similarity index and singular value decomposition to improve the perceptual quality of the converted grayscale images. The experimental results based on an image quality assessment for image decolorization and its success rate (using the Cadik and COLOR250 datasets) show that the proposed image decolorization technique performs better than eight existing benchmark algorithms for image decolorization. In the second part of the paper, the effectiveness of incorporating the chrominance component for scene classification tasks is demonstrated using a deep belief network-based image classification system developed using dense scale-invariant feature transforms. The amount of chrominance information incorporated into the proposed image decolorization technique is confirmed with the improvement to the overall scene classification accuracy. Moreover, the overall scene classification performance improved by combining the models obtained using the proposed method and conventional decolorization methods.

HEp-2 cell image classification method based on very deep convolutional networks with small datasets

NASA Astrophysics Data System (ADS)

Lu, Mengchi; Gao, Long; Guo, Xifeng; Liu, Qiang; Yin, Jianping

2017-07-01

Human Epithelial-2 (HEp-2) cell images staining patterns classification have been widely used to identify autoimmune diseases by the anti-Nuclear antibodies (ANA) test in the Indirect Immunofluorescence (IIF) protocol. Because manual test is time consuming, subjective and labor intensive, image-based Computer Aided Diagnosis (CAD) systems for HEp-2 cell classification are developing. However, methods proposed recently are mostly manual features extraction with low accuracy. Besides, the scale of available benchmark datasets is small, which does not exactly suitable for using deep learning methods. This issue will influence the accuracy of cell classification directly even after data augmentation. To address these issues, this paper presents a high accuracy automatic HEp-2 cell classification method with small datasets, by utilizing very deep convolutional networks (VGGNet). Specifically, the proposed method consists of three main phases, namely image preprocessing, feature extraction and classification. Moreover, an improved VGGNet is presented to address the challenges of small-scale datasets. Experimental results over two benchmark datasets demonstrate that the proposed method achieves superior performance in terms of accuracy compared with existing methods.

Manifold Regularized Experimental Design for Active Learning.

PubMed

Zhang, Lining; Shum, Hubert P H; Shao, Ling

2016-12-02

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.

Assignment of protein sequences to existing domain and family classification systems: Pfam and the PDB.

PubMed

Xu, Qifang; Dunbrack, Roland L

2012-11-01

Automating the assignment of existing domain and protein family classifications to new sets of sequences is an important task. Current methods often miss assignments because remote relationships fail to achieve statistical significance. Some assignments are not as long as the actual domain definitions because local alignment methods often cut alignments short. Long insertions in query sequences often erroneously result in two copies of the domain assigned to the query. Divergent repeat sequences in proteins are often missed. We have developed a multilevel procedure to produce nearly complete assignments of protein families of an existing classification system to a large set of sequences. We apply this to the task of assigning Pfam domains to sequences and structures in the Protein Data Bank (PDB). We found that HHsearch alignments frequently scored more remotely related Pfams in Pfam clans higher than closely related Pfams, thus, leading to erroneous assignment at the Pfam family level. A greedy algorithm allowing for partial overlaps was, thus, applied first to sequence/HMM alignments, then HMM-HMM alignments and then structure alignments, taking care to join partial alignments split by large insertions into single-domain assignments. Additional assignment of repeat Pfams with weaker E-values was allowed after stronger assignments of the repeat HMM. Our database of assignments, presented in a database called PDBfam, contains Pfams for 99.4% of chains >50 residues. The Pfam assignment data in PDBfam are available at http://dunbrack2.fccc.edu/ProtCid/PDBfam, which can be searched by PDB codes and Pfam identifiers. They will be updated regularly.

A new pre-classification method based on associative matching method

NASA Astrophysics Data System (ADS)

Katsuyama, Yutaka; Minagawa, Akihiro; Hotta, Yoshinobu; Omachi, Shinichiro; Kato, Nei

2010-01-01

Reducing the time complexity of character matching is critical to the development of efficient Japanese Optical Character Recognition (OCR) systems. To shorten processing time, recognition is usually split into separate preclassification and recognition stages. For high overall recognition performance, the pre-classification stage must both have very high classification accuracy and return only a small number of putative character categories for further processing. Furthermore, for any practical system, the speed of the pre-classification stage is also critical. The associative matching (AM) method has often been used for fast pre-classification, because its use of a hash table and reliance solely on logical bit operations to select categories makes it highly efficient. However, redundant certain level of redundancy exists in the hash table because it is constructed using only the minimum and maximum values of the data on each axis and therefore does not take account of the distribution of the data. We propose a modified associative matching method that satisfies the performance criteria described above but in a fraction of the time by modifying the hash table to reflect the underlying distribution of training characters. Furthermore, we show that our approach outperforms pre-classification by clustering, ANN and conventional AM in terms of classification accuracy, discriminative power and speed. Compared to conventional associative matching, the proposed approach results in a 47% reduction in total processing time across an evaluation test set comprising 116,528 Japanese character images.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

PubMed

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

GIS coupled Multiple Criteria based Decision Support for Classification of Urban Coastal Areas in India

NASA Astrophysics Data System (ADS)

Dhiman, R.; Kalbar, P.; Inamdar, A. B.

2017-12-01

Coastal area classification in India is a challenge for federal and state government agencies due to fragile institutional framework, unclear directions in implementation of costal regulations and violations happening at private and government level. This work is an attempt to improvise the objectivity of existing classification methods to synergies the ecological systems and socioeconomic development in coastal cities. We developed a Geographic information system coupled Multi-criteria Decision Making (GIS-MCDM) approach to classify urban coastal areas where utility functions are used to transform the costal features into quantitative membership values after assessing the sensitivity of urban coastal ecosystem. Furthermore, these membership values for costal features are applied in different weighting schemes to derive Coastal Area Index (CAI) which classifies the coastal areas in four distinct categories viz. 1) No Development Zone, 2) Highly Sensitive Zone, 3) Moderately Sensitive Zone and 4) Low Sensitive Zone based on the sensitivity of urban coastal ecosystem. Mumbai, a coastal megacity in India is used as case study for demonstration of proposed method. Finally, uncertainty analysis using Monte Carlo approach to validate the sensitivity of CAI under specific multiple scenarios is carried out. Results of CAI method shows the clear demarcation of coastal areas in GIS environment based on the ecological sensitivity. CAI provides better decision support for federal and state level agencies to classify urban coastal areas according to the regional requirement of coastal resources considering resilience and sustainable development. CAI method will strengthen the existing institutional framework for decision making in classification of urban coastal areas where most effective coastal management options can be proposed.

A semi-automated image analysis procedure for in situ plankton imaging systems.

PubMed

Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M

2015-01-01

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that could not be removed by the procedure. The procedure was tested on 89,419 images collected in Chesapeake Bay, and results were consistent with visual counts with >80% accuracy for all three groups.

A Semi-Automated Image Analysis Procedure for In Situ Plankton Imaging Systems

PubMed Central

Bi, Hongsheng; Guo, Zhenhua; Benfield, Mark C.; Fan, Chunlei; Ford, Michael; Shahrestani, Suzan; Sieracki, Jeffery M.

2015-01-01

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that could not be removed by the procedure. The procedure was tested on 89,419 images collected in Chesapeake Bay, and results were consistent with visual counts with >80% accuracy for all three groups. PMID:26010260

Web-Enhanced Networking: A Future Alternative for Command and Control 2025

DTIC Science & Technology

2010-01-01

folksonomies .”6 Since the launch of Facebook in 2004, the utility of virtual networking and live stream applications has been brought to the main stage...connections that could exist between actors. (Kilduff & Tsai, p30) folksonomy A type of classification system for online content, created by an

A Call for an Empirical Taxonomy of Schools

ERIC Educational Resources Information Center

Van Ryzin, Mark J.

2008-01-01

Many educational researchers have identified issues on classifying schools and some have made use of ad-hoc classification systems in their analyses; however, these solutions are generally one-dimensional, which prohibits them from capturing the full breadth of variation among schools. To understand the amount of variation that exist in schools…

Library Automation: Guidelines to Costing.

ERIC Educational Resources Information Center

Ford, Geoffrey

As with all new programs, the costs associated with library automation must be carefully considered before implementation. This document suggests guidelines to be followed and areas to be considered in the costing of library procedures. An existing system model has been suggested as a standard (Appendix A) and a classification of library tasks…

Taxonomic Proposal: Create sixteen new species in existing genera of the families Alphaflexiviridae and Betaflexiviridae

USDA-ARS?s Scientific Manuscript database

A transparent and functional system for virus classification is essential to allow scientists to correctly identify and report on viruses detected in different hosts or locations without ambiguity. New research into relationships between previously characterized and newly-emerging viruses may requir...

Categorizing Drugs and Drug-Taking: A More Meaningful Approach.

ERIC Educational Resources Information Center

Gold, Robert S.; Duncan, David F.

This document reviews various definitions of the nature and classification of drugs. Difficulties with existing categorizations which use such bases as clinical utility, molecular structure, effects on the central nervous system, legality, and hazard potential are disucssed. A more meaningful categorization based on the availability and sources of…

The classification of anxiety and hysterical states. Part I. Historical review and empirical delineation.

PubMed

Sheehan, D V; Sheehan, K H

1982-08-01

The history of the classification of anxiety, hysterical, and hypochondriacal disorders is reviewed. Problems in the ability of current classification schemes to predict, control, and describe the relationship between the symptoms and other phenomena are outlined. Existing classification schemes failed the first test of a good classification model--that of providing categories that are mutually exclusive. The independence of these diagnostic categories from each other does not appear to hold up on empirical testing. In the absence of inherently mutually exclusive categories, further empirical investigation of these classes is obstructed since statistically valid analysis of the nominal data and any useful multivariate analysis would be difficult if not impossible. It is concluded that the existing classifications are unsatisfactory and require some fundamental reconceptualization.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed

Rocha, José C; Passalia, Felipe; Matos, Felipe D; Maserati, Marc P; Alves, Mayra F; Almeida, Tamie G de; Cardoso, Bruna L; Basso, Andrea C; Nogueira, Marcelo F G

2016-08-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed Central

Rocha, José C.; Passalia, Felipe; Matos, Felipe D.; Maserati Jr, Marc P.; Alves, Mayra F.; de Almeida, Tamie G.; Cardoso, Bruna L.; Basso, Andrea C.; Nogueira, Marcelo F. G.

2016-01-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment. PMID:27584609

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2017-01-01

Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection

PubMed Central

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2017-01-01

Objectives Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Methods Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Results Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. Conclusion The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports. PMID:28166263

SWOT analysis of Banff: strengths, weaknesses, opportunities and threats of the international Banff consensus process and classification system for renal allograft pathology.

PubMed

Mengel, M; Sis, B; Halloran, P F

2007-10-01

The Banff process defined the diagnostic histologic lesions for renal allograft rejection and created a standardized classification system where none had existed. By correcting this deficit the process had universal impact on clinical practice and clinical and basic research. All trials of new drugs since the early 1990s benefited, because the Banff classification of lesions permitted the end point of biopsy-proven rejection. The Banff process has strengths, weaknesses, opportunities and threats (SWOT). The strength is its self-organizing group structure to create consensus. Consensus does not mean correctness: defining consensus is essential if a widely held view is to be proved wrong. The weaknesses of the Banff process are the absence of an independent external standard to test the classification; and its almost exclusive reliance on histopathology, which has inherent limitations in intra- and interobserver reproducibility, particularly at the interface between borderline and rejection, is exactly where clinicians demand precision. The opportunity lies in the new technology such as transcriptomics, which can form an external standard and can be incorporated into a new classification combining the elegance of histopathology and the objectivity of transcriptomics. The threat is the degree to which the renal transplant community will participate in and support this process.

Continuous robust sound event classification using time-frequency features and deep learning

PubMed Central

Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification. PMID:28892478

Continuous robust sound event classification using time-frequency features and deep learning.

PubMed

McLoughlin, Ian; Zhang, Haomin; Xie, Zhipeng; Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification.

UAS Detection Classification and Neutralization: Market Survey 2015

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

Birch, Gabriel Carisle; Griffin, John Clark; Erdman, Matthew Kelly

The purpose of this document is to briefly frame the challenges of detecting low, slow, and small (LSS) unmanned aerial systems (UAS). The conclusion drawn from internal discussions and external reports is the following; detection of LSS UAS is a challenging problem that can- not be achieved with a single detection modality for all potential targets. Classification of LSS UAS, especially classification in the presence of background clutter (e.g., urban environment) or other non-threating targets (e.g., birds), is under-explored. Though information of avail- able technologies is sparse, many of the existing options for UAS detection appear to be in theirmore » infancy (when compared to more established ground-based air defense systems for larger and/or faster threats). Companies currently providing or developing technologies to combat the UAS safety and security problem are certainly worth investigating, however, no company has provided the statistical evidence necessary to support robust detection, identification, and/or neutralization of LSS UAS targets. The results of a market survey are included that highlights potential commercial entities that could contribute some technology that assists in the detection, classification, and neutral- ization of a LSS UAS. This survey found no clear and obvious commercial solution, though recommendations are given for further investigation of several potential systems.« less

A Bayesian taxonomic classification method for 16S rRNA gene sequences with improved species-level accuracy.

PubMed

Gao, Xiang; Lin, Huaiying; Revanna, Kashi; Dong, Qunfeng

2017-05-10

Species-level classification for 16S rRNA gene sequences remains a serious challenge for microbiome researchers, because existing taxonomic classification tools for 16S rRNA gene sequences either do not provide species-level classification, or their classification results are unreliable. The unreliable results are due to the limitations in the existing methods which either lack solid probabilistic-based criteria to evaluate the confidence of their taxonomic assignments, or use nucleotide k-mer frequency as the proxy for sequence similarity measurement. We have developed a method that shows significantly improved species-level classification results over existing methods. Our method calculates true sequence similarity between query sequences and database hits using pairwise sequence alignment. Taxonomic classifications are assigned from the species to the phylum levels based on the lowest common ancestors of multiple database hits for each query sequence, and further classification reliabilities are evaluated by bootstrap confidence scores. The novelty of our method is that the contribution of each database hit to the taxonomic assignment of the query sequence is weighted by a Bayesian posterior probability based upon the degree of sequence similarity of the database hit to the query sequence. Our method does not need any training datasets specific for different taxonomic groups. Instead only a reference database is required for aligning to the query sequences, making our method easily applicable for different regions of the 16S rRNA gene or other phylogenetic marker genes. Reliable species-level classification for 16S rRNA or other phylogenetic marker genes is critical for microbiome research. Our software shows significantly higher classification accuracy than the existing tools and we provide probabilistic-based confidence scores to evaluate the reliability of our taxonomic classification assignments based on multiple database matches to query sequences. Despite its higher computational costs, our method is still suitable for analyzing large-scale microbiome datasets for practical purposes. Furthermore, our method can be applied for taxonomic classification of any phylogenetic marker gene sequences. Our software, called BLCA, is freely available at https://github.com/qunfengdong/BLCA .

CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes.

PubMed

White, Clarence; Ismail, Hamid D; Saigo, Hiroto; Kc, Dukka B

2017-12-28

The β-Lactamase (BL) enzyme family is an important class of enzymes that plays a key role in bacterial resistance to antibiotics. As the newly identified number of BL enzymes is increasing daily, it is imperative to develop a computational tool to classify the newly identified BL enzymes into one of its classes. There are two types of classification of BL enzymes: Molecular Classification and Functional Classification. Existing computational methods only address Molecular Classification and the performance of these existing methods is unsatisfactory. We addressed the unsatisfactory performance of the existing methods by implementing a Deep Learning approach called Convolutional Neural Network (CNN). We developed CNN-BLPred, an approach for the classification of BL proteins. The CNN-BLPred uses Gradient Boosted Feature Selection (GBFS) in order to select the ideal feature set for each BL classification. Based on the rigorous benchmarking of CCN-BLPred using both leave-one-out cross-validation and independent test sets, CCN-BLPred performed better than the other existing algorithms. Compared with other architectures of CNN, Recurrent Neural Network, and Random Forest, the simple CNN architecture with only one convolutional layer performs the best. After feature extraction, we were able to remove ~95% of the 10,912 features using Gradient Boosted Trees. During 10-fold cross validation, we increased the accuracy of the classic BL predictions by 7%. We also increased the accuracy of Class A, Class B, Class C, and Class D performance by an average of 25.64%. The independent test results followed a similar trend. We implemented a deep learning algorithm known as Convolutional Neural Network (CNN) to develop a classifier for BL classification. Combined with feature selection on an exhaustive feature set and using balancing method such as Random Oversampling (ROS), Random Undersampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE), CNN-BLPred performs significantly better than existing algorithms for BL classification.

A patch-based convolutional neural network for remote sensing image classification.

PubMed

Sharma, Atharva; Liu, Xiuwen; Yang, Xiaojun; Shi, Di

2017-11-01

Availability of accurate land cover information over large areas is essential to the global environment sustainability; digital classification using medium-resolution remote sensing data would provide an effective method to generate the required land cover information. However, low accuracy of existing per-pixel based classification methods for medium-resolution data is a fundamental limiting factor. While convolutional neural networks (CNNs) with deep layers have achieved unprecedented improvements in object recognition applications that rely on fine image structures, they cannot be applied directly to medium-resolution data due to lack of such fine structures. In this paper, considering the spatial relation of a pixel to its neighborhood, we propose a new deep patch-based CNN system tailored for medium-resolution remote sensing data. The system is designed by incorporating distinctive characteristics of medium-resolution data; in particular, the system computes patch-based samples from multidimensional top of atmosphere reflectance data. With a test site from the Florida Everglades area (with a size of 771 square kilometers), the proposed new system has outperformed pixel-based neural network, pixel-based CNN and patch-based neural network by 24.36%, 24.23% and 11.52%, respectively, in overall classification accuracy. By combining the proposed deep CNN and the huge collection of medium-resolution remote sensing data, we believe that much more accurate land cover datasets can be produced over large areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

Profile of a city: characterizing and classifying urban soils in the city of Ghent

NASA Astrophysics Data System (ADS)

Delbecque, Nele; Verdoodt, Ann

2017-04-01

Worldwide, urban lands are expanding rapidly. Conversion of agricultural and natural landscapes to urban fabric can strongly influence soil properties through soil sealing, excavation, leveling, contamination, waste disposal and land management. Urban lands, often characterized by intensive use, need to deliver many production, ecological and cultural ecosystem services. To safeguard this natural capital for future generations, an improved understanding of biogeochemical characteristics, processes and functions of urban soils in time and space is essential. Additionally, existing (inter)national soil classification systems, based on the identification of soil genetic horizons, do not always allow a functional classification of urban soils. This research aims (1) to gain insight into urban soils and their properties in the city of Ghent (Belgium), and (2) to develop a procedure to functionally incorporate urban soils into existing (inter)national soil classification systems. Undisturbed soil cores (depth up to 1.25 m) are collected at 15 locations in Ghent with different times since development and land uses. Geotek MSCL-scans are taken to determine magnetic susceptibility and gamma density and to obtain high resolution images. Physico-chemical characterization of the soil cores is performed by means of detailed soil profile descriptions, traditional lab analyses, as well as proximal soil sensing techniques (XRF). The first results of this research will be presented and critically discussed to improve future efforts to characterize, classify and evaluate urban soils and their ecosystem services.

Acute pesticide poisoning: a proposed classification tool.

PubMed

Thundiyil, Josef G; Stober, Judy; Besbelli, Nida; Pronczuk, Jenny

2008-03-01

Cases of acute pesticide poisoning (APP) account for significant morbidity and mortality worldwide. Developing countries are particularly susceptible due to poorer regulation, lack of surveillance systems, less enforcement, lack of training and inadequate access to information systems. Previous research has demonstrated wide variability in incidence rates for APP. This is possibly due to inconsistent reporting methodology and exclusion of occupational and non-intentional poisonings. The purpose of this document is to create a standard case definition to facilitate the identification and diagnosis of all causes of APP, especially at the field level, rural clinics and primary health-care systems. This document is a synthesis of existing literature and case definitions that have been previously proposed by other authors around the world. It provides a standardized case definition and classification scheme for APP into categories of probable, possible and unlikely/unknown cases. Its use is intended to be applicable worldwide to contribute to identification of the scope of existing problems and thus promote action for improved management and prevention. By enabling a field diagnosis for APP, this standardized case definition may facilitate immediate medical management of pesticide poisoning and aid in estimating its incidence.

Coal-cleaning plant refuse characterization

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

Cavalet, J.R.; Torak, E.R.

1985-06-01

This report describes a study performed for the Electric Power Research Institute's Coal Cleaning Test Facility in Homer City, Pennsylvania. The purpose of the study was to design a standard methods for chemically and physically classifying refuse generated by physical coal cleaning and to construct a matrix that will accurately predict how a particular refuse will react to particular disposal methods - based solely on raw-coal characteristics and the process used to clean the coal. The value of such a classification system (which has not existed to this point) is the ability to design efficient and economical systems for disposingmore » of specific coal cleaning refuse. The report describes the project's literature search and a four-tier classification system. It also provides designs for test piles, sampling procedures, and guidelines for a series of experiments to test the classfication system and create an accurate, reliable predictive matrix. 38 refs., 39 figs., 35 tabs.« less

ON DEPARTURES FROM INDEPENDENCE IN CROSS-CLASSIFICATIONS.

ERIC Educational Resources Information Center

CASE, C. MARSTON

THIS NOTE IS CONCERNED WITH IDEAS AND PROBLEMS INVOLVED IN CROSS-CLASSIFICATION OF OBSERVATIONS ON A GIVEN POPULATION, ESPECIALLY TWO-DIMENSIONAL CROSS-CLASSIFICATIONS. MAIN OBJECTIVES OF THE NOTE INCLUDE--(1) ESTABLISHMENT OF A CONCEPTUAL FRAMEWORK FOR CHARACTERIZATION AND COMPARISON OF CROSS-CLASSIFICATIONS, (2) DISCUSSION OF EXISTING METHODS…

46 CFR 8.250 - Acceptance of standards and functions delegated under existing regulations.

Code of Federal Regulations, 2011 CFR

2011-10-01

... APPLICABLE TO THE PUBLIC VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.250 Acceptance of standards and functions delegated under existing regulations. (a) Classification society class... society has received authorization to conduct a related delegated function. (b) A recognized...

46 CFR 8.250 - Acceptance of standards and functions delegated under existing regulations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... APPLICABLE TO THE PUBLIC VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.250 Acceptance of standards and functions delegated under existing regulations. (a) Classification society class... society has received authorization to conduct a related delegated function. (b) A recognized...

The changes in hazard classification and product notification procedures of the new European CLP and Cosmetics Regulations.

PubMed

de Groot, Ronald; Brekelmans, Pieter; Herremans, Joke; Meulenbelt, Jan

2010-01-01

The United Nations Globally Harmonized System of Classification and Labelling of Chemicals (UN-GHS) is developed to harmonize the criteria for hazard communication worldwide. The European Regulation on classification, labeling, and packaging of substances and mixtures [CLP Regulation (European Commission, EC) No 1272/2008] will align the existing European Union (EU) legislation to the UN-GHS. This CLP Regulation entered into force on January 20, 2009, and will, after a transitional period, replace the current rules on classification, labeling, and packaging for supply and use in Europe. Both old and new classifications will exist simultaneously until 2010 for substances and until 2015 for mixtures. The new hazard classification will introduce new health hazard classes and categories, with associated new hazard pictograms, signal words, Hazard (H)-statements, and Precautionary (P)-statements as labeling elements. Furthermore, the CLP Regulation will affect the notification of product information on hazardous products to poisons information centers (PICs). At this moment product notification widely varies in procedures and requirements across EU Member States. Article 45 of the CLP Regulation contains a provision stating that the EC will (by January 20, 2012) review the possibility of harmonizing product notification. The European Association of Poisons Centres and Clinical Toxicologists (EAPCCT) is recognized as an important stakeholder. For cosmetic products, the new Cosmetics Regulation will directly implement a new procedure for electronic cosmetic product notification in all EU Member States. Both the CLP Regulation and the Cosmetics Regulation will develop their own product notification procedure within different time frames. Harmonization of notification procedures for both product groups, especially a common electronic format, would be most effective from a cost-benefit viewpoint and would be welcomed by PICs.

Defining and classifying medical error: lessons for patient safety reporting systems.

PubMed

Tamuz, M; Thomas, E J; Franchois, K E

2004-02-01

It is important for healthcare providers to report safety related events, but little attention has been paid to how the definition and classification of events affects a hospital's ability to learn from its experience. To examine how the definition and classification of safety related events influences key organizational routines for gathering information, allocating incentives, and analyzing event reporting data. In semi-structured interviews, professional staff and administrators in a tertiary care teaching hospital and its pharmacy were asked to describe the existing programs designed to monitor medication safety, including the reporting systems. With a focus primarily on the pharmacy staff, interviews were audio recorded, transcribed, and analyzed using qualitative research methods. Eighty six interviews were conducted, including 36 in the hospital pharmacy. Examples are presented which show that: (1) the definition of an event could lead to under-reporting; (2) the classification of a medication error into alternative categories can influence the perceived incentives and disincentives for incident reporting; (3) event classification can enhance or impede organizational routines for data analysis and learning; and (4) routines that promote organizational learning within the pharmacy can reduce the flow of medication error data to the hospital. These findings from one hospital raise important practical and research questions about how reporting systems are influenced by the definition and classification of safety related events. By understanding more clearly how hospitals define and classify their experience, we may improve our capacity to learn and ultimately improve patient safety.

The Society for Vascular Surgery Lower Extremity Threatened Limb Classification System: risk stratification based on wound, ischemia, and foot infection (WIfI).

PubMed

Mills, Joseph L; Conte, Michael S; Armstrong, David G; Pomposelli, Frank B; Schanzer, Andres; Sidawy, Anton N; Andros, George

2014-01-01

Critical limb ischemia, first defined in 1982, was intended to delineate a subgroup of patients with a threatened lower extremity primarily because of chronic ischemia. It was the intent of the original authors that patients with diabetes be excluded or analyzed separately. The Fontaine and Rutherford Systems have been used to classify risk of amputation and likelihood of benefit from revascularization by subcategorizing patients into two groups: ischemic rest pain and tissue loss. Due to demographic shifts over the last 40 years, especially a dramatic rise in the incidence of diabetes mellitus and rapidly expanding techniques of revascularization, it has become increasingly difficult to perform meaningful outcomes analysis for patients with threatened limbs using these existing classification systems. Particularly in patients with diabetes, limb threat is part of a broad disease spectrum. Perfusion is only one determinant of outcome; wound extent and the presence and severity of infection also greatly impact the threat to a limb. Therefore, the Society for Vascular Surgery Lower Extremity Guidelines Committee undertook the task of creating a new classification of the threatened lower extremity that reflects these important considerations. We term this new framework, the Society for Vascular Surgery Lower Extremity Threatened Limb Classification System. Risk stratification is based on three major factors that impact amputation risk and clinical management: Wound, Ischemia, and foot Infection (WIfI). The implementation of this classification system is intended to permit more meaningful analysis of outcomes for various forms of therapy in this challenging, but heterogeneous population. Copyright © 2014 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

A New Tool for Classifying Small Solar System Objects

NASA Astrophysics Data System (ADS)

Desfosses, Ryan; Arel, D.; Walker, M. E.; Ziffer, J.; Harvell, T.; Campins, H.; Fernandez, Y. R.

2011-05-01

An artificial intelligence program, AutoClass, which was developed by NASA's Artificial Intelligence Branch, uses Bayesian classification theory to automatically choose the most probable classification distribution to describe a dataset. To investigate its usefulness to the Planetary Science community, we tested its ability to reproduce the taxonomic classes as defined by Tholen and Barucci (1989). Of the 406 asteroids from the Eight Color Asteroid Survey (ECAS) we chose for our test, 346 were firmly classified and all but 3 (<1%) were classified by Autoclass as they had been in the previous classification system (Walker et al., 2011). We are now applying it to larger datasets to improve the taxonomy of currently unclassified objects. Having demonstrated AutoClass's ability to recreate existing classification effectively, we extended this work to investigations of albedo-based classification systems. To determine how predictive albedo can be, we used data from the Infrared Astronomical Satellite (IRAS) database in conjunction with the large Sloan Digital Sky Survey (SDSS), which contains color and position data for over 200,000 classified and unclassified asteroids (Ivesic et al., 2001). To judge our success we compared our results with a similar approach to classifying objects using IRAS albedo and asteroid color by Tedesco et al. (1989). Understanding the distribution of the taxonomic classes is important to understanding the history and evolution of our Solar System. AutoClass's success in categorizing ECAS, IRAS and SDSS asteroidal data highlights its potential to scan large domains for natural classes in small solar system objects. Based upon our AutoClass results, we intend to make testable predictions about asteroids observed with the Wide-field Infrared Survey Explorer (WISE).

Optical character recognition of camera-captured images based on phase features

NASA Astrophysics Data System (ADS)

Diaz-Escobar, Julia; Kober, Vitaly

2015-09-01

Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.

Classification and Lineage Tracing of SH2 Domains Throughout Eukaryotes.

PubMed

Liu, Bernard A

2017-01-01

Today there exists a rapidly expanding number of sequenced genomes. Cataloging protein interaction domains such as the Src Homology 2 (SH2) domain across these various genomes can be accomplished with ease due to existing algorithms and predictions models. An evolutionary analysis of SH2 domains provides a step towards understanding how SH2 proteins integrated with existing signaling networks to position phosphotyrosine signaling as a crucial driver of robust cellular communication networks in metazoans. However organizing and tracing SH2 domain across organisms and understanding their evolutionary trajectory remains a challenge. This chapter describes several methodologies towards analyzing the evolutionary trajectory of SH2 domains including a global SH2 domain classification system, which facilitates annotation of new SH2 sequences essential for tracing the lineage of SH2 domains throughout eukaryote evolution. This classification utilizes a combination of sequence homology, protein domain architecture and the boundary positions between introns and exons within the SH2 domain or genes encoding these domains. Discrete SH2 families can then be traced across various genomes to provide insight into its origins. Furthermore, additional methods for examining potential mechanisms for divergence of SH2 domains from structural changes to alterations in the protein domain content and genome duplication will be discussed. Therefore a better understanding of SH2 domain evolution may enhance our insight into the emergence of phosphotyrosine signaling and the expansion of protein interaction domains.

THE USE OF GEOMORPHOLOGY AND STREAM STABILITY IN THE ASSESSMENT OF THE RISK OF STREAM IMPAIRMENT FROM SEDIMENT

EPA Science Inventory

The evaluation of the current condition is critical to the management of streams impaired by sediment and other non-point source stressors, which adversely affect both physical habitat and water quality. Several rating and classification systems based on geomorphic data exist for...

Identification of ICD Codes Suggestive of Child Maltreatment

ERIC Educational Resources Information Center

Schnitzer, Patricia G.; Slusher, Paula L.; Kruse, Robin L.; Tarleton, Molly M.

2011-01-01

Objective: In order to be reimbursed for the care they provide, hospitals in the United States are required to use a standard system to code all discharge diagnoses: the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9). Although ICD-9 codes specific for child maltreatment exist, they do not identify all…

Options for Conducting a Pay Equity Study of Federal Pay and Classification Systems.

ERIC Educational Resources Information Center

Comptroller General of the U.S., Washington, DC.

This report discusses ways to determine why female Federal employees earn less than male Federal employees. Two general approaches are discussed: economic analysis and job content. Economic analysis attempts to measure and explain existing wage differentials between men and women using characteristics of individuals, occupations, and the…

Developing a Value of Information (VoI) Enabled System from Collection to Analysis

DTIC Science & Technology

2016-11-01

Information, Android, smartphone , information dissemination, visual analytic 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...List of Figures Fig. 1 Spot report main screen .........................................................................2 Fig. 2 Smartphone app...included the creation of 2 Android smartphone applications (apps) and the enhancement of an existing tool (Contour). Prior work with Android

Innovation Policies from the European Union: Methods for Classification

ERIC Educational Resources Information Center

Rodriguez, Victor; Montalvo, Carlos

2007-01-01

This study focuses on taxonomic and typological methods of innovation policies in the European institutional context. Although many types of policies affect innovation, no universally accepted criteria exist to classify them. As innovation policy in a myriad of thematic areas--systemic model--has become pluralized, this article offers a method for…

A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.

PubMed

Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar

2017-08-01

Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Participatory Design Methods for C2 Systems (Proceedings/Presentation)

DTIC Science & Technology

2006-01-01

Cognitive Task Analysis (CTA) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION 18. NUMBER 19a. NAME OF RESPONSIBLE PERSON OF ABSTRACT OF PAGES Janet E. Miller...systems to support cognitive work such as is accomplished in a network-centric -environment. Cognitive task analysis (CTA) methods are used to...of cognitive task analysis methodologies exist (Schraagen et al., 2000). However, many of these methods are skeptically viewed by a domain’s

Vehicle detection in aerial surveillance using dynamic Bayesian networks.

PubMed

Cheng, Hsu-Yung; Weng, Chih-Chia; Chen, Yi-Ying

2012-04-01

We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.

Economics of childbirth.

PubMed

Fahy, Michael; Doyle, Orla; Denny, Kevin; McAuliffe, Fionnuala M; Robson, Michael

2013-05-01

Increasing birth rates have raised questions for policy makers and hospital management about the economic costs of childbirth. The purpose of this article is to identify and review all existing scientific studies in relation to the economic costs of alternative modes of childbirth delivery and to highlight deficiencies in the existing scientific research. We searched Cochrane, Centre for Reviews and Dissemination, EconLit, the Excerpta Medica Database, the Health Economic Evaluations Database, MEDLINE and PubMed. Thirty articles are included in this review. The main findings suggest that there is no internationally acceptable childbirth cost and clinical outcome classification system that allows for comparisons across different delivery modes. This review demonstrates that a better understanding and classification of the costs and associated clinical outcomes of childbirth is required to allow for valid comparisons between maternity units, and to inform policy makers and hospital management. © 2013 The Authors Acta Obstetricia et Gynecologica Scandinavica © 2013 Nordic Federation of Societies of Obstetrics and Gynecology.

Assignment of protein sequences to existing domain and family classification systems: Pfam and the PDB

PubMed Central

Dunbrack, Roland L.

2012-01-01

Motivation: Automating the assignment of existing domain and protein family classifications to new sets of sequences is an important task. Current methods often miss assignments because remote relationships fail to achieve statistical significance. Some assignments are not as long as the actual domain definitions because local alignment methods often cut alignments short. Long insertions in query sequences often erroneously result in two copies of the domain assigned to the query. Divergent repeat sequences in proteins are often missed. Results: We have developed a multilevel procedure to produce nearly complete assignments of protein families of an existing classification system to a large set of sequences. We apply this to the task of assigning Pfam domains to sequences and structures in the Protein Data Bank (PDB). We found that HHsearch alignments frequently scored more remotely related Pfams in Pfam clans higher than closely related Pfams, thus, leading to erroneous assignment at the Pfam family level. A greedy algorithm allowing for partial overlaps was, thus, applied first to sequence/HMM alignments, then HMM–HMM alignments and then structure alignments, taking care to join partial alignments split by large insertions into single-domain assignments. Additional assignment of repeat Pfams with weaker E-values was allowed after stronger assignments of the repeat HMM. Our database of assignments, presented in a database called PDBfam, contains Pfams for 99.4% of chains >50 residues. Availability: The Pfam assignment data in PDBfam are available at http://dunbrack2.fccc.edu/ProtCid/PDBfam, which can be searched by PDB codes and Pfam identifiers. They will be updated regularly. Contact: Roland.Dunbracks@fccc.edu PMID:22942020

Causes of death and associated conditions (Codac) – a utilitarian approach to the classification of perinatal deaths

PubMed Central

Frøen, J Frederik; Pinar, Halit; Flenady, Vicki; Bahrin, Safiah; Charles, Adrian; Chauke, Lawrence; Day, Katie; Duke, Charles W; Facchinetti, Fabio; Fretts, Ruth C; Gardener, Glenn; Gilshenan, Kristen; Gordijn, Sanne J; Gordon, Adrienne; Guyon, Grace; Harrison, Catherine; Koshy, Rachel; Pattinson, Robert C; Petersson, Karin; Russell, Laurie; Saastad, Eli; Smith, Gordon CS; Torabi, Rozbeh

2009-01-01

A carefully classified dataset of perinatal mortality will retain the most significant information on the causes of death. Such information is needed for health care policy development, surveillance and international comparisons, clinical services and research. For comparability purposes, we propose a classification system that could serve all these needs, and be applicable in both developing and developed countries. It is developed to adhere to basic concepts of underlying cause in the International Classification of Diseases (ICD), although gaps in ICD prevent classification of perinatal deaths solely on existing ICD codes. We tested the Causes of Death and Associated Conditions (Codac) classification for perinatal deaths in seven populations, including two developing country settings. We identified areas of potential improvements in the ability to retain existing information, ease of use and inter-rater agreement. After revisions to address these issues we propose Version II of Codac with detailed coding instructions. The ten main categories of Codac consist of three key contributors to global perinatal mortality (intrapartum events, infections and congenital anomalies), two crucial aspects of perinatal mortality (unknown causes of death and termination of pregnancy), a clear distinction of conditions relevant only to the neonatal period and the remaining conditions are arranged in the four anatomical compartments (fetal, cord, placental and maternal). For more detail there are 94 subcategories, further specified in 577 categories in the full version. Codac is designed to accommodate both the main cause of death as well as two associated conditions. We suggest reporting not only the main cause of death, but also the associated relevant conditions so that scenarios of combined conditions and events are captured. The appropriately applied Codac system promises to better manage information on causes of perinatal deaths, the conditions associated with them, and the most common clinical scenarios for future study and comparisons. PMID:19515228

Causes of death and associated conditions (Codac): a utilitarian approach to the classification of perinatal deaths.

PubMed

Frøen, J Frederik; Pinar, Halit; Flenady, Vicki; Bahrin, Safiah; Charles, Adrian; Chauke, Lawrence; Day, Katie; Duke, Charles W; Facchinetti, Fabio; Fretts, Ruth C; Gardener, Glenn; Gilshenan, Kristen; Gordijn, Sanne J; Gordon, Adrienne; Guyon, Grace; Harrison, Catherine; Koshy, Rachel; Pattinson, Robert C; Petersson, Karin; Russell, Laurie; Saastad, Eli; Smith, Gordon C S; Torabi, Rozbeh

2009-06-10

A carefully classified dataset of perinatal mortality will retain the most significant information on the causes of death. Such information is needed for health care policy development, surveillance and international comparisons, clinical services and research. For comparability purposes, we propose a classification system that could serve all these needs, and be applicable in both developing and developed countries. It is developed to adhere to basic concepts of underlying cause in the International Classification of Diseases (ICD), although gaps in ICD prevent classification of perinatal deaths solely on existing ICD codes.We tested the Causes of Death and Associated Conditions (Codac) classification for perinatal deaths in seven populations, including two developing country settings. We identified areas of potential improvements in the ability to retain existing information, ease of use and inter-rater agreement. After revisions to address these issues we propose Version II of Codac with detailed coding instructions.The ten main categories of Codac consist of three key contributors to global perinatal mortality (intrapartum events, infections and congenital anomalies), two crucial aspects of perinatal mortality (unknown causes of death and termination of pregnancy), a clear distinction of conditions relevant only to the neonatal period and the remaining conditions are arranged in the four anatomical compartments (fetal, cord, placental and maternal).For more detail there are 94 subcategories, further specified in 577 categories in the full version. Codac is designed to accommodate both the main cause of death as well as two associated conditions. We suggest reporting not only the main cause of death, but also the associated relevant conditions so that scenarios of combined conditions and events are captured.The appropriately applied Codac system promises to better manage information on causes of perinatal deaths, the conditions associated with them, and the most common clinical scenarios for future study and comparisons.

Beluga whale (Delphinapterus leucas) vocalizations and call classification from the eastern Beaufort Sea population.

PubMed

Garland, Ellen C; Castellote, Manuel; Berchok, Catherine L

2015-06-01

Beluga whales, Delphinapterus leucas, have a graded call system; call types exist on a continuum making classification challenging. A description of vocalizations from the eastern Beaufort Sea beluga population during its spring migration are presented here, using both a non-parametric classification tree analysis (CART), and a Random Forest analysis. Twelve frequency and duration measurements were made on 1019 calls recorded over 14 days off Icy Cape, Alaska, resulting in 34 identifiable call types with 83% agreement in classification for both CART and Random Forest analyses. This high level of agreement in classification, with an initial subjective classification of calls into 36 categories, demonstrates that the methods applied here provide a quantitative analysis of a graded call dataset. Further, as calls cannot be attributed to individuals using single sensor passive acoustic monitoring efforts, these methods provide a comprehensive analysis of data where the influence of pseudo-replication of calls from individuals is unknown. This study is the first to describe the vocal repertoire of a beluga population using a robust and repeatable methodology. A baseline eastern Beaufort Sea beluga population repertoire is presented here, against which the call repertoire of other seasonally sympatric Alaskan beluga populations can be compared.

A scheme for a flexible classification of dietary and health biomarkers.

PubMed

Gao, Qian; Praticò, Giulia; Scalbert, Augustin; Vergères, Guy; Kolehmainen, Marjukka; Manach, Claudine; Brennan, Lorraine; Afman, Lydia A; Wishart, David S; Andres-Lacueva, Cristina; Garcia-Aloy, Mar; Verhagen, Hans; Feskens, Edith J M; Dragsted, Lars O

2017-01-01

Biomarkers are an efficient means to examine intakes or exposures and their biological effects and to assess system susceptibility. Aided by novel profiling technologies, the biomarker research field is undergoing rapid development and new putative biomarkers are continuously emerging in the scientific literature. However, the existing concepts for classification of biomarkers in the dietary and health area may be ambiguous, leading to uncertainty about their application. In order to better understand the potential of biomarkers and to communicate their use and application, it is imperative to have a solid scheme for biomarker classification that will provide a well-defined ontology for the field. In this manuscript, we provide an improved scheme for biomarker classification based on their intended use rather than the technology or outcomes (six subclasses are suggested: food compound intake biomarkers (FCIBs), food or food component intake biomarkers (FIBs), dietary pattern biomarkers (DPBs), food compound status biomarkers (FCSBs), effect biomarkers, physiological or health state biomarkers). The application of this scheme is described in detail for the dietary and health area and is compared with previous biomarker classification for this field of research.

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

NASA Astrophysics Data System (ADS)

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.

An economic analysis of money follows the patient.

PubMed

McElroy, B; Murphy, A

2014-03-01

As part of the proposed changes to re-design the Irish health-care system, the Department of Health (money follows the patient-policy paper on hospital financing, 2013b) outlined a new funding model for Irish hospitals-money follows the patient (MFTP). This will replace the existing system which is predominately prospective with hospitals receiving a block grant per annum. MFTP will fund episodes of care rather than hospitals. Thus, hospital revenue will be directly linked to activity [activity-based funding (ABF)]. With ABF there is a fundamental shift to a system where hospitals generate their own income and this changes incentive structures. While some of these incentives are intended (reducing cost per case and increasing coding quality), others are less intended and less desirable. As a result, there may be reductions in quality, upcoding, cream skimming and increased pressure on other parts of the health system. In addition, MFTP may distort health system priorities. There are some feasibility concerns associated with the implementation of MFTP. Data collection, coding and classification capacity are crucial for its success. While MFTP can build on existing systems, significant investment is required for its success. This includes investment in coding and classification, infrastructure, skills, IT, contracting, commissioning, auditing and performance monitoring systems. Despite the challenges facing implementers, MFTP could greatly improve the transparency and accountability of the system. Thus if the downside risks are managed, there is potential for MFTP to confer significant benefits to Irish hospital care.

The Psychosomatic Disorders Pertaining to Dental Practice with Revised Working Type Classification

PubMed Central

2014-01-01

Psychosomatic disorders are defined as disorders characterized by physiological changes that originate partially from emotional factors. This article aims to discuss the psychosomatic disorders of the oral cavity with a revised working type classification. The author has added one more subset to the existing classification, i.e., disorders caused by altered perception of dentofacial form and function, which include body dysmorphic disorder. The author has also inserted delusional halitosis under the miscellaneous disorders classification of psychosomatic disorders and revised the already existing classification proposed for the psychosomatic disorders pertaining to dental practice. After the inclusion of the subset (disorders caused by altered perception of dentofacial form and function), the terminology "psychosomatic disorders of the oral cavity" is modified to "psychosomatic disorders pertaining to dental practice". PMID:24478896

The psychosomatic disorders pertaining to dental practice with revised working type classification.

PubMed

Shamim, Thorakkal

2014-01-01

Psychosomatic disorders are defined as disorders characterized by physiological changes that originate partially from emotional factors. This article aims to discuss the psychosomatic disorders of the oral cavity with a revised working type classification. The author has added one more subset to the existing classification, i.e., disorders caused by altered perception of dentofacial form and function, which include body dysmorphic disorder. The author has also inserted delusional halitosis under the miscellaneous disorders classification of psychosomatic disorders and revised the already existing classification proposed for the psychosomatic disorders pertaining to dental practice. After the inclusion of the subset (disorders caused by altered perception of dentofacial form and function), the terminology "psychosomatic disorders of the oral cavity" is modified to "psychosomatic disorders pertaining to dental practice".

Classifications for Cesarean Section: A Systematic Review

PubMed Central

Torloni, Maria Regina; Betran, Ana Pilar; Souza, Joao Paulo; Widmer, Mariana; Allen, Tomas; Gulmezoglu, Metin; Merialdi, Mario

2011-01-01

Background Rising cesarean section (CS) rates are a major public health concern and cause worldwide debates. To propose and implement effective measures to reduce or increase CS rates where necessary requires an appropriate classification. Despite several existing CS classifications, there has not yet been a systematic review of these. This study aimed to 1) identify the main CS classifications used worldwide, 2) analyze advantages and deficiencies of each system. Methods and Findings Three electronic databases were searched for classifications published 1968–2008. Two reviewers independently assessed classifications using a form created based on items rated as important by international experts. Seven domains (ease, clarity, mutually exclusive categories, totally inclusive classification, prospective identification of categories, reproducibility, implementability) were assessed and graded. Classifications were tested in 12 hypothetical clinical case-scenarios. From a total of 2948 citations, 60 were selected for full-text evaluation and 27 classifications identified. Indications classifications present important limitations and their overall score ranged from 2–9 (maximum grade = 14). Degree of urgency classifications also had several drawbacks (overall scores 6–9). Woman-based classifications performed best (scores 5–14). Other types of classifications require data not routinely collected and may not be relevant in all settings (scores 3–8). Conclusions This review and critical appraisal of CS classifications is a methodologically sound contribution to establish the basis for the appropriate monitoring and rational use of CS. Results suggest that women-based classifications in general, and Robson's classification, in particular, would be in the best position to fulfill current international and local needs and that efforts to develop an internationally applicable CS classification would be most appropriately placed in building upon this classification. The use of a single CS classification will facilitate auditing, analyzing and comparing CS rates across different settings and help to create and implement effective strategies specifically targeted to optimize CS rates where necessary. PMID:21283801

Pathological brain detection based on wavelet entropy and Hu moment invariants.

PubMed

Zhang, Yudong; Wang, Shuihua; Sun, Ping; Phillips, Preetha

2015-01-01

With the aim of developing an accurate pathological brain detection system, we proposed a novel automatic computer-aided diagnosis (CAD) to detect pathological brains from normal brains obtained by magnetic resonance imaging (MRI) scanning. The problem still remained a challenge for technicians and clinicians, since MR imaging generated an exceptionally large information dataset. A new two-step approach was proposed in this study. We used wavelet entropy (WE) and Hu moment invariants (HMI) for feature extraction, and the generalized eigenvalue proximal support vector machine (GEPSVM) for classification. To further enhance classification accuracy, the popular radial basis function (RBF) kernel was employed. The 10 runs of k-fold stratified cross validation result showed that the proposed "WE + HMI + GEPSVM + RBF" method was superior to existing methods w.r.t. classification accuracy. It obtained the average classification accuracies of 100%, 100%, and 99.45% over Dataset-66, Dataset-160, and Dataset-255, respectively. The proposed method is effective and can be applied to realistic use.

Towards an information geometric characterization/classification of complex systems. I. Use of generalized entropies

NASA Astrophysics Data System (ADS)

Ghikas, Demetris P. K.; Oikonomou, Fotios D.

2018-04-01

Using the generalized entropies which depend on two parameters we propose a set of quantitative characteristics derived from the Information Geometry based on these entropies. Our aim, at this stage, is to construct first some fundamental geometric objects which will be used in the development of our geometrical framework. We first establish the existence of a two-parameter family of probability distributions. Then using this family we derive the associated metric and we state a generalized Cramer-Rao Inequality. This gives a first two-parameter classification of complex systems. Finally computing the scalar curvature of the information manifold we obtain a further discrimination of the corresponding classes. Our analysis is based on the two-parameter family of generalized entropies of Hanel and Thurner (2011).

Acute kidney injury: not just acute renal failure anymore?

PubMed

Dirkes, Susan

2011-02-01

Until recently, no uniform standard existed for diagnosing and classifying acute renal failure. To clarify diagnosis, the Acute Dialysis Quality Initiative group stated its consensus on the need for a clear definition and classification system of renal dysfunction with measurable criteria. Today the term acute kidney injury has replaced the term acute renal failure, with an understanding that such injury is a common clinical problem in critically ill patients and typically is predictive of an increase in morbidity and mortality. A classification system, known as RIFLE (risk of injury, injury, failure, loss of function, and end-stage renal failure), includes specific goals for preventing acute kidney injury: adequate hydration, maintenance of renal perfusion, limiting exposure to nephrotoxins, drug protective strategies, and the use of renal replacement therapies that reduce renal injury.

A coastal and marine digital library at USGS

USGS Publications Warehouse

Lightsom, Fran

2003-01-01

The Marine Realms Information Bank (MRIB) is a distributed geolibrary [NRC, 1999] from the U.S. Geological Survey (USGS) and the Woods Hole Oceanographic Institution (WHOI), whose purpose is to classify, integrate, and facilitate access to Earth systems science information about ocean, lake, and coastal environments. Core MRIB services are: (1) the search and display of information holdings by place and subject, and (2) linking of information assets that exist in remote physical locations. The design of the MRIB features a classification system to integrate information from remotely maintained sources. This centralized catalogue organizes information using 12 criteria: locations, geologic time, physiographic features, biota, disciplines, research methods, hot topics, project names, agency names, authors, content type, and file type. For many of these fields, MRIB has developed classification hierarchies.

Case definition and classification of leukodystrophies and leukoencephalopathies.

PubMed

Vanderver, Adeline; Prust, Morgan; Tonduti, Davide; Mochel, Fanny; Hussey, Heather M; Helman, Guy; Garbern, James; Eichler, Florian; Labauge, Pierre; Aubourg, Patrick; Rodriguez, Diana; Patterson, Marc C; Van Hove, Johan L K; Schmidt, Johanna; Wolf, Nicole I; Boespflug-Tanguy, Odile; Schiffmann, Raphael; van der Knaap, Marjo S

2015-04-01

An approved definition of the term leukodystrophy does not currently exist. The lack of a precise case definition hampers efforts to study the epidemiology and the relevance of genetic white matter disorders to public health. Thirteen experts at multiple institutions participated in iterative consensus building surveys to achieve definition and classification of disorders as leukodystrophies using a modified Delphi approach. A case definition for the leukodystrophies was achieved, and a total of 30 disorders were classified under this definition. In addition, a separate set of disorders with heritable white matter abnormalities but not meeting criteria for leukodystrophy, due to presumed primary neuronal involvement and prominent systemic manifestations, was classified as genetic leukoencephalopathies (gLE). A case definition of leukodystrophies and classification of heritable white matter disorders will permit more detailed epidemiologic studies of these disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

Literature survey for suppression of scattered light in large space telescopes

NASA Technical Reports Server (NTRS)

Tifft, W. G.; Fannin, B. B.

1973-01-01

A literature survey is presented of articles dealing with all aspects of predicting, measuring, and controlling unwanted scattered (stray) light. The survey is divided into four broad classifications: (1) existing baffle/telescope designs; (2) computer programs for the analysis/design of light suppression systems; (3) the mechanism, measurement, and control of light scattering; and (4) the advantages and problems introduced by the space environment for the operation of diffraction-limited optical systems.

Fusion with Language Models Improves Spelling Accuracy for ERP-based Brain Computer Interface Spellers

PubMed Central

Orhan, Umut; Erdogmus, Deniz; Roark, Brian; Purwar, Shalini; Hild, Kenneth E.; Oken, Barry; Nezamfar, Hooman; Fried-Oken, Melanie

2013-01-01

Event related potentials (ERP) corresponding to a stimulus in electroencephalography (EEG) can be used to detect the intent of a person for brain computer interfaces (BCI). This paradigm is widely utilized to build letter-by-letter text input systems using BCI. Nevertheless using a BCI-typewriter depending only on EEG responses will not be sufficiently accurate for single-trial operation in general, and existing systems utilize many-trial schemes to achieve accuracy at the cost of speed. Hence incorporation of a language model based prior or additional evidence is vital to improve accuracy and speed. In this paper, we study the effects of Bayesian fusion of an n-gram language model with a regularized discriminant analysis ERP detector for EEG-based BCIs. The letter classification accuracies are rigorously evaluated for varying language model orders as well as number of ERP-inducing trials. The results demonstrate that the language models contribute significantly to letter classification accuracy. Specifically, we find that a BCI-speller supported by a 4-gram language model may achieve the same performance using 3-trial ERP classification for the initial letters of the words and using single trial ERP classification for the subsequent ones. Overall, fusion of evidence from EEG and language models yields a significant opportunity to increase the word rate of a BCI based typing system. PMID:22255652

Discovering disease-disease associations by fusing systems-level molecular data

PubMed Central

Žitnik, Marinka; Janjić, Vuk; Larminie, Chris; Zupan, Blaž; Pržulj, Nataša

2013-01-01

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion. PMID:24232732

Discovering disease-disease associations by fusing systems-level molecular data.

PubMed

Žitnik, Marinka; Janjić, Vuk; Larminie, Chris; Zupan, Blaž; Pržulj, Nataša

2013-11-15

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion.

Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification.

PubMed

d'Alessandro, Brian; O'Neil, Cathy; LaGatta, Tom

2017-06-01

Recent research has helped to cultivate growing awareness that machine-learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science community, leaving its members with little concrete guidance to proactively address these concerns. This article introduces issues of discrimination to the data science community on its own terms. In it, we tour the familiar data-mining process while providing a taxonomy of common practices that have the potential to produce unintended discrimination. We also survey how discrimination is commonly measured, and suggest how familiar development processes can be augmented to mitigate systems' discriminatory potential. We advocate that data scientists should be intentional about modeling and reducing discriminatory outcomes. Without doing so, their efforts will result in perpetuating any systemic discrimination that may exist, but under a misleading veil of data-driven objectivity.

Developing an Information Infrastructure To Support Information Retrieval: Towards a Theory of Clustering Based in Classification.

ERIC Educational Resources Information Center

Micco, Mary; Popp, Rich

Techniques for building a world-wide information infrastructure by reverse engineering existing databases to link them in a hierarchical system of subject clusters to create an integrated database are explored. The controlled vocabulary of the Library of Congress Subject Headings is used to ensure consistency and group similar items. Each database…

Spontaneously Combustible Solids -- A Literature Search

DTIC Science & Technology

1975-05-01

Wasahizeon, D.* C. It. K(EY WORDS (Continue on reviers side It necesary and Identify by block number) Pyrophoric Materials Hazardous Materials...and Identify by block number) Existing information on spontaneously combustible solids including pyrophoric - air hazardous materials and water... pyrophoric -air hazardous and water reactive materials. All available hazard classification systems and test methods releting to spontaneous combustion have

[To represent needs of nursing care using nursing diagnoses: potentials and restrictions of the NANDA classification and ICNP].

PubMed

Schilder, Michael

2005-03-01

Nursing diagnoses represent individual reactions to existing or potential changes in one's state of health. They are result of a diagnostic process, which is part of the dynamic nursing care process in its whole. Thus, as a basis of nursing interventions diagnoses have to be proved continuously. The classification of the North American Nursing Diagnosis Association (NANDA) as well as the International Classification for Nursing Practice (ICNP) can be account to the international well-known classifications of nursing diagnoses. Comparing their structures, some fundamental differences between both classifications become obvious. While the NANDA classification represents a systematic structured body of nursing knowledge with regard to human health reactions patterns, the ICNP reflects a more comprehensive part of the nursing reality, since it also contains nursing interventions and outcomes. Until the latest changes by establishing the taxonomy II, NANDA diagnoses have primarily focused deficits. But in contrast to the diagnoses of the ICNP they also comprise etiological factors. To prove the applicability of both classifications to nursing practice, they have been applied to a case study of a female resident living in a nursing home. The results of analysis show that because of their different structures the NANDA classification and ICNP have their own possibilities and limitations in covering the resident's individual needs of nursing care. These characteristic potentials and restrictions have to be taken into account when one of the classification systems is going to be implemented into nursing practice.

On the validity of Zeeman's classification for three dimensional competitive differential equations with linearly determined nullclines

NASA Astrophysics Data System (ADS)

Jiang, Jifa; Niu, Lei

2017-12-01

We study three dimensional competitive differential equations with linearly determined nullclines and prove that they always have 33 stable nullcline classes in total. Each class is given in terms of inequalities on the intrinsic growth rates and competitive coefficients and is independent of generating functions. The common characteristics are that every trajectory converges to an equilibrium in classes 1-25, that Hopf bifurcations do not occur within class 32, and that there is always a heteroclinic cycle in class 27. Nontrivial dynamical behaviors, such as the existence and multiplicity of limit cycles, only may occur in classes 26-33, but these nontrivial dynamical behaviors depend on generating functions. We show that Hopf bifurcation can occur within each of classes 26-31 for continuous-time Leslie/Gower system and Ricker system, the same as Lotka-Volterra system; but it only occurs in classes 26 and 27 for continuous-time Atkinson/Allen system and Gompertz system. There is an apparent distinction between Lotka-Volterra system and Leslie/Gower system, Ricker system, Atkinson/Allen system, and Gompertz system with the identical growth rate. Lotka-Volterra system with the identical growth rate has no limit cycle, but admits a center on the carrying simplex in classes 26 and 27. But Leslie/Gower system, Ricker system, Atkinson/Allen system, and Gompertz system with the identical growth rate do possess limit cycles. At last, we provide examples to show that Leslie/Gower system and Ricker system can also admit two limit cycles. This general classification greatly widens applications of Zeeman's method and makes it possible to investigate the existence and multiplicity of limit cycles, centers and stability of heteroclinic cycles for three dimensional competitive systems with linearly determined nullclines, as done in planar systems.

Using existing case-mix methods to fund trauma cases.

PubMed

Monakova, Julia; Blais, Irene; Botz, Charles; Chechulin, Yuriy; Picciano, Gino; Basinski, Antoni

2010-01-01

Policymakers frequently face the need to increase funding in isolated and frequently heterogeneous (clinically and in terms of resource consumption) patient subpopulations. This article presents a methodologic solution for testing the appropriateness of using existing grouping and weighting methodologies for funding subsets of patients in the scenario where a case-mix approach is preferable to a flat-rate based payment system. Using as an example the subpopulation of trauma cases of Ontario lead trauma hospitals, the statistical techniques of linear and nonlinear regression models, regression trees, and spline models were applied to examine the fit of the existing case-mix groups and reference weights for the trauma cases. The analyses demonstrated that for funding Ontario trauma cases, the existing case-mix systems can form the basis for rational and equitable hospital funding, decreasing the need to develop a different grouper for this subset of patients. This study confirmed that Injury Severity Score is a poor predictor of costs for trauma patients. Although our analysis used the Canadian case-mix classification system and cost weights, the demonstrated concept of using existing case-mix systems to develop funding rates for specific subsets of patient populations may be applicable internationally.

Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics

NASA Astrophysics Data System (ADS)

Cho, Baek Hwan; Chang, Chuho; Lee, Jong-Ha; Ko, Eun Young; Seong, Yeong Kyeong; Woo, Kyoung-Gu

2013-02-01

The existence of microcalcifications (MCs) is an important marker of malignancy in breast cancer. In spite of the benefits in mass detection for dense breasts, ultrasonography is believed that it might not reliably detect MCs. For computer aided diagnosis systems, however, accurate detection of MCs has the possibility of improving the performance in both Breast Imaging-Reporting and Data System (BI-RADS) lexicon description for calcifications and malignancy classification. We propose a new efficient and effective method for MC detection using image enhancement and threshold adjacency statistics (TAS). The main idea of TAS is to threshold an image and to count the number of white pixels with a given number of adjacent white pixels. Our contribution is to adopt TAS features and apply image enhancement to facilitate MC detection in ultrasound images. We employed fuzzy logic, tophat filter, and texture filter to enhance images for MCs. Using a total of 591 images, the classification accuracy of the proposed method in MC detection showed 82.75%, which is comparable to that of Haralick texture features (81.38%). When combined, the performance was as high as 85.11%. In addition, our method also showed the ability in mass classification when combined with existing features. In conclusion, the proposed method exploiting image enhancement and TAS features has the potential to deal with MC detection in ultrasound images efficiently and extend to the real-time localization and visualization of MCs.

9 CFR 145.94 - Terminology and classification; States.

Code of Federal Regulations, 2014 CFR

2014-01-01

... classification; States. (a) U.S. Pullorum-Typhoid Clean State. (1) A State will be declared a U.S. Pullorum-Typhoid Clean State when it has been determined by the Service that: (i) The State is in compliance with...)(i) through (vii). (ii) No pullorum disease or fowl typhoid is known to exist nor to have existed in...

9 CFR 145.94 - Terminology and classification; States.

Code of Federal Regulations, 2012 CFR

2012-01-01

... classification; States. (a) U.S. Pullorum-Typhoid Clean State. (1) A State will be declared a U.S. Pullorum-Typhoid Clean State when it has been determined by the Service that: (i) The State is in compliance with...)(i) through (vii). (ii) No pullorum disease or fowl typhoid is known to exist nor to have existed in...

9 CFR 145.94 - Terminology and classification; States.

Code of Federal Regulations, 2013 CFR

2013-01-01

... classification; States. (a) U.S. Pullorum-Typhoid Clean State. (1) A State will be declared a U.S. Pullorum-Typhoid Clean State when it has been determined by the Service that: (i) The State is in compliance with...)(i) through (vii). (ii) No pullorum disease or fowl typhoid is known to exist nor to have existed in...

A data-stream classification system for investigating terrorist threats

NASA Astrophysics Data System (ADS)

Schulz, Alexia; Dettman, Joshua; Gottschalk, Jeffrey; Kotson, Michael; Vuksani, Era; Yu, Tamara

2016-05-01

The role of cyber forensics in criminal investigations has greatly increased in recent years due to the wealth of data that is collected and available to investigators. Physical forensics has also experienced a data volume and fidelity revolution due to advances in methods for DNA and trace evidence analysis. Key to extracting insight is the ability to correlate across multi-modal data, which depends critically on identifying a touch-point connecting the separate data streams. Separate data sources may be connected because they refer to the same individual, entity or event. In this paper we present a data source classification system tailored to facilitate the investigation of potential terrorist activity. This taxonomy is structured to illuminate the defining characteristics of a particular terrorist effort and designed to guide reporting to decision makers that is complete, concise, and evidence-based. The classification system has been validated and empirically utilized in the forensic analysis of a simulated terrorist activity. Next-generation analysts can use this schema to label and correlate across existing data streams, assess which critical information may be missing from the data, and identify options for collecting additional data streams to fill information gaps.

Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images.

PubMed

Mane, Vijay Mahadeo; Jadhav, D V

2017-05-24

Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

Classification of gravity-flow deposits and their significance for unconventional petroleum exploration, with a case study from the Triassic Yanchang Formation (southern Ordos Basin, China)

NASA Astrophysics Data System (ADS)

Fan, Aiping; Yang, Renchao; (Tom) van Loon, A. J.; Yin, Wei; Han, Zuozhen; Zavala, Carlos

2018-08-01

The ongoing exploration for shale oil and gas has focused sedimentological research on the transport and deposition mechanisms of fine-grained sediments, and more specifically on fine-grained mass-flow deposits. It appears, however, that no easily applicable classification scheme for gravity-flow deposits exists, and that such classifications almost exclusively deal with sandy and coarser sediments. Since the lack of a good classification system for fine-grained gravity flow deposits hampers scientific communication and understanding, we propose a classification scheme on the basis of the mud content in combination with the presumed transport mechanism. This results in twelve types of gravity-flow deposits. In order to show the practical applicability of this classification system, we apply it to the Triassic lacustrine Yanchang Formation in the southern Ordos Basin (China), which contains numerous slumps, debris-flows deposits, turbidites and hyperpycnites. The slumps and debrites occur mostly close to a delta front, and the turbidites and hyperpycnites extend over large areas from the delta slopes into the basin plain. The case study shows that (1) mud cannot only be transported but also deposited under active hydrodynamic conditions; (2) fine-grained gravity-flow constitute a significant part of the lacustrine mudstones and shales; (3) muddy gravity flows are important for the transport and deposition of clastic particles, clay minerals and organic matter, and thus are important mechanisms involved in the generation of hydrocarbons, also largely determining the reservoir capability for unconventional petroleum.

Levels of Evidence in Cosmetic Surgery: Analysis and Recommendations Using a New CLEAR Classification

PubMed Central

2013-01-01

Background: The Level of Evidence rating was introduced in 2011 to grade the quality of publications. This system evaluates study design but does not assess several other quality indicators. This study introduces a new “Cosmetic Level of Evidence And Recommendation” (CLEAR) classification that includes additional methodological criteria and compares this new classification with the existing system. Methods: All rated publications in the Cosmetic Section of Plastic and Reconstructive Surgery, July 2011 through June 2013, were evaluated. The published Level of Evidence rating (1–5) and criteria relevant to study design and methodology for each study were tabulated. A new CLEAR rating was assigned to each article, including a recommendation grade (A–D). The published Level of Evidence rating (1–5) was compared with the recommendation grade determined using the CLEAR classification. Results: Among the 87 cosmetic articles, 48 studies (55%) were designated as level 4. Three articles were assigned a level 1, but they contained deficiencies sufficient to undermine the conclusions. The correlation between the published Level of Evidence classification (1–5) and CLEAR Grade (A–D) was weak (ρ = 0.11, not significant). Only 41 studies (48%) evaluated consecutive patients or consecutive patients meeting inclusion criteria. Conclusions: The CLEAR classification considers methodological factors in evaluating study reliability. A prospective study among consecutive patients meeting eligibility criteria, with a reported inclusion rate, the use of contemporaneous controls when indicated, and consideration of confounders is a realistic goal. Such measures are likely to improve study quality. PMID:25289261

Data Modeling Challenges of Advanced Interoperability.

PubMed

Blobel, Bernd; Oemig, Frank; Ruotsalainen, Pekka

2018-01-01

Progressive health paradigms, involving many different disciplines and combining multiple policy domains, requires advanced interoperability solutions. This results in special challenges for modeling health systems. The paper discusses classification systems for data models and enterprise business architectures and compares them with the ISO Reference Architecture. On that basis, existing definitions, specifications and standards of data models for interoperability are evaluated and their limitations are discussed. Amendments to correctly use those models and to better meet the aforementioned challenges are offered.

Classification of community types, successional sequences, and landscapes of the Copper River Delta, Alaska.

Treesearch

Keith. Boggs

2000-01-01

A classification of community types, successional sequences, and landscapes is presented for the piedmont of the Copper River Delta. The classification was based on a sampling of 471 sites. A total of 75 community types, 42 successional sequences, and 6 landscapes are described. The classification of community types reflects the existing vegetation communities on the...

A bioturbation classification of European marine infaunal invertebrates

PubMed Central

Queirós, Ana M; Birchenough, Silvana N R; Bremner, Julie; Godbold, Jasmin A; Parker, Ruth E; Romero-Ramirez, Alicia; Reiss, Henning; Solan, Martin; Somerfield, Paul J; Van Colen, Carl; Van Hoey, Gert; Widdicombe, Stephen

2013-01-01

Bioturbation, the biogenic modification of sediments through particle reworking and burrow ventilation, is a key mediator of many important geochemical processes in marine systems. In situ quantification of bioturbation can be achieved in a myriad of ways, requiring expert knowledge, technology, and resources not always available, and not feasible in some settings. Where dedicated research programmes do not exist, a practical alternative is the adoption of a trait-based approach to estimate community bioturbation potential (BPc). This index can be calculated from inventories of species, abundance and biomass data (routinely available for many systems), and a functional classification of organism traits associated with sediment mixing (less available). Presently, however, there is no agreed standard categorization for the reworking mode and mobility of benthic species. Based on information from the literature and expert opinion, we provide a functional classification for 1033 benthic invertebrate species from the northwest European continental shelf, as a tool to enable the standardized calculation of BPc in the region. Future uses of this classification table will increase the comparability and utility of large-scale assessments of ecosystem processes and functioning influenced by bioturbation (e.g., to support legislation). The key strengths, assumptions, and limitations of BPc as a metric are critically reviewed, offering guidelines for its calculation and application. PMID:24198953

Advanced Steel Microstructural Classification by Deep Learning Methods.

PubMed

Azimi, Seyed Majid; Britz, Dominik; Engstler, Michael; Fritz, Mario; Mücklich, Frank

2018-02-01

The inner structure of a material is called microstructure. It stores the genesis of a material and determines all its physical and chemical properties. While microstructural characterization is widely spread and well known, the microstructural classification is mostly done manually by human experts, which gives rise to uncertainties due to subjectivity. Since the microstructure could be a combination of different phases or constituents with complex substructures its automatic classification is very challenging and only a few prior studies exist. Prior works focused on designed and engineered features by experts and classified microstructures separately from the feature extraction step. Recently, Deep Learning methods have shown strong performance in vision applications by learning the features from data together with the classification step. In this work, we propose a Deep Learning method for microstructural classification in the examples of certain microstructural constituents of low carbon steel. This novel method employs pixel-wise segmentation via Fully Convolutional Neural Network (FCNN) accompanied by a max-voting scheme. Our system achieves 93.94% classification accuracy, drastically outperforming the state-of-the-art method of 48.89% accuracy. Beyond the strong performance of our method, this line of research offers a more robust and first of all objective way for the difficult task of steel quality appreciation.

The development of a classification schema for arts-based approaches to knowledge translation.

PubMed

Archibald, Mandy M; Caine, Vera; Scott, Shannon D

2014-10-01

Arts-based approaches to knowledge translation are emerging as powerful interprofessional strategies with potential to facilitate evidence uptake, communication, knowledge, attitude, and behavior change across healthcare provider and consumer groups. These strategies are in the early stages of development. To date, no classification system for arts-based knowledge translation exists, which limits development and understandings of effectiveness in evidence syntheses. We developed a classification schema of arts-based knowledge translation strategies based on two mechanisms by which these approaches function: (a) the degree of precision in key message delivery, and (b) the degree of end-user participation. We demonstrate how this classification is necessary to explore how context, time, and location shape arts-based knowledge translation strategies. Classifying arts-based knowledge translation strategies according to their core attributes extends understandings of the appropriateness of these approaches for various healthcare settings and provider groups. The classification schema developed may enhance understanding of how, where, and for whom arts-based knowledge translation approaches are effective, and enable theorizing of essential knowledge translation constructs, such as the influence of context, time, and location on utilization strategies. The classification schema developed may encourage systematic inquiry into the effectiveness of these approaches in diverse interprofessional contexts. © 2014 Sigma Theta Tau International.

Management of thoracolumbar spine trauma: An overview

PubMed Central

Rajasekaran, S; Kanna, Rishi Mugesh; Shetty, Ajoy Prasad

2015-01-01

Thoracolumbar spine fractures are common injuries that can result in significant disability, deformity and neurological deficit. Controversies exist regarding the appropriate radiological investigations, the indications for surgical management and the timing, approach and type of surgery. This review provides an overview of the epidemiology, biomechanical principles, radiological and clinical evaluation, classification and management principles. Literature review of all relevant articles published in PubMed covering thoracolumbar spine fractures with or without neurologic deficit was performed. The search terms used were thoracolumbar, thoracic, lumbar, fracture, trauma and management. All relevant articles and abstracts covering thoracolumbar spine fractures with and without neurologic deficit were reviewed. Biomechanically the thoracolumbar spine is predisposed to a higher incidence of spinal injuries. Computed tomography provides adequate bony detail for assessing spinal stability while magnetic resonance imaging shows injuries to soft tissues (posterior ligamentous complex [PLC]) and neurological structures. Different classification systems exist and the most recent is the AO spine knowledge forum classification of thoracolumbar trauma. Treatment includes both nonoperative and operative methods and selected based on the degree of bony injury, neurological involvement, presence of associated injuries and the integrity of the PLC. Significant advances in imaging have helped in the better understanding of thoracolumbar fractures, including information on canal morphology and injury to soft tissue structures. The ideal classification that is simple, comprehensive and guides management is still elusive. Involvement of three columns, progressive neurological deficit, significant kyphosis and canal compromise with neurological deficit are accepted indications for surgical stabilization through anterior, posterior or combined approaches. PMID:25593358

Dimensional approaches to psychiatric classification: refining the research agenda for DSM-V: an introduction.

PubMed

Regier, Darrel A

2007-01-01

The American Psychiatric Association (APA) will publish the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V), in 2012. This paper reviews the extended, multi-faceted research planning preparations that APA has undertaken, several in collaboration with the World Health Organization and the U.S. National Institutes of Health, to assess the current state of diagnosis-relevant research and to generate short- and long-term recommendations for research needed to enrich DSM-V and future psychiatric classifications. This research review and planning process has underscored widespread interest among nosologists in the US and globally regarding the potential benefits for research and clinical practice of incorporating a dimensional component into the existing categorical, or binary, classification system in the DSM. Toward this end, the APA and its partners convened an international conference in July 2006 to critically appraise the use of dimensional constructs in psychiatric diagnostic systems. Resultant papers appear in this issue of International Journal of Methods in Psychiatric Research and in a forthcoming monograph to be published by APA. Copyright (c) 2007 John Wiley & Sons, Ltd.

Academic Radiologist Subspecialty Identification Using a Novel Claims-Based Classification System.

PubMed

Rosenkrantz, Andrew B; Wang, Wenyi; Hughes, Danny R; Ginocchio, Luke A; Rosman, David A; Duszak, Richard

2017-06-01

The objective of the present study is to assess the feasibility of a novel claims-based classification system for payer identification of academic radiologist subspecialties. Using a categorization scheme based on the Neiman Imaging Types of Service (NITOS) system, we mapped the Medicare Part B services billed by all radiologists from 2012 to 2014, assigning them to the following subspecialty categories: abdominal imaging, breast imaging, cardiothoracic imaging, musculoskeletal imaging, nuclear medicine, interventional radiology, and neuroradiology. The percentage of subspecialty work relative value units (RVUs) to total billed work RVUs was calculated for each radiologist nationwide. For radiologists at the top 20 academic departments funded by the National Institutes of Health, those percentages were compared with subspecialties designated on faculty websites. NITOS-based subspecialty assignments were also compared with the only radiologist subspecialty classifications currently recognized by Medicare (i.e., nuclear medicine and interventional radiology). Of 1012 academic radiologists studied, the median percentage of Medicare-billed NITOS-based subspecialty work RVUs matching the subspecialty designated on radiologists' own websites ranged from 71.3% (for nuclear medicine) to 98.9% (for neuroradiology). A NITOS-based work RVU threshold of 50% correctly classified 89.8% of radiologists (5.9% were not mapped to any subspecialty; subspecialty error rate, 4.2%). In contrast, existing Medicare provider codes identified only 46.7% of nuclear medicine physicians and 39.4% of interventional radiologists. Using a framework based on a recently established imaging health services research tool that maps service codes based on imaging modality and body region, Medicare claims data can be used to consistently identify academic radiologists by subspecialty in a manner not possible with the use of existing Medicare physician specialty identifiers. This method may facilitate more appropriate performance metrics for subspecialty academic physicians under emerging value-based payment models.

Columbia River Estuary ecosystem classification—Concept and application

USGS Publications Warehouse

Simenstad, Charles A.; Burke, Jennifer L.; O'Connor, Jim E.; Cannon, Charles; Heatwole, Danelle W.; Ramirez, Mary F.; Waite, Ian R.; Counihan, Timothy D.; Jones, Krista L.

2011-01-01

This document describes the concept, organization, and application of a hierarchical ecosystem classification that integrates saline and tidal freshwater reaches of estuaries in order to characterize the ecosystems of large flood plain rivers that are strongly influenced by riverine and estuarine hydrology. We illustrate the classification by applying it to the Columbia River estuary (Oregon-Washington, USA), a system that extends about 233 river kilometers (rkm) inland from the Pacific Ocean. More than three-quarters of this length is tidal freshwater. The Columbia River Estuary Ecosystem Classification ("Classification") is based on six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. We define and map Levels 1-3 for the entire Columbia River estuary with existing geospatial datasets, and provide examples of Levels 4-6 for one hydrogeomorphic reach. In particular, three levels of the Classification capture the scales and categories of ecosystem structure and processes that are most tractable to estuarine research, monitoring, and management. These three levels are the (1) eight hydrogeomorphic reaches that embody the formative geologic and tectonic processes that created the existing estuarine landscape and encompass the influence of the resulting physiography on interactions between fluvial and tidal hydrology and geomorphology across 230 kilometers (km) of estuary, (2) more than 15 ecosystem complexes composed of broad landforms created predominantly by geologic processes during the Holocene, and (3) more than 25 geomorphic catenae embedded within ecosystem complexes that represent distinct geomorphic landforms, structures, ecosystems, and habitats, and components of the estuarine landscape most likely to change over short time periods.

Comparison of using single- or multi-polarimetric TerraSAR-X images for segmentation and classification of man-made maritime objects

NASA Astrophysics Data System (ADS)

Teutsch, Michael; Saur, Günter

2011-11-01

Spaceborne SAR imagery offers high capability for wide-ranging maritime surveillance especially in situations, where AIS (Automatic Identification System) data is not available. Therefore, maritime objects have to be detected and optional information such as size, orientation, or object/ship class is desired. In recent research work, we proposed a SAR processing chain consisting of pre-processing, detection, segmentation, and classification for single-polarimetric (HH) TerraSAR-X StripMap images to finally assign detection hypotheses to class "clutter", "non-ship", "unstructured ship", or "ship structure 1" (bulk carrier appearance) respectively "ship structure 2" (oil tanker appearance). In this work, we extend the existing processing chain and are now able to handle full-polarimetric (HH, HV, VH, VV) TerraSAR-X data. With the possibility of better noise suppression using the different polarizations, we slightly improve both the segmentation and the classification process. In several experiments we demonstrate the potential benefit for segmentation and classification. Precision of size and orientation estimation as well as correct classification rates are calculated individually for single- and quad-polarization and compared to each other.

Developing collaborative classifiers using an expert-based model

USGS Publications Warehouse

Mountrakis, G.; Watts, R.; Luo, L.; Wang, Jingyuan

2009-01-01

This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Application of remote sensing technology to the solution of problems in the management of resources in Indiana

NASA Technical Reports Server (NTRS)

Weismiller, R. A.; Mroczynski, R. P. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The Lydick, South Bend West, South Bend East, and Osceola quadrangles were successfully classified into twenty-six cover types with a high degree of accuracy. The ability of this computer-assisted classification system to delineate various stages of urban development, from heavy industry to new suburban development, was of particular interest to the planning commission. The classification is clearly more beneficial than the existing agricultural soils and topographic maps, because it shows the current ground cover conditions all on one map. It shows how an area is developing along with the specific type and location of new development. The classification also shows at a glance whether development is taking place in an area suitable for development or if growth is taking place in prime agricultural land, areas of poor foundation material, or other places where development is not desirable.

75 FR 47897 - Proposed Collection; Comment Request for Regulation Project

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-09

...-Classification (Section 301.7701-4). DATES: Written comments should be received on or before October 8, 2010 to...: Title: Environmental Settlement Funds-Classification. OMB Number: 1545-1465. Regulation Project Number... classification of trusts formed to collect and disburse amounts for environmental remediation of an existing...

Classification and definition of misuse, abuse, and related events in clinical trials: ACTTION systematic review and recommendations.

PubMed

Smith, Shannon M; Dart, Richard C; Katz, Nathaniel P; Paillard, Florence; Adams, Edgar H; Comer, Sandra D; Degroot, Aldemar; Edwards, Robert R; Haddox, J David; Jaffe, Jerome H; Jones, Christopher M; Kleber, Herbert D; Kopecky, Ernest A; Markman, John D; Montoya, Ivan D; O'Brien, Charles; Roland, Carl L; Stanton, Marsha; Strain, Eric C; Vorsanger, Gary; Wasan, Ajay D; Weiss, Roger D; Turk, Dennis C; Dworkin, Robert H

2013-11-01

As the nontherapeutic use of prescription medications escalates, serious associated consequences have also increased. This makes it essential to estimate misuse, abuse, and related events (MAREs) in the development and postmarketing adverse event surveillance and monitoring of prescription drugs accurately. However, classifications and definitions to describe prescription drug MAREs differ depending on the purpose of the classification system, may apply to single events or ongoing patterns of inappropriate use, and are not standardized or systematically employed, thereby complicating the ability to assess MARE occurrence adequately. In a systematic review of existing prescription drug MARE terminology and definitions from consensus efforts, review articles, and major institutions and agencies, MARE terms were often defined inconsistently or idiosyncratically, or had definitions that overlapped with other MARE terms. The Analgesic, Anesthetic, and Addiction Clinical Trials, Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership convened an expert panel to develop mutually exclusive and exhaustive consensus classifications and definitions of MAREs occurring in clinical trials of analgesic medications to increase accuracy and consistency in characterizing their occurrence and prevalence in clinical trials. The proposed ACTTION classifications and definitions are designed as a first step in a system to adjudicate MAREs that occur in analgesic clinical trials and postmarketing adverse event surveillance and monitoring, which can be used in conjunction with other methods of assessing a treatment's abuse potential. Copyright © 2013 International Association for the Study of Pain. All rights reserved.

Santa Ana Forecasting and Classification

NASA Astrophysics Data System (ADS)

Rolinski, T.; Eichhorn, D.; D'Agostino, B. J.; Vanderburg, S.; Means, J. D.

2011-12-01

Southern California experiences wildfires every year, but under certain circumstances these fires grow into extremely large and destructive fires, such as the Cedar Fire of 2003 and the Witch Fire of 2007. The Cedar Fire burned over 1100 km2 , destroyed more than 2200 homes and killed 15 people; the Witch fire burned more than 800 km2, destroyed more than 1000 homes and killed 2 people. Fires can quickly become too large and dangerous to fight if they are accompanied by a very strong "Santa Ana" condition, which is a foehn-like wind that may bring strong winds and very low humidities. However there is an entire range of specific weather conditions that fall into the broad category of Santa Anas, from cold and blustery to hot with very little wind. All types are characterized by clear skies and low humidity. Since the potential for destructive fire is dependent on the characteristics of Santa Anas, as well as the level of fuel moisture, there exists a need for further classification, such as is done with tropical cyclones and after-the-fact with tornadoes. We use surface data and fuel moisture combined with reanalysis to diagnose those conditions that result in Santa Anas with the greatest potential for destructive fires. We use this data to produce a new classification system for Santa Anas. This classification system should be useful for informing the relevant agencies for mitigation and response planning. In the future this same classification may be made available to the general public.

Elbow instability: Are we able to classify it? Review of the literature and proposal of an all-inclusive classification system.

PubMed

Marinelli, A; Guerra, E; Rotini, R

2016-12-01

In the recent years, considerable improvements have come in biomechanical knowledge about the role of elbow stabilizers. In particular, the complex interactions among the different stabilizers when injured at the same time have been better understood. Anyway, uncertainties about both nomenclature and classification still exist in the definition of the different patterns of instability. The authors examine the literature of the last 130 years about elbow instability classification, analyzing the intuitions and the value of each of them. However, because of the lack of a satisfactory classification, in 2015 a working group has been created inside SICSeG (Italian Society of Shoulder and Elbow Surgery) with the aim of defining an exhaustive classification as simple, complete and reproducible as possible. A new all-inclusive elbow instability classification is proposed. This classification considers two main parameters: timing (acute and chronic forms) and involved stabilizers (simple and complex forms), and four secondary parameters: etiology (traumatic, rheumatic, congenital…), the involved joint (radius and ulna as a single unit articulating with the humerus or the proximal radio-ulnar joint), the degree of displacement (dislocation or subluxation) and the mechanism of instability or dislocation (PLRI, PMRI, direct axial loading, pure varus or valgus stress). This classification is at the same time complete enough to include all the instability patterns and practical enough to be effectively used in the clinical practice. This classification can help in defining a shared language, can improve our understanding of the disorder, reduce misunderstanding of diagnosis and improve comparison among different case series.

Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomography.

PubMed

Jeong, Jeong-Won; Shin, Dae C; Do, Synho; Marmarelis, Vasilis Z

2006-08-01

This paper presents a novel segmentation methodology for automated classification and differentiation of soft tissues using multiband data obtained with the newly developed system of high-resolution ultrasonic transmission tomography (HUTT) for imaging biological organs. This methodology extends and combines two existing approaches: the L-level set active contour (AC) segmentation approach and the agglomerative hierarchical kappa-means approach for unsupervised clustering (UC). To prevent the trapping of the current iterative minimization AC algorithm in a local minimum, we introduce a multiresolution approach that applies the level set functions at successively increasing resolutions of the image data. The resulting AC clusters are subsequently rearranged by the UC algorithm that seeks the optimal set of clusters yielding the minimum within-cluster distances in the feature space. The presented results from Monte Carlo simulations and experimental animal-tissue data demonstrate that the proposed methodology outperforms other existing methods without depending on heuristic parameters and provides a reliable means for soft tissue differentiation in HUTT images.

Does NDPH exist? Some clinical considerations.

PubMed

Manzoni, G C; Torelli, P

2011-05-01

The analysis of case series of new daily persistent headache (NDPH) reported so far in the literature and the clinical evaluation of affected patients seen at headache clinics suggest that the current International Classification of Headache Disorders (ICHD-II) diagnostic criteria for NDPH are not adequate. In particular, in several instances headache features are not consistent with those of tension-type headache, as the ICHD-II expects. Before making a diagnosis of primary NDPH, it is imperative to rule out that it may be due to any underlying systemic disease. Just as importantly, the presence of psychiatric comorbidity and the possible role played by stressful life factors in triggering NDPH onset should also be searched for. Probably, it will only be through some future improvement in the classification of headache attributed to psychiatric disorder (chapter 12 of the ICHD-II) on the one hand, and through a careful psychological evaluation of patients currently diagnosed as NDPH sufferers on the other, that we will finally know whether primary NDPH actually exists.

Optic nerve coloboma, Dandy-Walker malformation, microglossia, tongue hamartomata, cleft palate and apneic spells: an existing oral-facial-digital syndrome or a new variant?

PubMed

Toriello, Helga V; Lemire, Edmond G

2002-01-01

We report on a female infant with postaxial polydactyly of the hands, preaxial polydactyly of the right foot, cleft palate, microglossia and tongue hamartomata consistent with an oral-facial-digital syndrome (OFDS). The patient also had optic nerve colobomata, a Dandy-Walker malformation, micrognathia and apneic spells. This combination of clinical features has not been previously reported. This patient either expands the clinical features of one of the existing OFDS or represents a new variant. A review of the literature highlights the difficulties in making a specific diagnosis because of the different classification systems that exist in the literature.

78 FR 32067 - User Fees for 2013 Crop Cotton Classification Services to Growers

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-29

... Fees for 2013 Crop Cotton Classification Services to Growers AGENCY: Agricultural Marketing Service... cotton producers for 2013 crop cotton classification services at $2.20 per bale--the same level as in 2012. Revenues resulting from this cotton classing fee and existing reserves are sufficient to cover...

29 CFR 4.51 - Prevailing in the locality determinations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... determination is made. Such information is most frequently derived from area surveys made by the Bureau of Labor... classification data, patterns existing between survey periods, and the way the separate classification data... mean may be used include situations where: (1) The number of workers studied for the job classification...

Gait recognition based on integral outline

NASA Astrophysics Data System (ADS)

Ming, Guan; Fang, Lv

2017-02-01

Biometric identification technology replaces traditional security technology, which has become a trend, and gait recognition also has become a hot spot of research because its feature is difficult to imitate and theft. This paper presents a gait recognition system based on integral outline of human body. The system has three important aspects: the preprocessing of gait image, feature extraction and classification. Finally, using a method of polling to evaluate the performance of the system, and summarizing the problems existing in the gait recognition and the direction of development in the future.

Is U.S. climatic diversity well represented within the existing federal protection network?

PubMed

Batllori, Enric; Miller, Carol; Parisien, Marc-Andre; Parks, Sean A; Moritz, Max A

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans. The conterminous United States of America (CONUS) has an extensive system of protected areas managed by federal agencies, but a comprehensive assessment of how this network represents CONUS climate is lacking. We present a quantitative classification of the climate space that is independent from the geographic locations to evaluate the climatic representation of the existing protected area network. We use this classification to evaluate the coverage of each agency's jurisdiction and to identify current conservation deficits. Our findings reveal that the existing network poorly represents CONUS climatic diversity. Although rare climates are generally well represented by the network, the most common climates are particularly underrepresented. Overall, 83% of the area of the CONUS corresponds to climates underrepresented by the network. The addition of some currently unprotected federal lands to the network would enhance the coverage of CONUS climates. However, to fully palliate current conservation deficits, large-scale private-land conservation initiatives will be critical.

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

Melanoma recognition framework based on expert definition of ABCD for dermoscopic images.

PubMed

Abbas, Qaisar; Emre Celebi, M; Garcia, Irene Fondón; Ahmad, Waqar

2013-02-01

Melanoma Recognition based on clinical ABCD rule is widely used for clinical diagnosis of pigmented skin lesions in dermoscopy images. However, the current computer-aided diagnostic (CAD) systems for classification between malignant and nevus lesions using the ABCD criteria are imperfect due to use of ineffective computerized techniques. In this study, a novel melanoma recognition system (MRS) is presented by focusing more on extracting features from the lesions using ABCD criteria. The complete MRS system consists of the following six major steps: transformation to the CIEL*a*b* color space, preprocessing to enhance the tumor region, black-frame and hair artifacts removal, tumor-area segmentation, quantification of feature using ABCD criteria and normalization, and finally feature selection and classification. The MRS system for melanoma-nevus lesions is tested on a total of 120 dermoscopic images. To test the performance of the MRS diagnostic classifier, the area under the receiver operating characteristics curve (AUC) is utilized. The proposed classifier achieved a sensitivity of 88.2%, specificity of 91.3%, and AUC of 0.880. The experimental results show that the proposed MRS system can accurately distinguish between malignant and benign lesions. The MRS technique is fully automatic and can easily integrate to an existing CAD system. To increase the classification accuracy of MRS, the CASH pattern recognition technique, visual inspection of dermatologist, contextual information from the patients, and the histopathological tests can be included to investigate the impact with this system. © 2012 John Wiley & Sons A/S.

A Classification of Mediterranean Cyclones Based on Global Analyses

NASA Technical Reports Server (NTRS)

Reale, Oreste; Atlas, Robert

2003-01-01

The Mediterranean Sea region is dominated by baroclinic and orographic cyclogenesis. However, previous work has demonstrated the existence of rare but intense subsynoptic-scale cyclones displaying remarkable similarities to tropical cyclones and polar lows, including, but not limited to, an eye-like feature in the satellite imagery. The terms polar low and tropical cyclone have been often used interchangeably when referring to small-scale, convective Mediterranean vortices and no definitive statement has been made so far on their nature, be it sub-tropical or polar. Moreover, most of the classifications of Mediterranean cyclones have neglected the small-scale convective vortices, focusing only on the larger-scale and far more common baroclinic cyclones. A classification of all Mediterranean cyclones based on operational global analyses is proposed The classification is based on normalized horizontal shear, vertical shear, scale, low versus mid-level vorticity, low-level temperature gradients, and sea surface temperatures. In the classification system there is a continuum of possible events, according to the increasing role of barotropic instability and decreasing role of baroclinic instability. One of the main results is that the Mediterranean tropical cyclone-like vortices and the Mediterranean polar lows appear to be different types of events, in spite of the apparent similarity of their satellite imagery. A consistent terminology is adopted, stating that tropical cyclone- like vortices are the less baroclinic of all, followed by polar lows, cold small-scale cyclones and finally baroclinic lee cyclones. This classification is based on all the cyclones which occurred in a four-year period (between 1996 and 1999). Four cyclones, selected among all the ones which developed during this time-frame, are analyzed. Particularly, the classification allows to discriminate between two cyclones (occurred in October 1996 and in March 1999) which both display a very well-defined eye-like feature in the satellite imagery. According to our classification system, the two events are dynamically different and can be categorized as being respectively a tropical cyclone-like vortex and well-developed polar low.

CARSVM: a class association rule-based classification framework and its application to gene expression data.

PubMed

Kianmehr, Keivan; Alhajj, Reda

2008-09-01

In this study, we aim at building a classification framework, namely the CARSVM model, which integrates association rule mining and support vector machine (SVM). The goal is to benefit from advantages of both, the discriminative knowledge represented by class association rules and the classification power of the SVM algorithm, to construct an efficient and accurate classifier model that improves the interpretability problem of SVM as a traditional machine learning technique and overcomes the efficiency issues of associative classification algorithms. In our proposed framework: instead of using the original training set, a set of rule-based feature vectors, which are generated based on the discriminative ability of class association rules over the training samples, are presented to the learning component of the SVM algorithm. We show that rule-based feature vectors present a high-qualified source of discrimination knowledge that can impact substantially the prediction power of SVM and associative classification techniques. They provide users with more conveniences in terms of understandability and interpretability as well. We have used four datasets from UCI ML repository to evaluate the performance of the developed system in comparison with five well-known existing classification methods. Because of the importance and popularity of gene expression analysis as real world application of the classification model, we present an extension of CARSVM combined with feature selection to be applied to gene expression data. Then, we describe how this combination will provide biologists with an efficient and understandable classifier model. The reported test results and their biological interpretation demonstrate the applicability, efficiency and effectiveness of the proposed model. From the results, it can be concluded that a considerable increase in classification accuracy can be obtained when the rule-based feature vectors are integrated in the learning process of the SVM algorithm. In the context of applicability, according to the results obtained from gene expression analysis, we can conclude that the CARSVM system can be utilized in a variety of real world applications with some adjustments.

Lameness detection in dairy cattle: single predictor v. multivariate analysis of image-based posture processing and behaviour and performance sensing.

PubMed

Van Hertem, T; Bahr, C; Schlageter Tello, A; Viazzi, S; Steensels, M; Romanini, C E B; Lokhorst, C; Maltz, E; Halachmi, I; Berckmans, D

2016-09-01

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Authentication of bee pollen grains in bright-field microscopy by combining one-class classification techniques and image processing.

PubMed

Chica, Manuel

2012-11-01

A novel method for authenticating pollen grains in bright-field microscopic images is presented in this work. The usage of this new method is clear in many application fields such as bee-keeping sector, where laboratory experts need to identify fraudulent bee pollen samples against local known pollen types. Our system is based on image processing and one-class classification to reject unknown pollen grain objects. The latter classification technique allows us to tackle the major difficulty of the problem, the existence of many possible fraudulent pollen types, and the impossibility of modeling all of them. Different one-class classification paradigms are compared to study the most suitable technique for solving the problem. In addition, feature selection algorithms are applied to reduce the complexity and increase the accuracy of the models. For each local pollen type, a one-class classifier is trained and aggregated into a multiclassifier model. This multiclassification scheme combines the output of all the one-class classifiers in a unique final response. The proposed method is validated by authenticating pollen grains belonging to different Spanish bee pollen types. The overall accuracy of the system on classifying fraudulent microscopic pollen grain objects is 92.3%. The system is able to rapidly reject pollen grains, which belong to nonlocal pollen types, reducing the laboratory work and effort. The number of possible applications of this authentication method in the microscopy research field is unlimited. Copyright © 2012 Wiley Periodicals, Inc.

A taxonomy has been developed for outcomes in medical research to help improve knowledge discovery.

PubMed

Dodd, Susanna; Clarke, Mike; Becker, Lorne; Mavergames, Chris; Fish, Rebecca; Williamson, Paula R

2018-04-01

There is increasing recognition that insufficient attention has been paid to the choice of outcomes measured in clinical trials. The lack of a standardized outcome classification system results in inconsistencies due to ambiguity and variation in how outcomes are described across different studies. Being able to classify by outcome would increase efficiency in searching sources such as clinical trial registries, patient registries, the Cochrane Database of Systematic Reviews, and the Core Outcome Measures in Effectiveness Trials (COMET) database of core outcome sets (COS), thus aiding knowledge discovery. A literature review was carried out to determine existing outcome classification systems, none of which were sufficiently comprehensive or granular for classification of all potential outcomes from clinical trials. A new taxonomy for outcome classification was developed, and as proof of principle, outcomes extracted from all published COS in the COMET database, selected Cochrane reviews, and clinical trial registry entries were classified using this new system. Application of this new taxonomy to COS in the COMET database revealed that 274/299 (92%) COS include at least one physiological outcome, whereas only 177 (59%) include at least one measure of impact (global quality of life or some measure of functioning) and only 105 (35%) made reference to adverse events. This outcome taxonomy will be used to annotate outcomes included in COS within the COMET database and is currently being piloted for use in Cochrane Reviews within the Cochrane Linked Data Project. Wider implementation of this standard taxonomy in trial and systematic review databases and registries will further promote efficient searching, reporting, and classification of trial outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Defining active sacroiliitis on MRI for classification of axial spondyloarthritis: update by the ASAS MRI working group.

PubMed

Lambert, Robert G W; Bakker, Pauline A C; van der Heijde, Désirée; Weber, Ulrich; Rudwaleit, Martin; Hermann, K G; Sieper, Joachim; Baraliakos, Xenofon; Bennett, Alex; Braun, Jürgen; Burgos-Vargas, Rubén; Dougados, Maxime; Pedersen, Susanne Juhl; Jurik, Anne Grethe; Maksymowych, Walter P; Marzo-Ortega, Helena; Østergaard, Mikkel; Poddubnyy, Denis; Reijnierse, Monique; van den Bosch, Filip; van der Horst-Bruinsma, Irene; Landewé, Robert

2016-11-01

To review and update the existing definition of a positive MRI for classification of axial spondyloarthritis (SpA). The Assessment in SpondyloArthritis International Society (ASAS) MRI working group conducted a consensus exercise to review the definition of a positive MRI for inclusion in the ASAS classification criteria of axial SpA. Existing definitions and new data relevant to the MRI diagnosis and classification of sacroiliitis and spondylitis in axial SpA, published since the ASAS definition first appeared in print in 2009, were reviewed and discussed. The precise wording of the existing definition was examined in detail and the data and a draft proposal were presented to and voted on by the ASAS membership. The clear presence of bone marrow oedema on MRI in subchondral bone is still considered to be the defining observation that determines the presence of active sacroiliitis. Structural damage lesions seen on MRI may contribute to a decision by the observer that inflammatory lesions are genuinely due to SpA but are not required to meet the definition. The existing definition was clarified adding guidelines and images to assist in the application of the definition. The definition of a positive MRI for classification of axial SpA should continue to primarily depend on the imaging features of 'active sacroiliitis' until more data are available regarding MRI features of structural damage in the sacroiliac joint and MRI features in the spine and their utility when used for classification purposes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Multi-label spacecraft electrical signal classification method based on DBN and random forest

PubMed Central

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data. PMID:28486479

Multi-label spacecraft electrical signal classification method based on DBN and random forest.

PubMed

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data.

Molecular Phylogeny of the Widely Distributed Marine Protists, Phaeodaria (Rhizaria, Cercozoa).

PubMed

Nakamura, Yasuhide; Imai, Ichiro; Yamaguchi, Atsushi; Tuji, Akihiro; Not, Fabrice; Suzuki, Noritoshi

2015-07-01

Phaeodarians are a group of widely distributed marine cercozoans. These plankton organisms can exhibit a large biomass in the environment and are supposed to play an important role in marine ecosystems and in material cycles in the ocean. Accurate knowledge of phaeodarian classification is thus necessary to better understand marine biology, however, phylogenetic information on Phaeodaria is limited. The present study analyzed 18S rDNA sequences encompassing all existing phaeodarian orders, to clarify their phylogenetic relationships and improve their taxonomic classification. The monophyly of Phaeodaria was confirmed and strongly supported by phylogenetic analysis with a larger data set than in previous studies. The phaeodarian clade contained 11 subclades which generally did not correspond to the families and orders of the current classification system. Two families (Challengeriidae and Aulosphaeridae) and two orders (Phaeogromida and Phaeocalpida) are possibly polyphyletic or paraphyletic, and consequently the classification needs to be revised at both the family and order levels by integrative taxonomy approaches. Two morphological criteria, 1) the scleracoma type and 2) its surface structure, could be useful markers at the family level. Copyright © 2015 Elsevier GmbH. All rights reserved.

International Asteroid Mission (IAM)

NASA Astrophysics Data System (ADS)

Yamaguchi, Ryuuji

1991-07-01

International Asteroid Mission (IAM) is a program aimed at developing resources of asteroids abundantly existing near the earth. This report describes the research results of design project of the International Space University (ISU) held in 1990 at Tront-York University. ISU research and asteroid survey results, and the manned asteroid mining mission are outlined. Classification of asteroids existing near the earth and asteroid resource processing and use analyses are conducted. Asteroid selection flow charts are introduced, and the 1982HR-Orpheus is selected as a candidate asteroid because it takes an approaching orbit toward the earth, requires small delta V, and possesses abundant carbonaceous chondrites. Characteristics of 1982HR-Orpheus are presented. Mission requirements, mission outlines, transportation systems, and mining and processing systems for manned asteroid mining missions are presented.

The Utility and Challenges of Using ICD Codes in Child Maltreatment Research: A Review of Existing Literature

ERIC Educational Resources Information Center

Scott, Debbie; Tonmyr, Lil; Fraser, Jenny; Walker, Sue; McKenzie, Kirsten

2009-01-01

Objective: The objectives of this article are to explore the extent to which the International Statistical Classification of Diseases and Related Health Problems (ICD) has been used in child abuse research, to describe how the ICD system has been applied, and to assess factors affecting the reliability of ICD coded data in child abuse research.…

A Classification System for Navy Teams. Volume I. Technical Report.

DTIC Science & Technology

1981-09-01

studies are summarized in the following manner: 1. Democratic leadership yields more and better productivity than laissez-faire leadership. 2. Autocratic...leadership yields better short-term productivity, while democratic leadership obtains better long-term product- ivity, with consistently better...quality of output in demo- cratic leadership groups. 3. Less absenteeism and fewer dropouts exist under democratic leadership . 4. The absence of the leader

Integration of Landscape Ecosystem Classification and Historic Land Records in the Francis Marion National Forest

Treesearch

Peter U. Kennedy; Victor B. Shelburne

2002-01-01

Geographic Information Systems (GIS) data and historical plats ranging from 1716 to 1894 in the Coastal Flatwoods Region of South Carolina were used to quantify changes on a temporal scale. Combining the historic plats and associated witness trees (trees marking the boundaries of historic plats) with an existing database of the soils and other attributes was the basis...

Final Report on an Analysis of the Education and Training Systems at Milan, Michigan and Terre Haute, Indiana to Federal Prison Industries Incorporated, U.S. Department of Justice.

ERIC Educational Resources Information Center

Hitt, William D.; And Others

Existing education and training (E&T) programs at the Terre Haute Penitentiary, Indiana, and the Milan Federal Correctional Institution, Michigan, were described and evaluated. Needs, objectives, inmate classification and placement, staff, and other aspects were covered. Reports, staff and inmate interviews, study of instructional materials, and…

Postprocessing classification images

NASA Technical Reports Server (NTRS)

Kan, E. P.

1979-01-01

Program cleans up remote-sensing maps. It can be used with existing image-processing software. Remapped images closely resemble familiar resource information maps and can replace or supplement classification images not postprocessed by this program.

Evaluation of change detection techniques for monitoring coastal zone environments

NASA Technical Reports Server (NTRS)

Weismiller, R. A. (Principal Investigator); Kristof, S. J.; Scholz, D. K.; Anuta, P. E.; Momin, S. M.

1977-01-01

The author has identified the following significant results. Four change detection techniques were designed and implemented for evaluation: (1) post classification comparison change detection, (2) delta data change detection, (3) spectral/temporal change classification, and (4) layered spectral/temporal change classification. The post classification comparison technique reliably identified areas of change and was used as the standard for qualitatively evaluating the other three techniques. The layered spectral/temporal change classification and the delta data change detection results generally agreed with the post classification comparison technique results; however, many small areas of change were not identified. Major discrepancies existed between the post classification comparison and spectral/temporal change detection results.

Taxonomy for Common-Cause Failure Vulnerability and Mitigation

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

Wood, Richard Thomas; Korsah, Kofi; Mullens, James Allen

2015-09-01

Applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The potential for CCF vulnerability inhibits I&C modernization, thereby challenging the long-term sustainability of existing plants. For new plants and advanced reactor concepts, concern about CCF vulnerability in highly integrated digital I&C systems imposes a design burden that results in higher costs and increased complexity. The regulatory uncertainty in determining which mitigation strategies will be acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutionsmore » devised for existing plants. To address the conditions that constrain the transition to digital I&C technology by the US nuclear industry, crosscutting research is needed to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for nuclear power plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is investigating mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive basis to qualify digital technology for nuclear power applications. This report documents the development of a CCF taxonomy. The basis for the CCF taxonomy was generated by determining consistent terminology and establishing a classification approach. The terminology is based on definitions from standards, guides, and relevant nuclear power industry technical reports. The classification approach is derived from identified classification schemes focused on I&C systems and key characteristics, including failure modes. The CCF taxonomy provides the basis for a systematic organization of key systems aspects relevant to analyzing the potential for CCF vulnerability and the suitability of mitigation techniques. Development of an effective CCF taxonomy will help to provide a framework for establishing the objective analysis and assessment capabilities desired to facilitate rigorous identification of fault types and triggers that are the fundamental elements of CCF.« less

Optimal Representation of Anuran Call Spectrum in Environmental Monitoring Systems Using Wireless Sensor Networks.

PubMed

Luque, Amalia; Gómez-Bellido, Jesús; Carrasco, Alejandro; Barbancho, Julio

2018-06-03

The analysis and classification of the sounds produced by certain animal species, notably anurans, have revealed these amphibians to be a potentially strong indicator of temperature fluctuations and therefore of the existence of climate change. Environmental monitoring systems using Wireless Sensor Networks are therefore of interest to obtain indicators of global warming. For the automatic classification of the sounds recorded on such systems, the proper representation of the sound spectrum is essential since it contains the information required for cataloguing anuran calls. The present paper focuses on this process of feature extraction by exploring three alternatives: the standardized MPEG-7, the Filter Bank Energy (FBE), and the Mel Frequency Cepstral Coefficients (MFCC). Moreover, various values for every option in the extraction of spectrum features have been considered. Throughout the paper, it is shown that representing the frame spectrum with pure FBE offers slightly worse results than using the MPEG-7 features. This performance can easily be increased, however, by rescaling the FBE in a double dimension: vertically, by taking the logarithm of the energies; and, horizontally, by applying mel scaling in the filter banks. On the other hand, representing the spectrum in the cepstral domain, as in MFCC, has shown additional marginal improvements in classification performance.

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

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

Wang, Felix; Quach, Tu-Thach; Wheeler, Jason

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used tomore » reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.« less

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

DOE PAGES

Wang, Felix; Quach, Tu-Thach; Wheeler, Jason; ...

2018-04-05

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used tomore » reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.« less

Development of Single-Channel Hybrid BCI System Using Motor Imagery and SSVEP.

PubMed

Ko, Li-Wei; Ranga, S S K; Komarov, Oleksii; Chen, Chung-Chiang

2017-01-01

Numerous EEG-based brain-computer interface (BCI) systems that are being developed focus on novel feature extraction algorithms, classification methods and combining existing approaches to create hybrid BCIs. Several recent studies demonstrated various advantages of hybrid BCI systems in terms of an improved accuracy or number of commands available for the user. But still, BCI systems are far from realization for daily use. Having high performance with less number of channels is one of the challenging issues that persists, especially with hybrid BCI systems, where multiple channels are necessary to record information from two or more EEG signal components. Therefore, this work proposes a single-channel (C3 or C4) hybrid BCI system that combines motor imagery (MI) and steady-state visually evoked potential (SSVEP) approaches. This study demonstrates that besides MI features, SSVEP features can also be captured from C3 or C4 channel. The results show that due to rich feature information (MI and SSVEP) at these channels, the proposed hybrid BCI system outperforms both MI- and SSVEP-based systems having an average classification accuracy of 85.6 ± 7.7% in a two-class task.

A Complex Network Perspective on Clinical Science

PubMed Central

Hofmann, Stefan G.; Curtiss, Joshua; McNally, Richard J.

2016-01-01

Contemporary classification systems for mental disorders assume that abnormal behaviors are expressions of latent disease entities. An alternative to the latent disease model is the complex network approach. Instead of assuming that symptoms arise from an underlying disease entity, the complex network approach holds that disorders exist as systems of interrelated elements of a network. This approach also provides a framework for the understanding of therapeutic change. Depending on the structure of the network, change can occur abruptly once the network reaches a critical threshold (the tipping point). Homogeneous and highly connected networks often recover more slowly from local perturbations when the network approaches the tipping point, allowing for the possibility to predict treatment change, relapse, and recovery. In this article we discuss the complex network approach as an alternative to the latent disease model, and we discuss its implications for classification, therapy, relapse, and recovery. PMID:27694457

Computer vision-based classification of hand grip variations in neurorehabilitation.

PubMed

Zariffa, José; Steeves, John D

2011-01-01

The complexity of hand function is such that most existing upper limb rehabilitation robotic devices use only simplified hand interfaces. This is in contrast to the importance of the hand in regaining function after neurological injury. Computer vision technology has been used to identify hand posture in the field of Human Computer Interaction, but this approach has not been translated to the rehabilitation context. We describe a computer vision-based classifier that can be used to discriminate rehabilitation-relevant hand postures, and could be integrated into a virtual reality-based upper limb rehabilitation system. The proposed system was tested on a set of video recordings from able-bodied individuals performing cylindrical grasps, lateral key grips, and tip-to-tip pinches. The overall classification success rate was 91.2%, and was above 98% for 6 out of the 10 subjects. © 2011 IEEE

Heterogeneous but “Standard” Coding Systems for Adverse Events: Issues in Achieving Interoperability between Apples and Oranges

PubMed Central

Richesson, Rachel L.; Fung, Kin Wah; Krischer, Jeffrey P.

2008-01-01

Monitoring adverse events (AEs) is an important part of clinical research and a crucial target for data standards. The representation of adverse events themselves requires the use of controlled vocabularies with thousands of needed clinical concepts. Several data standards for adverse events currently exist, each with a strong user base. The structure and features of these current adverse event data standards (including terminologies and classifications) are different, so comparisons and evaluations are not straightforward, nor are strategies for their harmonization. Three different data standards - the Medical Dictionary for Regulatory Activities (MedDRA) and the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) terminologies, and Common Terminology Criteria for Adverse Events (CTCAE) classification - are explored as candidate representations for AEs. This paper describes the structural features of each coding system, their content and relationship to the Unified Medical Language System (UMLS), and unsettled issues for future interoperability of these standards. PMID:18406213

Groundwater dynamics converted to a groundwater classification as a tool for nature development programs in the dunes

NASA Astrophysics Data System (ADS)

Martens, Kristine; Van Camp, Marc; Van Damme, Dirk; Walraevens, Kristine

2013-08-01

Within the European Union, Habitat Directives are developed with the aim of restoration and preservation of endangered species. The level of biodiversity in coastal dune systems is generally very high compared to other natural ecosystems, but suffers from deterioration. Groundwater extraction and urbanisation are the main reasons for the decrease in biodiversity. Many restoration actions are being carried out and are focusing on the restoration of groundwater level with the aim of re-establishing rare species. These actions have different degrees of success. The evaluation of the actions is mainly based on the appearance of red list species. The groundwater classes, developed in the Netherlands, are used for the evaluation of opportunities for vegetation, while the natural variability of the groundwater level and quality are under-estimated. Vegetation is used as a seepage indicator. The existing classification is not valid in the Belgian dunes, as the vegetation observed in the study area is not in correspondence with this classification. Therefore, a new classification is needed. The new classification is based on the variability of the groundwater level on a long term with integration of ecological factors. Based on the new classification, the importance of seasonal and inter-yearly fluctuations of the water table can be deduced. Inter-yearly fluctuations are more important in recharge areas while seasonal fluctuations are dominant in discharge areas. The new classification opens opportunities for relating vegetation and groundwater dynamics.

Hydrologic classification of rivers based on cluster analysis of dimensionless hydrologic signatures: Applications for environmental instream flows

NASA Astrophysics Data System (ADS)

Praskievicz, S. J.; Luo, C.

2017-12-01

Classification of rivers is useful for a variety of purposes, such as generating and testing hypotheses about watershed controls on hydrology, predicting hydrologic variables for ungaged rivers, and setting goals for river management. In this research, we present a bottom-up (based on machine learning) river classification designed to investigate the underlying physical processes governing rivers' hydrologic regimes. The classification was developed for the entire state of Alabama, based on 248 United States Geological Survey (USGS) stream gages that met criteria for length and completeness of records. Five dimensionless hydrologic signatures were derived for each gage: slope of the flow duration curve (indicator of flow variability), baseflow index (ratio of baseflow to average streamflow), rising limb density (number of rising limbs per unit time), runoff ratio (ratio of long-term average streamflow to long-term average precipitation), and streamflow elasticity (sensitivity of streamflow to precipitation). We used a Bayesian clustering algorithm to classify the gages, based on the five hydrologic signatures, into distinct hydrologic regimes. We then used classification and regression trees (CART) to predict each gaged river's membership in different hydrologic regimes based on climatic and watershed variables. Using existing geospatial data, we applied the CART analysis to classify ungaged streams in Alabama, with the National Hydrography Dataset Plus (NHDPlus) catchment (average area 3 km2) as the unit of classification. The results of the classification can be used for meeting management and conservation objectives in Alabama, such as developing statewide standards for environmental instream flows. Such hydrologic classification approaches are promising for contributing to process-based understanding of river systems.

Climate Classification is an Important Factor in ­Assessing Hospital Performance Metrics

NASA Astrophysics Data System (ADS)

Boland, M. R.; Parhi, P.; Gentine, P.; Tatonetti, N. P.

2017-12-01

Context/Purpose: Climate is a known modulator of disease, but its impact on hospital performance metrics remains unstudied. Methods: We assess the relationship between Köppen-Geiger climate classification and hospital performance metrics, specifically 30-day mortality, as reported in Hospital Compare, and collected for the period July 2013 through June 2014 (7/1/2013 - 06/30/2014). A hospital-level multivariate linear regression analysis was performed while controlling for known socioeconomic factors to explore the relationship between all-cause mortality and climate. Hospital performance scores were obtained from 4,524 hospitals belonging to 15 distinct Köppen-Geiger climates and 2,373 unique counties. Results: Model results revealed that hospital performance metrics for mortality showed significant climate dependence (p<0.001) after adjusting for socioeconomic factors. Interpretation: Currently, hospitals are reimbursed by Governmental agencies using 30-day mortality rates along with 30-day readmission rates. These metrics allow Government agencies to rank hospitals according to their `performance' along these metrics. Various socioeconomic factors are taken into consideration when determining individual hospitals performance. However, no climate-based adjustment is made within the existing framework. Our results indicate that climate-based variability in 30-day mortality rates does exist even after socioeconomic confounder adjustment. Use of standardized high-level climate classification systems (such as Koppen-Geiger) would be useful to incorporate in future metrics. Conclusion: Climate is a significant factor in evaluating hospital 30-day mortality rates. These results demonstrate that climate classification is an important factor when comparing hospital performance across the United States.

A real-time heat strain risk classifier using heart rate and skin temperature.

PubMed

Buller, Mark J; Latzka, William A; Yokota, Miyo; Tharion, William J; Moran, Daniel S

2008-12-01

Heat injury is a real concern to workers engaged in physically demanding tasks in high heat strain environments. Several real-time physiological monitoring systems exist that can provide indices of heat strain, e.g. physiological strain index (PSI), and provide alerts to medical personnel. However, these systems depend on core temperature measurement using expensive, ingestible thermometer pills. Seeking a better solution, we suggest the use of a model which can identify the probability that individuals are 'at risk' from heat injury using non-invasive measures. The intent is for the system to identify individuals who need monitoring more closely or who should apply heat strain mitigation strategies. We generated a model that can identify 'at risk' (PSI 7.5) workers from measures of heart rate and chest skin temperature. The model was built using data from six previously published exercise studies in which some subjects wore chemical protective equipment. The model has an overall classification error rate of 10% with one false negative error (2.7%), and outperforms an earlier model and a least squares regression model with classification errors of 21% and 14%, respectively. Additionally, the model allows the classification criteria to be adjusted based on the task and acceptable level of risk. We conclude that the model could be a valuable part of a multi-faceted heat strain management system.

A new EMI system for detection and classification of challenging targets

NASA Astrophysics Data System (ADS)

Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.

2013-06-01

Advanced electromagnetic induction (EMI) sensors currently feature multi-axis illumination of targets and tri-axial vector sensing (e.g., MetalMapper), or exploit multi-static array data acquisition (e.g., TEMTADS). They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance relative to the previous generation of single-axis, monostatic sensors. However, these advances yet have to improve significantly our ability to classify small, deep, and otherwise challenging targets. Particularly, recent live-site discrimination studies at Camp Butner, NC and Camp Beale, CA have revealed that it is more challenging to detect and discriminate small munitions (with calibers ranging from 20 mm to 60 mm) than larger ones. In addition, a live-site test at the Massachusetts Military Reservation, MA highlighted the difficulties for current sensors to classify large, deep, and overlapping targets with high confidence. There are two main approaches to overcome these problems: 1) adapt advanced EMI models to the existing systems and 2) improve the detection limits of current sensors by modifying their hardware. In this paper we demonstrate a combined software/hardware approach that will provide extended detection range and spatial resolution to next-generation EMI systems; we analyze and invert EMI data to extract classification features for small and deep targets; and we propose a new system that features a large transmitter coil.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Building the United States National Vegetation Classification

USGS Publications Warehouse

Franklin, S.B.; Faber-Langendoen, D.; Jennings, M.; Keeler-Wolf, T.; Loucks, O.; Peet, R.; Roberts, D.; McKerrow, A.

2012-01-01

The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.

Ecoregions as a level of ecological analysis

USGS Publications Warehouse

Wright, R.G.; Murray, M.P.; Merrill, T.

1998-01-01

There have been many attempts to classify geographic areas into zones of similar characteristics. Recent focus has been on ecoregions. We examined how well the boundaries of the most commonly used ecoregion classifications for the US matched the boundaries of existing vegetation cover mapped at three levels of classification, fine, mid- and coarse scale. We analyzed ecoregions in Idaho, Oregon and Washington. The results were similar among the two ecoregion classifications. For both ecoregion delineations and all three vegetation classifications, the patterns of existing vegetation did not correspond well with the patterns of ecoregions. Most vegetation types had a small proportion of their total area in a given ecoregion. There was also no dominance by one or more vegetation types in any ecoregion and contrary to our hypothesis, the level of congruence of vegetation patterns with ecoregion boundaries decreased as the level of classification became more general. The implications of these findings on the use of ecoregions as a planning tool and in the development of land conservation efforts are discussed.

Physiotherapy movement based classification approaches to low back pain: comparison of subgroups through review and developer/expert survey.

PubMed

Karayannis, Nicholas V; Jull, Gwendolen A; Hodges, Paul W

2012-02-20

Several classification schemes, each with its own philosophy and categorizing method, subgroup low back pain (LBP) patients with the intent to guide treatment. Physiotherapy derived schemes usually have a movement impairment focus, but the extent to which other biological, psychological, and social factors of pain are encompassed requires exploration. Furthermore, within the prevailing 'biological' domain, the overlap of subgrouping strategies within the orthopaedic examination remains unexplored. The aim of this study was "to review and clarify through developer/expert survey, the theoretical basis and content of physical movement classification schemes, determine their relative reliability and similarities/differences, and to consider the extent of incorporation of the bio-psycho-social framework within the schemes". A database search for relevant articles related to LBP and subgrouping or classification was conducted. Five dominant movement-based schemes were identified: Mechanical Diagnosis and Treatment (MDT), Treatment Based Classification (TBC), Pathoanatomic Based Classification (PBC), Movement System Impairment Classification (MSI), and O'Sullivan Classification System (OCS) schemes. Data were extracted and a survey sent to the classification scheme developers/experts to clarify operational criteria, reliability, decision-making, and converging/diverging elements between schemes. Survey results were integrated into the review and approval obtained for accuracy. Considerable diversity exists between schemes in how movement informs subgrouping and in the consideration of broader neurosensory, cognitive, emotional, and behavioural dimensions of LBP. Despite differences in assessment philosophy, a common element lies in their objective to identify a movement pattern related to a pain reduction strategy. Two dominant movement paradigms emerge: (i) loading strategies (MDT, TBC, PBC) aimed at eliciting a phenomenon of centralisation of symptoms; and (ii) modified movement strategies (MSI, OCS) targeted towards documenting the movement impairments associated with the pain state. Schemes vary on: the extent to which loading strategies are pursued; the assessment of movement dysfunction; and advocated treatment approaches. A biomechanical assessment predominates in the majority of schemes (MDT, PBC, MSI), certain psychosocial aspects (fear-avoidance) are considered in the TBC scheme, certain neurophysiologic (central versus peripherally mediated pain states) and psychosocial (cognitive and behavioural) aspects are considered in the OCS scheme.

Design and update of a classification system: the UCSD map of science.

PubMed

Börner, Katy; Klavans, Richard; Patek, Michael; Zoss, Angela M; Biberstine, Joseph R; Light, Robert P; Larivière, Vincent; Boyack, Kevin W

2012-01-01

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier's Scopus (about 15,000 source titles, 2001-2005) and Thomson Reuters' Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001-2004)-about 16,000 unique source titles. The updated map and classification adds six years (2005-2010) of WoS data and three years (2006-2008) from Scopus to the existing category structure-increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others.

Design and Update of a Classification System: The UCSD Map of Science

PubMed Central

Börner, Katy; Klavans, Richard; Patek, Michael; Zoss, Angela M.; Biberstine, Joseph R.; Light, Robert P.; Larivière, Vincent; Boyack, Kevin W.

2012-01-01

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier’s Scopus (about 15,000 source titles, 2001–2005) and Thomson Reuters’ Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001–2004)–about 16,000 unique source titles. The updated map and classification adds six years (2005–2010) of WoS data and three years (2006–2008) from Scopus to the existing category structure–increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others. PMID:22808037

Evaluating terrain based criteria for snow avalanche exposure ratings using GIS

NASA Astrophysics Data System (ADS)

Delparte, Donna; Jamieson, Bruce; Waters, Nigel

2010-05-01

Snow avalanche terrain in backcountry regions of Canada is increasingly being assessed based upon the Avalanche Terrain Exposure Scale (ATES). ATES is a terrain based classification introduced in 2004 by Parks Canada to identify "simple", "challenging" and "complex" backcountry areas. The ATES rating system has been applied to well over 200 backcountry routes, has been used in guidebooks, trailhead signs and maps and is part of the trip planning component of the AVALUATOR™, a simple decision-support tool for backcountry users. Geographic Information Systems (GIS) offers a means to model and visualize terrain based criteria through the use of digital elevation model (DEM) and land cover data. Primary topographic variables such as slope, aspect and curvature are easily derived from a DEM and are compatible with the equivalent evaluation criteria in ATES. Other components of the ATES classification are difficult to extract from a DEM as they are not strictly terrain based. An overview is provided of the terrain variables that can be generated from DEM and land cover data; criteria from ATES which are not clearly terrain based are identified for further study or revision. The second component of this investigation was the development of an algorithm for inputting suitable ATES criteria into a GIS, thereby mimicking the process avalanche experts use when applying the ATES classification to snow avalanche terrain. GIS based classifications were compared to existing expert assessments for validity. The advantage of automating the ATES classification process through GIS is to assist avalanche experts with categorizing and mapping remote backcountry terrain.

Advances in algorithm fusion for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-11-01

Along with other sensors, the Navy uses high-resolution sonar to detect and classify sea mines in mine-hunting operations. Scientists and engineers have devoted substantial effort to the development of automated detection and classification (D/C) algorithms for these high-resolution systems. Several factors spurred these efforts, including: (1) aids for operators to reduce work overload; (2) more optimal use of all available data; and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and manmade clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms (Algorithm Fusion) have been studied. To date, the results have been remarkable, including reliable robustness to new environments. In this paper a brief history of existing Algorithm Fusion technology and some techniques recently used to improve performance are presented. An exploration of new developments is presented in conclusion.

Musculoskeletal manifestations of systemic lupus erythmatosus.

PubMed

Mahmoud, Khaled; Zayat, Ahmed; Vital, Edward M

2017-09-01

Imaging studies suggest potential changes to the classification and assessment of inflammatory musculoskeletal lupus. This is important because of the burden of disease but the potential for new targeted therapies. Using our current classification and treatment, musculoskeletal symptoms continue to impact significantly on quality of life and work disability. Ultrasound and MRI studies suggested that new approaches to the diagnosis, classification, and evaluation of these symptoms are needed. Many patients with pain but no synovitis have ultrasound-proven joint and tendon inflammation but would not qualify for clinical trials or score highly on disease activity instruments. MRI studies show that erosions are more common than previously thought and may have a different pathogenesis than RA. Immunology studies suggest differences from other autoimmune synovitis, with a complex role for type I interferons. A wide range of biologic therapies appear more consistently effective for arthritis than some other manifestations. Changes to the selection of patients for therapy and stratification using musculoskeletal imaging may offer new approaches to clinical trials and the routine care of systemic lupus erythematosus patients with inflammatory musculoskeletal symptoms. Outcomes may thereby be improved using existing therapies. There are significant knowledge gaps that must be addressed to achieve these potential improved outcomes.

[Assessment of geriatric patients' care needs based on sosia classification: the reality of the lombardy region in nursing home.

PubMed

Vanalli, Mariangela

2016-11-01

The increased demand to care that originates from demographic changes called in Italy a rapid development in Nursing Home with particular emergency the problem of programme the welfare response. It is essential the development of a classification system able to describe the stratification of the case mix on the basis of the care requirements, allowing a remuneration in function of the complexity care. Since 2003, the Lombardy region has introduced a case-mix reimbursement system for nursing homes based on the SOSIA form which classifies residents into eight classes of frailty. In the present study the agreement between SOSIA classification and other well documented instruments, including Barthel Index, Mini-Mental State Examination on the basis of three indicators (mobility, cognition, comorbidity) is evaluated in eight classes of frailty. However, it is not any research project was published in order to assess the agreement between SOSIA classification and other measuring instruments. Although various methods exist by which researchers have attempted to measure the need for nursing care, there is no nationally accepted system for determining the total amount of registered nursing resources required by residents in long-term care. The aim of this study was to evaluate the correlation between SOSIA and filing systems widely used, such as the degree of Barthel disability rating scale, the Mini-Mental State Examination to offer care appropriate for the case-mix. Only the higher complexity care has classified in the first two classes, while the remaining levels has categorized in the lowest paid. Misclassification therefore induces an underestimation of the real care needs and, consequently, inadequate remuneration.

Automatic Line Calling Badminton System

NASA Astrophysics Data System (ADS)

Affandi Saidi, Syahrul; Adawiyah Zulkiplee, Nurabeahtul; Muhammad, Nazmizan; Sarip, Mohd Sharizan Md

2018-05-01

A system and relevant method are described to detect whether a projectile impact occurs on one side of a boundary line or the other. The system employs the use of force sensing resistor-based sensors that may be designed in segments or assemblies and linked to a mechanism with a display. An impact classification system is provided for distinguishing between various events, including a footstep, ball impact and tennis racquet contact. A sensor monitoring system is provided for determining the condition of sensors and providing an error indication if sensor problems exist. A service detection system is provided when the system is used for tennis that permits activation of selected groups of sensors and deactivation of others.

Utilizing feedback in adaptive SAR ATR systems

NASA Astrophysics Data System (ADS)

Horsfield, Owen; Blacknell, David

2009-05-01

Existing SAR ATR systems are usually trained off-line with samples of target imagery or CAD models, prior to conducting a mission. If the training data is not representative of mission conditions, then poor performance may result. In addition, it is difficult to acquire suitable training data for the many target types of interest. The Adaptive SAR ATR Problem Set (AdaptSAPS) program provides a MATLAB framework and image database for developing systems that adapt to mission conditions, meaning less reliance on accurate training data. A key function of an adaptive system is the ability to utilise truth feedback to improve performance, and it is this feature which AdaptSAPS is intended to exploit. This paper presents a new method for SAR ATR that does not use training data, based on supervised learning. This is achieved by using feature-based classification, and several new shadow features have been developed for this purpose. These features allow discrimination of vehicles from clutter, and classification of vehicles into two classes: targets, comprising military combat types, and non-targets, comprising bulldozers and trucks. The performance of the system is assessed using three baseline missions provided with AdaptSAPS, as well as three additional missions. All performance metrics indicate a distinct learning trend over the course of a mission, with most third and fourth quartile performance levels exceeding 85% correct classification. It has been demonstrated that these performance levels can be maintained even when truth feedback rates are reduced by up to 55% over the course of a mission.

Ecosystem services classification: A systems ecology perspective of the cascade framework.

PubMed

La Notte, Alessandra; D'Amato, Dalia; Mäkinen, Hanna; Paracchini, Maria Luisa; Liquete, Camino; Egoh, Benis; Geneletti, Davide; Crossman, Neville D

2017-03-01

Ecosystem services research faces several challenges stemming from the plurality of interpretations of classifications and terminologies. In this paper we identify two main challenges with current ecosystem services classification systems: i) the inconsistency across concepts, terminology and definitions, and; ii) the mix up of processes and end-state benefits, or flows and assets. Although different ecosystem service definitions and interpretations can be valuable for enriching the research landscape, it is necessary to address the existing ambiguity to improve comparability among ecosystem-service-based approaches. Using the cascade framework as a reference, and Systems Ecology as a theoretical underpinning, we aim to address the ambiguity across typologies. The cascade framework links ecological processes with elements of human well-being following a pattern similar to a production chain. Systems Ecology is a long-established discipline which provides insight into complex relationships between people and the environment. We present a refreshed conceptualization of ecosystem services which can support ecosystem service assessment techniques and measurement. We combine the notions of biomass, information and interaction from system ecology, with the ecosystem services conceptualization to improve definitions and clarify terminology. We argue that ecosystem services should be defined as the interactions (i.e. processes) of the ecosystem that produce a change in human well-being, while ecosystem components or goods, i.e. countable as biomass units, are only proxies in the assessment of such changes. Furthermore, Systems Ecology can support a re-interpretation of the ecosystem services conceptualization and related applied research, where more emphasis is needed on the underpinning complexity of the ecological system.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Generalized implementation of software safety policies

NASA Technical Reports Server (NTRS)

Knight, John C.; Wika, Kevin G.

1994-01-01

As part of a research program in the engineering of software for safety-critical systems, we are performing two case studies. The first case study, which is well underway, is a safety-critical medical application. The second, which is just starting, is a digital control system for a nuclear research reactor. Our goal is to use these case studies to permit us to obtain a better understanding of the issues facing developers of safety-critical systems, and to provide a vehicle for the assessment of research ideas. The case studies are not based on the analysis of existing software development by others. Instead, we are attempting to create software for new and novel systems in a process that ultimately will involve all phases of the software lifecycle. In this abstract, we summarize our results to date in a small part of this project, namely the determination and classification of policies related to software safety that must be enforced to ensure safe operation. We hypothesize that this classification will permit a general approach to the implementation of a policy enforcement mechanism.

Dance recognition system using lower body movement.

PubMed

Simpson, Travis T; Wiesner, Susan L; Bennett, Bradford C

2014-02-01

The current means of locating specific movements in film necessitate hours of viewing, making the task of conducting research into movement characteristics and patterns tedious and difficult. This is particularly problematic for the research and analysis of complex movement systems such as sports and dance. While some systems have been developed to manually annotate film, to date no automated way of identifying complex, full body movement exists. With pattern recognition technology and knowledge of joint locations, automatically describing filmed movement using computer software is possible. This study used various forms of lower body kinematic analysis to identify codified dance movements. We created an algorithm that compares an unknown move with a specified start and stop against known dance moves. Our recognition method consists of classification and template correlation using a database of model moves. This system was optimized to include nearly 90 dance and Tai Chi Chuan movements, producing accurate name identification in over 97% of trials. In addition, the program had the capability to provide a kinematic description of either matched or unmatched moves obtained from classification recognition.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

PubMed Central

Gonzalez, Luis F.; Montes, Glen A.; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.

2016-01-01

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. PMID:26784196

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

PubMed

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Hybrid EEG-EOG brain-computer interface system for practical machine control.

PubMed

Punsawad, Yunyong; Wongsawat, Yodchanan; Parnichkun, Manukid

2010-01-01

Practical issues such as accuracy with various subjects, number of sensors, and time for training are important problems of existing brain-computer interface (BCI) systems. In this paper, we propose a hybrid framework for the BCI system that can make machine control more practical. The electrooculogram (EOG) is employed to control the machine in the left and right directions while the electroencephalogram (EEG) is employed to control the forword, no action, and complete stop motions of the machine. By using only 2-channel biosignals, the average classification accuracy of more than 95% can be achieved.

Development of a Ballistic Impact Detection System

DTIC Science & Technology

2004-09-01

body surface remains the largest variable to overcome. The snug fit of the body amour stabilizes the sensors and their response . The data from the...estimated to average 1 hour per response , including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data...ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 22 19a. NAME OF RESPONSIBLE PERSON

Photomorphic analysis techniques: An interim spatial analysis using satellite remote sensor imagery and historical data

NASA Technical Reports Server (NTRS)

Keuper, H. R.; Peplies, R. W.; Gillooly, R. P.

1977-01-01

The use of machine scanning and/or computer-based techniques to provide greater objectivity in the photomorphic approach was investigated. Photomorphic analysis and its application in regional planning are discussed. Topics included: delineation of photomorphic regions; inadequacies of existing classification systems; tonal and textural characteristics and signature analysis techniques; pattern recognition and Fourier transform analysis; and optical experiments. A bibliography is included.

Care for the Critically Injured Burn Patient Modulation of Burn Scars Through Laser Deliver of Stem Cells

DTIC Science & Technology

2013-10-01

average 1 hour per response , including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed...dermal remodeling 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...evaluations made prior to each biopsy. The initial grading system took into account vascularity , pliability, color, contour, texture, and

MeMoVolc report on classification and dynamics of volcanic explosive eruptions

NASA Astrophysics Data System (ADS)

Bonadonna, C.; Cioni, R.; Costa, A.; Druitt, T.; Phillips, J.; Pioli, L.; Andronico, D.; Harris, A.; Scollo, S.; Bachmann, O.; Bagheri, G.; Biass, S.; Brogi, F.; Cashman, K.; Dominguez, L.; Dürig, T.; Galland, O.; Giordano, G.; Gudmundsson, M.; Hort, M.; Höskuldsson, A.; Houghton, B.; Komorowski, J. C.; Küppers, U.; Lacanna, G.; Le Pennec, J. L.; Macedonio, G.; Manga, M.; Manzella, I.; Vitturi, M. de'Michieli; Neri, A.; Pistolesi, M.; Polacci, M.; Ripepe, M.; Rossi, E.; Scheu, B.; Sulpizio, R.; Tripoli, B.; Valade, S.; Valentine, G.; Vidal, C.; Wallenstein, N.

2016-11-01

Classifications of volcanic eruptions were first introduced in the early twentieth century mostly based on qualitative observations of eruptive activity, and over time, they have gradually been developed to incorporate more quantitative descriptions of the eruptive products from both deposits and observations of active volcanoes. Progress in physical volcanology, and increased capability in monitoring, measuring and modelling of explosive eruptions, has highlighted shortcomings in the way we classify eruptions and triggered a debate around the need for eruption classification and the advantages and disadvantages of existing classification schemes. Here, we (i) review and assess existing classification schemes, focussing on subaerial eruptions; (ii) summarize the fundamental processes that drive and parameters that characterize explosive volcanism; (iii) identify and prioritize the main research that will improve the understanding, characterization and classification of volcanic eruptions and (iv) provide a roadmap for producing a rational and comprehensive classification scheme. In particular, classification schemes need to be objective-driven and simple enough to permit scientific exchange and promote transfer of knowledge beyond the scientific community. Schemes should be comprehensive and encompass a variety of products, eruptive styles and processes, including for example, lava flows, pyroclastic density currents, gas emissions and cinder cone or caldera formation. Open questions, processes and parameters that need to be addressed and better characterized in order to develop more comprehensive classification schemes and to advance our understanding of volcanic eruptions include conduit processes and dynamics, abrupt transitions in eruption regime, unsteadiness, eruption energy and energy balance.

The comprehensiveness of the ESHRE/ESGE classification of female genital tract congenital anomalies: a systematic review of cases not classified by the AFS system.

PubMed

Di Spiezio Sardo, A; Campo, R; Gordts, S; Spinelli, M; Cosimato, C; Tanos, V; Brucker, S; Li, T C; Gergolet, M; De Angelis, C; Gianaroli, L; Grimbizis, G

2015-05-01

How comprehensive is the recently published European Society of Human Reproduction and Embryology (ESHRE)/European Society for Gynaecological Endoscopy (ESGE) classification system of female genital anomalies? The ESHRE/ESGE classification provides a comprehensive description and categorization of almost all of the currently known anomalies that could not be classified properly with the American Fertility Society (AFS) system. Until now, the more accepted classification system, namely that of the AFS, is associated with serious limitations in effective categorization of female genital anomalies. Many cases published in the literature could not be properly classified using the AFS system, yet a clear and accurate classification is a prerequisite for treatment. The CONUTA (CONgenital UTerine Anomalies) ESHRE/ESGE group conducted a systematic review of the literature to examine if those types of anomalies that could not be properly classified with the AFS system could be effectively classified with the use of the new ESHRE/ESGE system. An electronic literature search through Medline, Embase and Cochrane library was carried out from January 1988 to January 2014. Three participants independently screened, selected articles of potential interest and finally extracted data from all the included studies. Any disagreement was discussed and resolved after consultation with a fourth reviewer and the results were assessed independently and approved by all members of the CONUTA group. Among the 143 articles assessed in detail, 120 were finally selected reporting 140 cases that could not properly fit into a specific class of the AFS system. Those 140 cases were clustered in 39 different types of anomalies. The congenital anomaly involved a single organ in 12 (30.8%) out of the 39 types of anomalies, while multiple organs and/or segments of Müllerian ducts (complex anomaly) were involved in 27 (69.2%) types. Uterus was the organ most frequently involved (30/39: 76.9%), followed by cervix (26/39: 66.7%) and vagina (23/39: 59%). In all 39 types, the ESHRE/ESGE classification system provided a comprehensive description of each single or complex anomaly. A precise categorization was reached in 38 out of 39 types studied. Only one case of a bizarre uterine anomaly, with no clear embryological defect, could not be categorized and thus was placed in Class 6 (un-classified) of the ESHRE/ESGE system. The review of the literature was thorough but we cannot rule out the possibility that other defects exist which will also require testing in the new ESHRE/ESGE system. These anomalies, however, must be rare. The comprehensiveness of the ESHRE/ESGE classification adds objective scientific validity to its use. This may, therefore, promote its further dissemination and acceptance, which will have a positive outcome in clinical care and research. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology.

Classification of the Lie and Noether point symmetries for the Wave and the Klein-Gordon equations in pp-wave spacetimes

NASA Astrophysics Data System (ADS)

Paliathanasis, A.; Tsamparlis, M.; Mustafa, M. T.

2018-02-01

A complete classification of the Lie and Noether point symmetries for the Klein-Gordon and the wave equation in pp-wave spacetimes is obtained. The classification analysis is carried out by reducing the problem of the determination of the point symmetries to the problem of existence of conformal killing vectors on the pp-wave spacetimes. Employing the existing results for the isometry classes of the pp-wave spacetimes, the functional form of the potential is determined for which the Klein-Gordon equation admits point symmetries and Noetherian conservation law. Finally the Lie and Noether point symmetries of the wave equation are derived.

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

A remote sensing based vegetation classification logic for global land cover analysis

USGS Publications Warehouse

Running, Steven W.; Loveland, Thomas R.; Pierce, Lars L.; Nemani, R.R.; Hunt, E. Raymond

1995-01-01

This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.

Technical support for creating an artificial intelligence system for feature extraction and experimental design

NASA Technical Reports Server (NTRS)

Glick, B. J.

1985-01-01

Techniques for classifying objects into groups or clases go under many different names including, most commonly, cluster analysis. Mathematically, the general problem is to find a best mapping of objects into an index set consisting of class identifiers. When an a priori grouping of objects exists, the process of deriving the classification rules from samples of classified objects is known as discrimination. When such rules are applied to objects of unknown class, the process is denoted classification. The specific problem addressed involves the group classification of a set of objects that are each associated with a series of measurements (ratio, interval, ordinal, or nominal levels of measurement). Each measurement produces one variable in a multidimensional variable space. Cluster analysis techniques are reviewed and methods for incuding geographic location, distance measures, and spatial pattern (distribution) as parameters in clustering are examined. For the case of patterning, measures of spatial autocorrelation are discussed in terms of the kind of data (nominal, ordinal, or interval scaled) to which they may be applied.

The utility of the diagnosis of pedophilia: a comparison of various classification procedures.

PubMed

Kingston, Drew A; Firestone, Philip; Moulden, Heather M; Bradford, John M

2007-06-01

This study examined the utility of the diagnosis of pedophilia in a sample of extra-familial child molesters assessed at a university teaching hospital between 1982 and 1992. Pedophilia was defined in one of four ways: (1) DSM diagnosis made by a psychiatrist; (2) deviant phallometric profile; (3) DSM diagnosis and a deviant phallometric profile; and, (4) high scores based on the Screening Scale for Pedophilic Interest (Seto & Lalumière, 2001). Demographic data, psychological tests, and offence history were obtained and group differences were analyzed along with the ability of certain variables to contribute uniquely to the classification of pedophilia. Results indicated that few significant differences existed on psychological measures between pedophilic and nonpedophilic extra-familial child molesters regardless of the classification system employed. Finally, results indicated that the procedures used to define pedophilia were not significantly related to one another. Results are discussed in terms of the utility of the diagnosis of pedophilia.

Forested land cover classification on the Cumberland Plateau, Jackson County, Alabama: a comparison of Landsat ETM+ and SPOT5 images

Treesearch

Yong Wang; Shanta Parajuli; Callie Schweitzer; Glendon Smalley; Dawn Lemke; Wubishet Tadesse; Xiongwen Chen

2010-01-01

Forest cover classifications focus on the overall growth form (physiognomy) of the community, dominant vegetation, and species composition of the existing forest. Accurately classifying the forest cover type is important for forest inventory and silviculture. We compared classification accuracy based on Landsat Enhanced Thematic Mapper Plus (Landsat ETM+) and Satellite...

Cell dynamic morphology classification using deep convolutional neural networks.

PubMed

Li, Heng; Pang, Fengqian; Shi, Yonggang; Liu, Zhiwen

2018-05-15

Cell morphology is often used as a proxy measurement of cell status to understand cell physiology. Hence, interpretation of cell dynamic morphology is a meaningful task in biomedical research. Inspired by the recent success of deep learning, we here explore the application of convolutional neural networks (CNNs) to cell dynamic morphology classification. An innovative strategy for the implementation of CNNs is introduced in this study. Mouse lymphocytes were collected to observe the dynamic morphology, and two datasets were thus set up to investigate the performances of CNNs. Considering the installation of deep learning, the classification problem was simplified from video data to image data, and was then solved by CNNs in a self-taught manner with the generated image data. CNNs were separately performed in three installation scenarios and compared with existing methods. Experimental results demonstrated the potential of CNNs in cell dynamic morphology classification, and validated the effectiveness of the proposed strategy. CNNs were successfully applied to the classification problem, and outperformed the existing methods in the classification accuracy. For the installation of CNNs, transfer learning was proved to be a promising scheme. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

An intelligent interactive visual database management system for Space Shuttle closeout image management

NASA Technical Reports Server (NTRS)

Ragusa, James M.; Orwig, Gary; Gilliam, Michael; Blacklock, David; Shaykhian, Ali

1994-01-01

Status is given of an applications investigation on the potential for using an expert system shell for classification and retrieval of high resolution, digital, color space shuttle closeout photography. This NASA funded activity has focused on the use of integrated information technologies to intelligently classify and retrieve still imagery from a large, electronically stored collection. A space shuttle processing problem is identified, a working prototype system is described, and commercial applications are identified. A conclusion reached is that the developed system has distinct advantages over the present manual system and cost efficiencies will result as the system is implemented. Further, commercial potential exists for this integrated technology.

Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

PubMed

Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

2018-04-18

There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

Drug-nutrient interaction in clinical nutrition.

PubMed

Chan, Lingtak-Neander

2002-05-01

Drug-nutrient interactions have been recognized for decades. It is known that improper management of some of these interactions may lead to therapeutic failure or cause serious adverse effects to the patients. While most of the known drug-nutrient interactions involve changes in oral bioavailabilities and absorption of the offending compounds, recent investigations suggest that different mechanisms also exist. A mechanism-derived classification system for drug-nutrient interactions has only recently been developed. This system should facilitate the future research and development of practice guidelines in the identification and management of important interactions.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

Use of Log-Linear Models in Classification Problems.

DTIC Science & Technology

1981-12-01

polynomials. The second example involves infant hypoxic trauma, and many cells are empty. The existence conditions are used to find a model for which esti...mates of cell frequencies exist and are in good agreement with the ob- served data. Key Words: Classification problem, log-difference models, minimum 8...variates define k states, which are labeled consecutively. Thus, while MB define cells in their tables by an I-vector Z, we simply take Z to be a

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

The Comprehensive AOCMF Classification System: Condylar Process Fractures - Level 3 Tutorial

PubMed Central

Neff, Andreas; Cornelius, Carl-Peter; Rasse, Michael; Torre, Daniel Dalla; Audigé, Laurent

2014-01-01

This tutorial outlines the detailed system for fractures of the condylar process at the precision level 3 and is organized in a sequence of sections dealing with the description of the classification system within topographical subdivisions along with rules for fracture coding and a series of case examples with clinical imaging. Basically, the condylar process comprises three fracture levels and is subdivided into the head region, the condylar neck, and the condylar base. Fractures of the condylar head show typical fracture lines either within the lateral pole zone, which may lead to loss of vertical height, or medially to the pole zone, with the latter ones usually not compromising the vertical condyle to fossa relation. In condylar head fractures, the morphology is further described by the presence of minor or major fragmentation, the vertical apposition of fragments at the plane of the head fracture, the displacement of the condylar head with regard to the fossa including a potential distortion of the condylar head congruency resulting in dystopic condyle to fossa relations and the presence or absence of a loss of vertical ramus height. A specific vertical fracture pattern extending from the head to the neck or base subregion is considered. Fractures of the condylar neck and base can be differentiated according to a newly introduced one-third to two-thirds rule with regard to the proportion of the fracture line above and below the level of the sigmoid notch, which is presented in the classification article, and are basically subdivided according to the presence or absence of displacement or dislocation. In both condylar neck and base fractures, the classification is again based on the above mentioned parameters such as fragmentation, displacement of the condylar head with regard to the fossa, including dystopic condyle to fossa relations and loss of vertical ramus height, that is, according to the measurement of the condylar process. In addition, the classification assesses a sideward displacement including the respective displacement sector at the neck or base fracture site as well as the angulation of the superior main fragment and also considers a potential displacement of the caudal fragment with regard to the fossa, which may occur in fractures affecting additional fracture locations in the mandible. The design of this classification is discussed along with a review of existing classification systems. The condylar process for fracture location was defined according to the level 2 system presented in a previous tutorial in this special issue. PMID:25489390

The Comprehensive AOCMF Classification System: Condylar Process Fractures - Level 3 Tutorial.

PubMed

Neff, Andreas; Cornelius, Carl-Peter; Rasse, Michael; Torre, Daniel Dalla; Audigé, Laurent

2014-12-01

This tutorial outlines the detailed system for fractures of the condylar process at the precision level 3 and is organized in a sequence of sections dealing with the description of the classification system within topographical subdivisions along with rules for fracture coding and a series of case examples with clinical imaging. Basically, the condylar process comprises three fracture levels and is subdivided into the head region, the condylar neck, and the condylar base. Fractures of the condylar head show typical fracture lines either within the lateral pole zone, which may lead to loss of vertical height, or medially to the pole zone, with the latter ones usually not compromising the vertical condyle to fossa relation. In condylar head fractures, the morphology is further described by the presence of minor or major fragmentation, the vertical apposition of fragments at the plane of the head fracture, the displacement of the condylar head with regard to the fossa including a potential distortion of the condylar head congruency resulting in dystopic condyle to fossa relations and the presence or absence of a loss of vertical ramus height. A specific vertical fracture pattern extending from the head to the neck or base subregion is considered. Fractures of the condylar neck and base can be differentiated according to a newly introduced one-third to two-thirds rule with regard to the proportion of the fracture line above and below the level of the sigmoid notch, which is presented in the classification article, and are basically subdivided according to the presence or absence of displacement or dislocation. In both condylar neck and base fractures, the classification is again based on the above mentioned parameters such as fragmentation, displacement of the condylar head with regard to the fossa, including dystopic condyle to fossa relations and loss of vertical ramus height, that is, according to the measurement of the condylar process. In addition, the classification assesses a sideward displacement including the respective displacement sector at the neck or base fracture site as well as the angulation of the superior main fragment and also considers a potential displacement of the caudal fragment with regard to the fossa, which may occur in fractures affecting additional fracture locations in the mandible. The design of this classification is discussed along with a review of existing classification systems. The condylar process for fracture location was defined according to the level 2 system presented in a previous tutorial in this special issue.

Early postoperative repair status after rotator cuff repair cannot be accurately classified using questionnaires of patient function and isokinetic strength evaluation.

PubMed

Colliver, Jessica; Wang, Allan; Joss, Brendan; Ebert, Jay; Koh, Eamon; Breidahl, William; Ackland, Timothy

2016-04-01

This study investigated if patients with an intact tendon repair or partial-thickness retear early after rotator cuff repair display differences in clinical evaluations and whether early tendon healing can be predicted using these assessments. We prospectively evaluated 60 patients at 16 weeks after arthroscopic supraspinatus repair. Evaluation included the Oxford Shoulder Score, 11-item version of the Disabilities of the Arm, Shoulder and Hand, visual analog scale for pain, 12-item Short Form Health Survey, isokinetic strength, and magnetic resonance imaging (MRI). Independent t tests investigated clinical differences in patients based on the Sugaya MRI rotator cuff classification system (grades 1, 2, or 3). Discriminant analysis determined whether intact repairs (Sugaya grade 1) and partial-thickness retears (Sugaya grades 2 and 3) could be predicted. No differences (P < .05) existed in the clinical or strength measures. Although discriminant analysis revealed the 11-item version of the Disabilities of the Arm, Shoulder and Hand produced a 97% true-positive rate for predicting partial thickness retears, it also produced a 90% false-positive rate whereby it incorrectly predicted a retear in 90% of patients whose repair was intact. The ability to discriminate between groups was enhanced with up to 5 variables entered; however, only 87% of the partial-retear group and 36% of the intact-repair group were correctly classified. No differences in clinical scores existed between patients stratified by the Sugaya MRI classification system at 16 weeks. An intact repair or partial-thickness retear could not be accurately predicted. Our results suggest that correct classification of healing in the early postoperative stages should involve imaging. Copyright © 2016 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

The clinical diagnosis and misdiagnosis of senile dementia of Lewy body type (SDLT).

PubMed

McKeith, I G; Fairbairn, A F; Perry, R H; Thompson, P

1994-09-01

Current clinical classifications do not contain specific diagnostic categories for patients with senile dementia of the Lewy body type (SDLT), recently proposed as the second commonest neuropathological cause of dementia in the elderly. This study determines how existing clinical diagnosis systems label SDLT patients and suggests how such patients may be identified. A range of clinical diagnostic criteria for dementia were applied to case notes of autopsy-confirmed SDLT (n = 20), dementia of Alzheimer type (DAT; n = 21) and multi-infarct dementia (MID; n = 9) patients who had received psychogeriatric assessment. The predictive validity of each set of clinical criteria was calculated against the external criterion of neuropathological diagnosis. Many SDLT patients erroneously met criteria for MID (35% with Hachinski scores > or = 7) or for DAT (15% by NINCDS 'probable AD', 35% by DSM-III-R DAT and 50% by NINCDS 'possible AD'). Up to 85% of SDLT cases could be correctly identified using recently published specific criteria. SDLT usually has a discernible clinical syndrome and existing clinical classifications may need revision to diagnose correctly such patients.

Rare myositis-specific autoantibody associations among Hungarian patients with idiopathic inflammatory myopathy.

PubMed

Bodoki, L; Nagy-Vincze, M; Griger, Z; Betteridge, Z; Szöllősi, L; Jobanputra, R; Dankó, K

2015-01-01

Idiopathic inflammatory myopathies are systemic, chronic autoimmune diseases characterized by symmetrical, proximal muscle weakness. Homogeneous groups present with similar symptoms. The response to therapy and prognosis could be facilitated by myositis-specific autoantibodies, and in this way, give rise to immunoserological classification. The myositis-specific autoantibodies are directed against specific proteins found in the cytoplasm or in the nucleus of the cells. To date, literature suggests the rarity of the co-existence of two myositis-specific autoantibodies. In this study the authors highlight rare associations of myositis-specific autoantibodies. Three hundred and thirty-seven Hungarian patients with polymyositis or dermatomyositis were studied. Their clinical findings were noted retrospectively. Specific blood tests identified six patients with the rare co-existence of myositis-specific autoantibodies, anti-Jo-1 and anti-SRP, anti-Jo-1 and anti-Mi-2, anti-Mi-2 and anti-PL-12, anti-Mi-2 and anti-SRP, and anti-SRP and anti-PL-7, respectively. This case review aims to identify the clinical importance of these rare associations and their place within the immunoserological classification.

Possible realization of interacting symmetry-protected topological phases in topological crystalline insulators

NASA Astrophysics Data System (ADS)

Isobe, Hiroki; Fu, Liang

2015-03-01

The effects of electron-electron interaction in edge states of mirror-symmetry protected topological crystalline insulators (TCI's) are discussed. The analysis is performed by using bosonized Hamiltonian following the Tomonaga-Luttinger liquid theory. When two pairs of helical edge states exist, electron-electron interaction could gap out one edge mode, which is a possible realization of interacting symmetry-protected topological (SPT) phases. This type of SPT phase is closely related to a Luther-Emery liquid in spinful 1D system. We also propose a method of detecting the SPT phases by STM. The other focus of the study is the classification of SPT phases in mirror-symmetry protected TCI's. By adopting the Chern-Simons theory, we find that electron-electron interaction reduces the classification from Z to Z4. It means that the edge states can be gapped out when four pairs of edge states exist. In other cases, the edge modes cannot be fully gapped. Each of these states corresponds to a different SPT phase depending on the relevant interaction process.

Entropy Based Feature Selection for Fuzzy Set-Valued Information Systems

NASA Astrophysics Data System (ADS)

Ahmed, Waseem; Sufyan Beg, M. M.; Ahmad, Tanvir

2018-06-01

In Set-valued Information Systems (SIS), several objects contain more than one value for some attributes. Tolerance relation used for handling SIS sometimes leads to loss of certain information. To surmount this problem, fuzzy rough model was introduced. However, in some cases, SIS may contain some real or continuous set-values. Therefore, the existing fuzzy rough model for handling Information system with fuzzy set-values needs some changes. In this paper, Fuzzy Set-valued Information System (FSIS) is proposed and fuzzy similarity relation for FSIS is defined. Yager's relative conditional entropy was studied to find the significance measure of a candidate attribute of FSIS. Later, using these significance values, three greedy forward algorithms are discussed for finding the reduct and relative reduct for the proposed FSIS. An experiment was conducted on a sample population of the real dataset and a comparison of classification accuracies of the proposed FSIS with the existing SIS and single-valued Fuzzy Information Systems was made, which demonstrated the effectiveness of proposed FSIS.

Identifying States of a Financial Market

NASA Astrophysics Data System (ADS)

Münnix, Michael C.; Shimada, Takashi; Schäfer, Rudi; Leyvraz, Francois; Seligman, Thomas H.; Guhr, Thomas; Stanley, H. Eugene

2012-09-01

The understanding of complex systems has become a central issue because such systems exist in a wide range of scientific disciplines. We here focus on financial markets as an example of a complex system. In particular we analyze financial data from the S&P 500 stocks in the 19-year period 1992-2010. We propose a definition of state for a financial market and use it to identify points of drastic change in the correlation structure. These points are mapped to occurrences of financial crises. We find that a wide variety of characteristic correlation structure patterns exist in the observation time window, and that these characteristic correlation structure patterns can be classified into several typical ``market states''. Using this classification we recognize transitions between different market states. A similarity measure we develop thus affords means of understanding changes in states and of recognizing developments not previously seen.

Identifying states of a financial market.

PubMed

Münnix, Michael C; Shimada, Takashi; Schäfer, Rudi; Leyvraz, Francois; Seligman, Thomas H; Guhr, Thomas; Stanley, H Eugene

2012-01-01

The understanding of complex systems has become a central issue because such systems exist in a wide range of scientific disciplines. We here focus on financial markets as an example of a complex system. In particular we analyze financial data from the S&P 500 stocks in the 19-year period 1992-2010. We propose a definition of state for a financial market and use it to identify points of drastic change in the correlation structure. These points are mapped to occurrences of financial crises. We find that a wide variety of characteristic correlation structure patterns exist in the observation time window, and that these characteristic correlation structure patterns can be classified into several typical "market states". Using this classification we recognize transitions between different market states. A similarity measure we develop thus affords means of understanding changes in states and of recognizing developments not previously seen.

Classification of Ion Mobility Data Using the Neural Network Approach

NASA Technical Reports Server (NTRS)

Duong, T. A.; Kanik, I.

2005-01-01

Determination of atmospheric and surface elemental and molecular composition of various solar system bodies is essential to the development of a firm understanding of the origin and evolution of the solar system. Furthermore, such data is needed to address the intriguing question of whether or not life exists or once existed elsewhere in the Solar System. As such, these measurements are among the primary scientific goals of NASA s current and future planetary missions. In recent years, significant progress toward both miniaturization and field portability of in situ analytical separation and detection devices have been made with future planetary explorations in mind. However, despite all these advances, accurate in situ identification of atmospheric and surface compounds remains a big challenge. In response to that we are developing various hardware and software tools which would enable us to uniquely identify species of interest in a complex chemical environment.

Subject-Adaptive Real-Time Sleep Stage Classification Based on Conditional Random Field

PubMed Central

Luo, Gang; Min, Wanli

2007-01-01

Sleep staging is the pattern recognition task of classifying sleep recordings into sleep stages. This task is one of the most important steps in sleep analysis. It is crucial for the diagnosis and treatment of various sleep disorders, and also relates closely to brain-machine interfaces. We report an automatic, online sleep stager using electroencephalogram (EEG) signal based on a recently-developed statistical pattern recognition method, conditional random field, and novel potential functions that have explicit physical meanings. Using sleep recordings from human subjects, we show that the average classification accuracy of our sleep stager almost approaches the theoretical limit and is about 8% higher than that of existing systems. Moreover, for a new subject snew with limited training data Dnew, we perform subject adaptation to improve classification accuracy. Our idea is to use the knowledge learned from old subjects to obtain from Dnew a regulated estimate of CRF’s parameters. Using sleep recordings from human subjects, we show that even without any Dnew, our sleep stager can achieve an average classification accuracy of 70% on snew. This accuracy increases with the size of Dnew and eventually becomes close to the theoretical limit. PMID:18693884

The classification and application of toxic Chinese materia medica.

PubMed

Liu, Xinmin; Wang, Qiong; Song, Guangqing; Zhang, Guangping; Ye, Zuguang; Williamson, Elizabeth M

2014-03-01

Many important drugs in the Chinese materia medica (CMM) are known to be toxic, and it has long been recognized in classical Chinese medical theory that toxicity can arise directly from the components of a single CMM or may be induced by an interaction between combined CMM. Traditional Chinese Medicine presents a unique set of pharmaceutical theories that include particular methods for processing, combining and decocting, and these techniques contribute to reducing toxicity as well as enhancing efficacy. The current classification of toxic CMM drugs, traditional methods for processing toxic CMM and the prohibited use of certain combinations, is based on traditional experience and ancient texts and monographs, but accumulating evidence increasingly supports their use to eliminate or reduce toxicity. Modern methods are now being used to evaluate the safety of CMM; however, a new system for describing the toxicity of Chinese herbal medicines may need to be established to take into account those herbs whose toxicity is delayed or otherwise hidden, and which have not been incorporated into the traditional classification. This review explains the existing classification and justifies it where appropriate, using experimental results often originally published in Chinese and previously not available outside China. Copyright © 2013 John Wiley & Sons, Ltd.

Protein Sequence Classification with Improved Extreme Learning Machine Algorithms

PubMed Central

2014-01-01

Precisely classifying a protein sequence from a large biological protein sequences database plays an important role for developing competitive pharmacological products. Comparing the unseen sequence with all the identified protein sequences and returning the category index with the highest similarity scored protein, conventional methods are usually time-consuming. Therefore, it is urgent and necessary to build an efficient protein sequence classification system. In this paper, we study the performance of protein sequence classification using SLFNs. The recent efficient extreme learning machine (ELM) and its invariants are utilized as the training algorithms. The optimal pruned ELM is first employed for protein sequence classification in this paper. To further enhance the performance, the ensemble based SLFNs structure is constructed where multiple SLFNs with the same number of hidden nodes and the same activation function are used as ensembles. For each ensemble, the same training algorithm is adopted. The final category index is derived using the majority voting method. Two approaches, namely, the basic ELM and the OP-ELM, are adopted for the ensemble based SLFNs. The performance is analyzed and compared with several existing methods using datasets obtained from the Protein Information Resource center. The experimental results show the priority of the proposed algorithms. PMID:24795876

A Study of Feature Combination for Vehicle Detection Based on Image Processing

PubMed Central

2014-01-01

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. PMID:24672299

A complete electrical shock hazard classification system and its application

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

Gordon, Lloyd; Cartelli, Laura; Graham, Nicole

Current electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. As a result, this leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. We find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz power. This paper proposes a method of classifying allmore » of the electrical shock hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Lastly, the new comprehensive electrical shock hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards.« less

A complete electrical shock hazard classification system and its application

DOE PAGES

Gordon, Lloyd; Cartelli, Laura; Graham, Nicole

2018-02-08

Current electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. As a result, this leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. We find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz power. This paper proposes a method of classifying allmore » of the electrical shock hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Lastly, the new comprehensive electrical shock hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards.« less

A new classification scheme of European cold-water coral habitats: Implications for ecosystem-based management of the deep sea

NASA Astrophysics Data System (ADS)

Davies, J. S.; Guillaumont, B.; Tempera, F.; Vertino, A.; Beuck, L.; Ólafsdóttir, S. H.; Smith, C. J.; Fosså, J. H.; van den Beld, I. M. J.; Savini, A.; Rengstorf, A.; Bayle, C.; Bourillet, J.-F.; Arnaud-Haond, S.; Grehan, A.

2017-11-01

Cold-water corals (CWC) can form complex structures which provide refuge, nursery grounds and physical support for a diversity of other living organisms. However, irrespectively from such ecological significance, CWCs are still vulnerable to human pressures such as fishing, pollution, ocean acidification and global warming Providing coherent and representative conservation of vulnerable marine ecosystems including CWCs is one of the aims of the Marine Protected Areas networks being implemented across European seas and oceans under the EC Habitats Directive, the Marine Strategy Framework Directive and the OSPAR Convention. In order to adequately represent ecosystem diversity, these initiatives require a standardised habitat classification that organises the variety of biological assemblages and provides consistent and functional criteria to map them across European Seas. One such classification system, EUNIS, enables a broad level classification of the deep sea based on abiotic and geomorphological features. More detailed lower biotope-related levels are currently under-developed, particularly with regards to deep-water habitats (>200 m depth). This paper proposes a hierarchical CWC biotope classification scheme that could be incorporated by existing classification schemes such as EUNIS. The scheme was developed within the EU FP7 project CoralFISH to capture the variability of CWC habitats identified using a wealth of seafloor imagery datasets from across the Northeast Atlantic and Mediterranean. Depending on the resolution of the imagery being interpreted, this hierarchical scheme allows data to be recorded from broad CWC biotope categories down to detailed taxonomy-based levels, thereby providing a flexible yet valuable information level for management. The CWC biotope classification scheme identifies 81 biotopes and highlights the limitations of the classification framework and guidance provided by EUNIS, the EC Habitats Directive, OSPAR and FAO; which largely underrepresent CWC habitats.

Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

PubMed Central

Faye, Ibrahima; Samir, Brahim Belhaouari; Md Said, Abas

2014-01-01

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth. PMID:25045727

A new approach to enhance the performance of decision tree for classifying gene expression data.

PubMed

Hassan, Md; Kotagiri, Ramamohanarao

2013-12-20

Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

Reduction from cost-sensitive ordinal ranking to weighted binary classification.

PubMed

Lin, Hsuan-Tien; Li, Ling

2012-05-01

We present a reduction framework from ordinal ranking to binary classification. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended examples with any binary classification algorithm, and constructing a ranker from the binary classifier. Based on the framework, we show that a weighted 0/1 loss of the binary classifier upper-bounds the mislabeling cost of the ranker, both error-wise and regret-wise. Our framework allows not only the design of good ordinal ranking algorithms based on well-tuned binary classification approaches, but also the derivation of new generalization bounds for ordinal ranking from known bounds for binary classification. In addition, our framework unifies many existing ordinal ranking algorithms, such as perceptron ranking and support vector ordinal regression. When compared empirically on benchmark data sets, some of our newly designed algorithms enjoy advantages in terms of both training speed and generalization performance over existing algorithms. In addition, the newly designed algorithms lead to better cost-sensitive ordinal ranking performance, as well as improved listwise ranking performance.

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Death of the Westphalia State System, Implications for Future Military Employment

DTIC Science & Technology

2008-05-01

information is estimated to average 1 hour per response , including the time for reviewing instructions, searching existing data sources, gathering and...16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON McCoy, Jeffrey D. MAJ a...Black Hawk Down, 333. 8 of a world that was becoming more connected or “globalized” in which greater economic and social stability is achieved.6

An update of commercial infrared sensing and imaging instruments

NASA Technical Reports Server (NTRS)

Kaplan, Herbert

1989-01-01

A classification of infrared sensing instruments by type and application, listing commercially available instruments, from single point thermal probes to on-line control sensors, to high speed, high resolution imaging systems is given. A review of performance specifications follows, along with a discussion of typical thermographic display approaches utilized by various imager manufacturers. An update report on new instruments, new display techniques and newly introduced features of existing instruments is given.

Considerations for designing robotic upper limb rehabilitation devices

NASA Astrophysics Data System (ADS)

Nadas, I.; Vaida, C.; Gherman, B.; Pisla, D.; Carbone, G.

2017-12-01

The present study highlights the advantages of robotic systems for post-stroke rehabilitation of the upper limb. The latest demographic studies illustrate a continuous increase of the average life span, which leads to a continuous increase of stroke incidents and patients requiring rehabilitation. Some studies estimate that by 2030 the number of physical therapists will be insufficient for the patients requiring physical rehabilitation, imposing a shift in the current methodologies. A viable option is the implementation of robotic systems that assist the patient in performing rehabilitation exercises, the physical therapist role being to establish the therapeutic program for each patient and monitor their individual progress. Using a set of clinical measurements for the upper limb motions, the analysis of rehabilitation robotic systems provides a comparative study between the motions required by clinicians and the ones that robotic systems perform for different therapeutic exercises. A critical analysis of existing robots is performed using several classifications: mechanical design, assistance type, actuation and power transmission, control systems and human robot interaction (HRI) strategies. This classification will determine a set of pre-requirements for the definition of new concepts and efficient solutions for robotic assisted rehabilitation therapy.

14 CFR 1203.406 - Additional classification factors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Section 1203.406 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION INFORMATION SECURITY... other Government departments and agencies should be considered. Classification of official information... exists elsewhere for the information under consideration which would make it necessary to assign a higher...

Ecological Land Classification: Applications to Identify the Productive Potential of Southern Forests

Treesearch

Dennis L. Mengel; D. Thompson Tew; [Editors

1991-01-01

Eighteen papers representing four categories-Regional Overviews; Classification System Development; Classification System Interpretation; Mapping/GIS Applications in Classification Systems-present the state of the art in forest-land classification and evaluation in the South. In addition, nine poster papers are presented.

Automated quasi-3D spine curvature quantification and classification

NASA Astrophysics Data System (ADS)

Khilari, Rupal; Puchin, Juris; Okada, Kazunori

2018-02-01

Scoliosis is a highly prevalent spine deformity that has traditionally been diagnosed through measurement of the Cobb angle on radiographs. More recent technology such as the commercial EOS imaging system, although more accurate, also require manual intervention for selecting the extremes of the vertebrae forming the Cobb angle. This results in a high degree of inter and intra observer error in determining the extent of spine deformity. Our primary focus is to eliminate the need for manual intervention by robustly quantifying the curvature of the spine in three dimensions, making it consistent across multiple observers. Given the vertebrae centroids, the proposed Vertebrae Sequence Angle (VSA) estimation and segmentation algorithm finds the largest angle between consecutive pairs of centroids within multiple inflection points on the curve. To exploit existing clinical diagnostic standards, the algorithm uses a quasi-3-dimensional approach considering the curvature in the coronal and sagittal projection planes of the spine. Experiments were performed with manuallyannotated ground-truth classification of publicly available, centroid-annotated CT spine datasets. This was compared with the results obtained from manual Cobb and Centroid angle estimation methods. Using the VSA, we then automatically classify the occurrence and the severity of spine curvature based on Lenke's classification for idiopathic scoliosis. We observe that the results appear promising with a scoliotic angle lying within +/- 9° of the Cobb and Centroid angle, and vertebrae positions differing by at the most one position. Our system also resulted in perfect classification of scoliotic from healthy spines with our dataset with six cases.

Knowledge-rich temporal relation identification and classification in clinical notes

PubMed Central

D’Souza, Jennifer; Ng, Vincent

2014-01-01

Motivation: We examine the task of temporal relation classification for the clinical domain. Our approach to this task departs from existing ones in that it is (i) ‘knowledge-rich’, employing sophisticated knowledge derived from discourse relations as well as both domain-independent and domain-dependent semantic relations, and (ii) ‘hybrid’, combining the strengths of rule-based and learning-based approaches. Evaluation results on the i2b2 Clinical Temporal Relations Challenge corpus show that our approach yields a 17–24% and 8–14% relative reduction in error over a state-of-the-art learning-based baseline system when gold-standard and automatically identified temporal relations are used, respectively. Database URL: http://www.hlt.utdallas.edu/~jld082000/temporal-relations/ PMID:25414383

Preliminary Study of Bioinformatics Patents and Their Classifications Registered in the KIPRIS Database.

PubMed

Park, Hyun-Seok

2012-12-01

Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.

Creating a better picture of chronic pain: improving pain pictogram designs through systematic evaluation of user responses

PubMed Central

Stones, Catherine; Knapp, Peter; Closs, S Jose

2016-01-01

This article discusses the challenges of visually representing pain qualities in pictogram design. An existing set of 12 pictograms designed for people with literacy problems was evaluated to understand more about misunderstandings of pictogram interpretation. Two sets of university students from different disciplines were asked to interpret the pictograms, and a novel classification system was developed to categorise answer types, as ‘location’, ‘affective’, temporal’ or ‘literal’. Several design recommendations are made as a result that will help improve the design of pain pictograms as a whole as well as guide designers of related pictogram work. We demonstrate how, through the robust classification of incorrect responses, it is possible to extract useful comprehension error patterns to inform future design. PMID:27867507

A diagram retrieval method with multi-label learning

NASA Astrophysics Data System (ADS)

Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

2015-01-01

In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

Experimental Observation of Three-Component New Fermions in Topological Semimetal MoP

NASA Astrophysics Data System (ADS)

Lv, B. Q.; Feng, Z.-L.; Xu, Q.-N.; Ma, J.-Z.; Kong, L.-Y.; Richard, Pierre; Huang, Y.-B.; Strocov, V. N.; Fang, C.; Weng, H.-M.; Shi, Y.-G.; Qian, Tian; Ding, Hong; Paul Scherrer Institute, Swiss Light Source, CH-5232 Villigen PSI, Switzerland Team; Shanghai Synchrotron Radiation Facility, Shanghai Institute of Applied Physics Team; University of Chinese Academy of Sciences, Beijing 100190, China Team; Collaborative Innovation Center of Quantum Matter, Beijing, China Collaboration; Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China Team

Condensed matter systems can host quasiparticle excitations that are analogues to elementary particles such as Majorana, Weyl, and Dirac fermions. Recent advances in band theory have expanded the classification of fermions in crystals, and revealed crystal symmetry-protected electron excitations that have no high-energy counterparts. Here, using angle-resolved photoemission spectroscopy, we demonstrate the existence of a triply degenerate point in the electronic structure of MoP crystal, where the quasiparticle excitations are beyond the Majorana-Weyl-Dirac classification. Furthermore, we observe pairs of Weyl points in the bulk electronic structure coexisting with the new fermions, thus introducing a platform for studying the interplay between different types of fermions. We thank Binbin Fu, Nan Xu, and Xin Gao for the assistance in the ARPES experiments.

CV-Muzar - The Virtual Community Environment that Uses Multiagent Systems for Formation of Groups

NASA Astrophysics Data System (ADS)

de Marchi, Ana Carolina Bertoletti; Moraes, Márcia Cristina

The purpose of this chapter is to present two agents' societies responsible for group formation (sub-communities) in CV-Muzar (Augusto Ruschi Zoobotanical Museum Virtual Community of the University of Passo Fundo). These societies are integrated to execute a data mining classification process. The first society is a static society that intends preprocessing data, investigating the information about groups in the CV-Muzar. The second society is a dynamical society that will make a classification process by analyzing the existing groups and look for participants that have common subjects in order to constitute a sub-community. The formation of sub-communities is a new functionality within the CV-Muzar that intends to bring the participants together according to two scopes: interest similarity and knowledge complementarities.

Comparing ecoregional classifications for natural areas management in the Klamath Region, USA

USGS Publications Warehouse

Sarr, Daniel A.; Duff, Andrew; Dinger, Eric C.; Shafer, Sarah L.; Wing, Michael; Seavy, Nathaniel E.; Alexander, John D.

2015-01-01

We compared three existing ecoregional classification schemes (Bailey, Omernik, and World Wildlife Fund) with two derived schemes (Omernik Revised and Climate Zones) to explore their effectiveness in explaining species distributions and to better understand natural resource geography in the Klamath Region, USA. We analyzed presence/absence data derived from digital distribution maps for trees, amphibians, large mammals, small mammals, migrant birds, and resident birds using three statistical analyses of classification accuracy (Analysis of Similarity, Canonical Analysis of Principal Coordinates, and Classification Strength). The classifications were roughly comparable in classification accuracy, with Omernik Revised showing the best overall performance. Trees showed the strongest fidelity to the classifications, and large mammals showed the weakest fidelity. We discuss the implications for regional biogeography and describe how intermediate resolution ecoregional classifications may be appropriate for use as natural areas management domains.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

Segmentation of bone and soft tissue regions in digital radiographic images of extremities

NASA Astrophysics Data System (ADS)

Pakin, S. Kubilay; Gaborski, Roger S.; Barski, Lori L.; Foos, David H.; Parker, Kevin J.

2001-07-01

This paper presents an algorithm for segmentation of computed radiography (CR) images of extremities into bone and soft tissue regions. The algorithm is a region-based one in which the regions are constructed using a growing procedure with two different statistical tests. Following the growing process, tissue classification procedure is employed. The purpose of the classification is to label each region as either bone or soft tissue. This binary classification goal is achieved by using a voting procedure that consists of clustering of regions in each neighborhood system into two classes. The voting procedure provides a crucial compromise between local and global analysis of the image, which is necessary due to strong exposure variations seen on the imaging plate. Also, the existence of regions whose size is large enough such that exposure variations can be observed through them makes it necessary to use overlapping blocks during the classification. After the classification step, resulting bone and soft tissue regions are refined by fitting a 2nd order surface to each tissue, and reevaluating the label of each region according to the distance between the region and surfaces. The performance of the algorithm is tested on a variety of extremity images using manually segmented images as gold standard. The experiments showed that our algorithm provided a bone boundary with an average area overlap of 90% compared to the gold standard.

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

PubMed

Ramírez, J; Górriz, J M; Ortiz, A; Martínez-Murcia, F J; Segovia, F; Salas-Gonzalez, D; Castillo-Barnes, D; Illán, I A; Puntonet, C G

2018-05-15

Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have suggested that people with MCI tend to progress to AD at a rate of about 10-15% per year. However, the ability of clinicians and machine learning systems to predict AD based on MRI biomarkers at an early stage is still a challenging problem that can have a great impact in improving treatments. The proposed system, developed by the SiPBA-UGR team for this challenge, is based on feature standardization, ANOVA feature selection, partial least squares feature dimension reduction and an ensemble of One vs. Rest random forest classifiers. With the aim of improving its performance when discriminating healthy controls (HC) from MCI, a second binary classification level was introduced that reconsiders the HC and MCI predictions of the first level. The system was trained and evaluated on an ADNI datasets that consist of T1-weighted MRI morphological measurements from HC, stable MCI, converter MCI and AD subjects. The proposed system yields a 56.25% classification score on the test subset which consists of 160 real subjects. The classifier yielded the best performance when compared to: (i) One vs. One (OvO), One vs. Rest (OvR) and error correcting output codes (ECOC) as strategies for reducing the multiclass classification task to multiple binary classification problems, (ii) support vector machines, gradient boosting classifier and random forest as base binary classifiers, and (iii) bagging ensemble learning. A robust method has been proposed for the international challenge on MCI prediction based on MRI data. The system yielded the second best performance during the competition with an accuracy rate of 56.25% when evaluated on the real subjects of the test set. Copyright © 2017 Elsevier B.V. All rights reserved.

Evidence for the Existing American Nurses Association-Recognized Standardized Nursing Terminologies: A Systematic Review

PubMed Central

Tastan, Sevinc; Linch, Graciele C. F.; Keenan, Gail M.; Stifter, Janet; McKinney, Dawn; Fahey, Linda; Dunn Lopez, Karen; Yao, Yingwei; Wilkie, Diana J.

2014-01-01

Objective To determine the state of the science for the five standardized nursing terminology sets in terms of level of evidence and study focus. Design Systematic Review. Data sources Keyword search of PubMed, CINAHL, and EMBASE databases from 1960s to March 19, 2012 revealed 1,257 publications. Review Methods From abstract review we removed duplicate articles, those not in English or with no identifiable standardized nursing terminology, and those with a low-level of evidence. From full text review of the remaining 312 articles, eight trained raters used a coding system to record standardized nursing terminology names, publication year, country, and study focus. Inter-rater reliability confirmed the level of evidence. We analyzed coded results. Results On average there were 4 studies per year between 1985 and 1995. The yearly number increased to 14 for the decade between 1996–2005, 21 between 2006–2010, and 25 in 2011. Investigators conducted the research in 27 countries. By evidence level for the 312 studies 72.4% were descriptive, 18.9% were observational, and 8.7% were intervention studies. Of the 312 reports, 72.1% focused on North American Nursing Diagnosis-International, Nursing Interventions Classification, Nursing Outcome Classification, or some combination of those three standardized nursing terminologies; 9.6% on Omaha System; 7.1% on International Classification for Nursing Practice; 1.6% on Clinical Care Classification/Home Health Care Classification; 1.6% on Perioperative Nursing Data Set; and 8.0% on two or more standardized nursing terminology sets. There were studies in all 10 foci categories including those focused on concept analysis/classification infrastructure (n = 43), the identification of the standardized nursing terminology concepts applicable to a health setting from registered nurses’ documentation (n = 54), mapping one terminology to another (n = 58), implementation of standardized nursing terminologies into electronic health records (n = 12), and secondary use of electronic health record data (n = 19). Conclusions Findings reveal that the number of standardized nursing terminology publications increased primarily since 2000 with most focusing on North American Nursing Diagnosis-International, Nursing Interventions Classification, and Nursing Outcome Classification. The majority of the studies were descriptive, qualitative, or correlational designs that provide a strong base for understanding the validity and reliability of the concepts underlying the standardized nursing terminologies. There is evidence supporting the successful integration and use in electronic health records for two standardized nursing terminology sets: (1) the North American Nursing Diagnosis-International, Nursing Interventions Classification, and Nursing Outcome Classification set; and (2) the Omaha System set. Researchers, however, should continue to strengthen standardized nursing terminology study designs to promote continuous improvement of the standardized nursing terminologies and use in clinical practice. PMID:24412062

Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study

NASA Astrophysics Data System (ADS)

Aljuboori, Ahmed S.; Coenen, Frans; Nsaif, Mohammed; Parsons, David J.

2018-05-01

Case-Based Reasoning (CBR) plays a major role in expert system research. However, a critical problem can be met when a CBR system retrieves incorrect cases. Class Association Rules (CARs) have been utilized to offer a potential solution in a previous work. The aim of this paper was to perform further validation of Case-Based Reasoning using a Classification based on Association Rules (CBRAR) to enhance the performance of Similarity Based Retrieval (SBR). The CBRAR strategy uses a classed frequent pattern tree algorithm (FP-CAR) in order to disambiguate wrongly retrieved cases in CBR. The research reported in this paper makes contributions to both fields of CBR and Association Rules Mining (ARM) in that full target cases can be extracted from the FP-CAR algorithm without invoking P-trees and union operations. The dataset used in this paper provided more efficient results when the SBR retrieves unrelated answers. The accuracy of the proposed CBRAR system outperforms the results obtained by existing CBR tools such as Jcolibri and FreeCBR.

Acute myocardial infarction and diagnosis-related groups: patient classification and hospital reimbursement in 11 European countries.

PubMed

Quentin, Wilm; Rätto, Hanna; Peltola, Mikko; Busse, Reinhard; Häkkinen, Unto

2013-07-01

As part of the diagnosis related groups in Europe (EuroDRG) project, researchers from 11 countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their DRG systems deal with patients admitted to hospital for acute myocardial infarction (AMI). The study aims to assist cardiologists and national authorities to optimize their DRG systems. National or regional databases were used to identify hospital cases with a primary diagnosis of AMI. Diagnosis-related group classification algorithms and indicators of resource consumption were compared for those DRGs that individually contained at least 1% of cases. Six standardized case vignettes were defined, and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems vary widely: they classify AMI patients according to different sets of variables into diverging numbers of DRGs (between 4 DRGs in Estonia and 16 DRGs in France). The most complex DRG is valued 11 times more resource intensive than an index case in Estonia but only 1.38 times more resource intensive than an index case in England. Comparisons of quasi prices for the case vignettes show that hypothetical payments for the index case amount to only €420 in Poland but to €7930 in Ireland. Large variation exists in the classification of AMI patients across Europe. Cardiologists and national DRG authorities should consider how other countries' DRG systems classify AMI patients in order to identify potential scope for improvement and to ensure fair and appropriate reimbursement.

Acute myocardial infarction and diagnosis-related groups: patient classification and hospital reimbursement in 11 European countries

PubMed Central

Quentin, Wilm; Rätto, Hanna; Peltola, Mikko; Busse, Reinhard; Häkkinen, Unto

2013-01-01

Aims As part of the diagnosis related groups in Europe (EuroDRG) project, researchers from 11 countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their DRG systems deal with patients admitted to hospital for acute myocardial infarction (AMI). The study aims to assist cardiologists and national authorities to optimize their DRG systems. Methods and results National or regional databases were used to identify hospital cases with a primary diagnosis of AMI. Diagnosis-related group classification algorithms and indicators of resource consumption were compared for those DRGs that individually contained at least 1% of cases. Six standardized case vignettes were defined, and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems vary widely: they classify AMI patients according to different sets of variables into diverging numbers of DRGs (between 4 DRGs in Estonia and 16 DRGs in France). The most complex DRG is valued 11 times more resource intensive than an index case in Estonia but only 1.38 times more resource intensive than an index case in England. Comparisons of quasi prices for the case vignettes show that hypothetical payments for the index case amount to only €420 in Poland but to €7930 in Ireland. Conclusions Large variation exists in the classification of AMI patients across Europe. Cardiologists and national DRG authorities should consider how other countries' DRG systems classify AMI patients in order to identify potential scope for improvement and to ensure fair and appropriate reimbursement. PMID:23364755

Natural Resources Inventory and Land Evaluation in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. A system was developed to operationally map and measure the areal extent of various land use categories for updating existing and producing new and actual thematic maps showing the latest state of rural and urban landscapes and its changes. The processing system includes: (1) preprocessing steps for radiometric and geometric corrections; (2) classification of the data by a multivariate procedure, using a stepwise linear discriminant analysis based on carefully selected training cells; and (3) output in form of color maps by printing black and white theme overlays of a selected scale with photomation system and its coloring and combination into a color composite.

Identification of asteroid dynamical families

NASA Technical Reports Server (NTRS)

Valsecchi, G. B.; Carusi, A.; Knezevic, Z.; Kresak, L.; Williams, J. G.

1989-01-01

Problems involved in the identification of asteroid dynamical families are discussed, and some methodological guidelines are presented. Asteroid family classifications are reviewed, and differences in the existing classifications are examined with special attention given to the effects of observational selection on the classification of family membership. The paper also discusses various theories of secular perturbations, including the classical linear theory, the theory of Williams (1969), and the higher order/degree theory of Yuasa (1973).

Real-Time Speech/Music Classification With a Hierarchical Oblique Decision Tree

DTIC Science & Technology

2008-04-01

REAL-TIME SPEECH/ MUSIC CLASSIFICATION WITH A HIERARCHICAL OBLIQUE DECISION TREE Jun Wang, Qiong Wu, Haojiang Deng, Qin Yan Institute of Acoustics...time speech/ music classification with a hierarchical oblique decision tree. A set of discrimination features in frequency domain are selected...handle signals without discrimination and can not work properly in the existence of multimedia signals. This paper proposes a real-time speech/ music

Hierarchical trie packet classification algorithm based on expectation-maximization clustering.

PubMed

Bi, Xia-An; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm.

Unsupervised classification of earth resources data.

NASA Technical Reports Server (NTRS)

Su, M. Y.; Jayroe, R. R., Jr.; Cummings, R. E.

1972-01-01

A new clustering technique is presented. It consists of two parts: (a) a sequential statistical clustering which is essentially a sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by existing supervised maximum liklihood classification technique.

Racial classification in the evolutionary sciences: a comparative analysis.

PubMed

Billinger, Michael S

2007-01-01

Human racial classification has long been a problem for the discipline of anthropology, but much of the criticism of the race concept has focused on its social and political connotations. The central argument of this paper is that race is not a specifically human problem, but one that exists in evolutionary thought in general. This paper looks at various disciplinary approaches to racial or subspecies classification, extending its focus beyond the anthropological race concept by providing a comparative analysis of the use of racial classification in evolutionary biology, genetics, and anthropology.

Is there any correlation between the ATS, BTS, ERS and GOLD COPD's severity scales and the frequency of hospital admissions?

PubMed

Tsoumakidou, Maria; Tzanakis, Nikolaos; Voulgaraki, Olga; Mitrouska, Ioanna; Chrysofakis, Georgios; Samiou, Maria; Siafakas, Nikolaos M

2004-02-01

Disagreement exists between different COPD guidelines considering classification of severity of the disease. The aim of our study was to determine whether there is any correlation between severity scales of various COPD guidelines (ATS, BTS, ERS and GOLD) and the frequency of hospitalisations for COPD exacerbation. A cohort of 67 COPD patients (65 male 2 female, 45 ex-smokers, 22 current smokers, aged (69.4 +/- 1.1)) was recruited from those admitted in the pulmonary clinic of the University Hospital of Heraklion, Crete for an acute exacerbation. Lung function tests and arterial blood gases analyses were performed during stable conditions at a scheduled visit 2 months after discharge. The patients were stratified using the FEV1 percent-predicted measurement of this visit into mild, moderate and severe in accordance to the ATS, BTS, ERS and GOLD scales of severity. The number of hospitalisations for acute exacerbation was recorded for the following 18 months. A total of 165 exacerbations were recorded. The correlation between the severity of COPD and the number of hospitalisations per year was statistically significant using the GOLD classification system of severity (P = 0.02 and r = 0.294). A weak correlation was also found between the number of hospitalisations and the ERS classification system (P = 0.05 and r = 0.24). No statistically significant correlation was found between the number of hospitalisations and the ATS or BTS severity scales. In conclusion the GOLD and ERS classification systems of severity of COPD correlated to exacerbations causing hospitalisation. The same was not true for the ATS and BTS severity scales. Better correlation was achieved with the GOLD scale.

Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

PubMed

Siuly; Li, Yan; Paul Wen, Peng

2014-03-01

Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A comprehensive and quantitative exploration of thousands of viral genomes

PubMed Central

Mahmoudabadi, Gita

2018-01-01

The complete assembly of viral genomes from metagenomic datasets (short genomic sequences gathered from environmental samples) has proven to be challenging, so there are significant blind spots when we view viral genomes through the lens of metagenomics. One approach to overcoming this problem is to leverage the thousands of complete viral genomes that are publicly available. Here we describe our efforts to assemble a comprehensive resource that provides a quantitative snapshot of viral genomic trends – such as gene density, noncoding percentage, and abundances of functional gene categories – across thousands of viral genomes. We have also developed a coarse-grained method for visualizing viral genome organization for hundreds of genomes at once, and have explored the extent of the overlap between bacterial and bacteriophage gene pools. Existing viral classification systems were developed prior to the sequencing era, so we present our analysis in a way that allows us to assess the utility of the different classification systems for capturing genomic trends. PMID:29624169

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California: year-1 progress

USGS Publications Warehouse

Forney, William; Raumann, Christian G.; Minor, T.B.; Smith, J. LaRue; Vogel, John; Vitales, Robert

2002-01-01

As part of the requirements for the Geographic Research and Applications Prospectus grants, this Open-File Report is the second of two that resulted from the first year of the project. The first Open-File Report (OFR 01-418) introduced the project, reviewed the existing body of literature, and outlined the research approach. This document will present an update of the research approach and offer some preliminary results from multiple efforts, specifically, the production of historical digital orthophoto quadrangles, the development of the land use/land cover (LULC) classification system, the development of a temporal transportation layer, the classification of anthropogenic cover types from the IKONOS imagery, a preliminary evaluation of landscape ecology metrics (quantification of spatial and temporal patterns of ecosystem structure and function with appropriate indices) and their utility in comparing two LULC systems, and a new initiative in community-based science and facilitation.

A comprehensive and quantitative exploration of thousands of viral genomes.

PubMed

Mahmoudabadi, Gita; Phillips, Rob

2018-04-19

The complete assembly of viral genomes from metagenomic datasets (short genomic sequences gathered from environmental samples) has proven to be challenging, so there are significant blind spots when we view viral genomes through the lens of metagenomics. One approach to overcoming this problem is to leverage the thousands of complete viral genomes that are publicly available. Here we describe our efforts to assemble a comprehensive resource that provides a quantitative snapshot of viral genomic trends - such as gene density, noncoding percentage, and abundances of functional gene categories - across thousands of viral genomes. We have also developed a coarse-grained method for visualizing viral genome organization for hundreds of genomes at once, and have explored the extent of the overlap between bacterial and bacteriophage gene pools. Existing viral classification systems were developed prior to the sequencing era, so we present our analysis in a way that allows us to assess the utility of the different classification systems for capturing genomic trends. © 2018, Mahmoudabadi et al.

Implementing the Biopharmaceutics Classification System in Drug Development: Reconciling Similarities, Differences, and Shared Challenges in the EMA and US-FDA-Recommended Approaches.

PubMed

Cardot, J-M; Garcia Arieta, A; Paixao, P; Tasevska, I; Davit, B

2016-07-01

The US-FDA recently posted a draft guideline for industry recommending procedures necessary to obtain a biowaiver for immediate-release oral dosage forms based on the Biopharmaceutics Classification System (BCS). This review compares the present FDA BCS biowaiver approach, with the existing European Medicines Agency (EMA) approach, with an emphasis on similarities, difficulties, and shared challenges. Some specifics of the current EMA BCS guideline are compared with those in the recently published draft US-FDA BCS guideline. In particular, similarities and differences in the EMA versus US-FDA approaches to establishing drug solubility, permeability, dissolution, and formulation suitability for BCS biowaiver are critically reviewed. Several case studies are presented to illustrate the (i) challenges of applying for BCS biowaivers for global registration in the face of differences in the EMA and US-FDA BCS biowaiver criteria, as well as (ii) challenges inherent in applying for BCS class I or III designation and common to both jurisdictions.

RRAM-based parallel computing architecture using k-nearest neighbor classification for pattern recognition

NASA Astrophysics Data System (ADS)

Jiang, Yuning; Kang, Jinfeng; Wang, Xinan

2017-03-01

Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.

The National Ecosystem Services Classification System: A Framework for Identifying and Reducing Relevant Uncertainties

NASA Astrophysics Data System (ADS)

Rhodes, C. R.; Sinha, P.; Amanda, N.

2013-12-01

In recent years the gap between what scientists know and what policymakers should appreciate in environmental decision making has received more attention, as the costs of the disconnect have become more apparent to both groups. Particularly for water-related policies, the EPA's Office of Water has struggled with benefit estimates held low by the inability to quantify ecological and economic effects that theory, modeling, and anecdotal or isolated case evidence suggest may prove to be larger. Better coordination with ecologists and hydrologists is being explored as a solution. The ecosystem services (ES) concept now nearly two decades old links ecosystem functions and processes to the human value system. But there remains no clear mapping of which ecosystem goods and services affect which individual or economic values. The National Ecosystem Services Classification System (NESCS, 'nexus') project brings together ecologists, hydrologists, and social scientists to do this mapping for aquatic and other ecosystem service-generating systems. The objective is to greatly reduce the uncertainty in water-related policy making by mapping and ultimately quantifying the various functions and products of aquatic systems, as well as how changes to aquatic systems impact the human economy and individual levels of non-monetary appreciation for those functions and products. Primary challenges to fostering interaction between scientists, social scientists, and policymakers are lack of a common vocabulary, and the need for a cohesive comprehensive framework that organizes concepts across disciplines and accommodates scientific data from a range of sources. NESCS builds the vocabulary and the framework so both may inform a scalable transdisciplinary policy-making application. This talk presents for discussion the process and progress in developing both this vocabulary and a classifying framework capable of bridging the gap between a newer but existing ecosystem services classification system, and a standardized industrial classification system. Our goal is to model then predict the effects of a policy choice on the environment, from impacts on ecological components and processes all the way through to endpoints in the human value chain.

IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

PubMed

Ali, Safdar; Majid, Abdul; Khan, Asifullah

2014-04-01

Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our analysis demonstrates that ensemble-RF, ensemble-SVM and ensemble-KNN are more effective than their individual counterparts. The proposed 'IDM-PhyChm-Ens' method has shown improved performance compared to existing techniques.

The comprehensiveness of the ESHRE/ESGE classification of female genital tract congenital anomalies: a systematic review of cases not classified by the AFS system

PubMed Central

Di Spiezio Sardo, A.; Campo, R.; Gordts, S.; Spinelli, M.; Cosimato, C.; Tanos, V.; Brucker, S.; Li, T. C.; Gergolet, M.; De Angelis, C.; Gianaroli, L.; Grimbizis, G.

2015-01-01

STUDY QUESTION How comprehensive is the recently published European Society of Human Reproduction and Embryology (ESHRE)/European Society for Gynaecological Endoscopy (ESGE) classification system of female genital anomalies? SUMMARY ANSWER The ESHRE/ESGE classification provides a comprehensive description and categorization of almost all of the currently known anomalies that could not be classified properly with the American Fertility Society (AFS) system. WHAT IS KNOWN ALREADY Until now, the more accepted classification system, namely that of the AFS, is associated with serious limitations in effective categorization of female genital anomalies. Many cases published in the literature could not be properly classified using the AFS system, yet a clear and accurate classification is a prerequisite for treatment. STUDY DESIGN, SIZE AND DURATION The CONUTA (CONgenital UTerine Anomalies) ESHRE/ESGE group conducted a systematic review of the literature to examine if those types of anomalies that could not be properly classified with the AFS system could be effectively classified with the use of the new ESHRE/ESGE system. An electronic literature search through Medline, Embase and Cochrane library was carried out from January 1988 to January 2014. Three participants independently screened, selected articles of potential interest and finally extracted data from all the included studies. Any disagreement was discussed and resolved after consultation with a fourth reviewer and the results were assessed independently and approved by all members of the CONUTA group. PARTICIPANTS/MATERIALS, SETTING, METHODS Among the 143 articles assessed in detail, 120 were finally selected reporting 140 cases that could not properly fit into a specific class of the AFS system. Those 140 cases were clustered in 39 different types of anomalies. MAIN RESULTS AND THE ROLE OF CHANCE The congenital anomaly involved a single organ in 12 (30.8%) out of the 39 types of anomalies, while multiple organs and/or segments of Müllerian ducts (complex anomaly) were involved in 27 (69.2%) types. Uterus was the organ most frequently involved (30/39: 76.9%), followed by cervix (26/39: 66.7%) and vagina (23/39: 59%). In all 39 types, the ESHRE/ESGE classification system provided a comprehensive description of each single or complex anomaly. A precise categorization was reached in 38 out of 39 types studied. Only one case of a bizarre uterine anomaly, with no clear embryological defect, could not be categorized and thus was placed in Class 6 (un-classified) of the ESHRE/ESGE system. LIMITATIONS, REASONS FOR CAUTION The review of the literature was thorough but we cannot rule out the possibility that other defects exist which will also require testing in the new ESHRE/ESGE system. These anomalies, however, must be rare. WIDER IMPLICATIONS OF THE FINDINGS The comprehensiveness of the ESHRE/ESGE classification adds objective scientific validity to its use. This may, therefore, promote its further dissemination and acceptance, which will have a positive outcome in clinical care and research. STUDY FUNDING/COMPETING INTEREST(S) None. PMID:25788565

Second-degree atrioventricular block.

PubMed

Zipes, D P

1979-09-01

1) While it is possible only one type of second-degree AV block exists electrophysiologically, the available data do not justify such a conclusion and it would seem more appropriate to remain a "splitter," and advocate separation and definition of multiple mechanisms, than to be a "lumper," and embrace a unitary concept. 2) The clinical classification of type I and type II AV block, based on present scalar electrocardiographic criteria, for the most part accurately differentiates clinically important categories of patients. Such a classification is descriptive, but serves a useful function and should be preserved, taking into account the caveats mentioned above. The site of block generally determines the clinical course for the patient. For most examples of AV block, the type I and type II classification in present use is based on the site of block. Because block in the His-Purkinje system is preceded by small or nonmeasurable increments, it is called type II AV block; but the very fact that it is preceded by small increments is because it occurs in the His-Purkinje system. Similar logic can be applied to type I AV block in the AV node. Exceptions do occur. If the site of AV block cannot be distinguished with certainity from the scalar ECG, an electrophysiologic study will generally reveal the answer.

Machine-learning-based Brokers for Real-time Classification of the LSST Alert Stream

NASA Astrophysics Data System (ADS)

Narayan, Gautham; Zaidi, Tayeb; Soraisam, Monika D.; Wang, Zhe; Lochner, Michelle; Matheson, Thomas; Saha, Abhijit; Yang, Shuo; Zhao, Zhenge; Kececioglu, John; Scheidegger, Carlos; Snodgrass, Richard T.; Axelrod, Tim; Jenness, Tim; Maier, Robert S.; Ridgway, Stephen T.; Seaman, Robert L.; Evans, Eric Michael; Singh, Navdeep; Taylor, Clark; Toeniskoetter, Jackson; Welch, Eric; Zhu, Songzhe; The ANTARES Collaboration

2018-05-01

The unprecedented volume and rate of transient events that will be discovered by the Large Synoptic Survey Telescope (LSST) demand that the astronomical community update its follow-up paradigm. Alert-brokers—automated software system to sift through, characterize, annotate, and prioritize events for follow-up—will be critical tools for managing alert streams in the LSST era. The Arizona-NOAO Temporal Analysis and Response to Events System (ANTARES) is one such broker. In this work, we develop a machine learning pipeline to characterize and classify variable and transient sources only using the available multiband optical photometry. We describe three illustrative stages of the pipeline, serving the three goals of early, intermediate, and retrospective classification of alerts. The first takes the form of variable versus transient categorization, the second a multiclass typing of the combined variable and transient data set, and the third a purity-driven subtyping of a transient class. Although several similar algorithms have proven themselves in simulations, we validate their performance on real observations for the first time. We quantitatively evaluate our pipeline on sparse, unevenly sampled, heteroskedastic data from various existing observational campaigns, and demonstrate very competitive classification performance. We describe our progress toward adapting the pipeline developed in this work into a real-time broker working on live alert streams from time-domain surveys.

European initiative for the application of the International Classification of Service Organization in Health-related Rehabilitation (ICSO-R).

PubMed

Kiekens, Carlotte; Meyer, Thorsten; Gimigliano, Francesca; Baffone, Cristiana; Gutenbrunner, Christoph M

2017-04-01

The International Classification of Functioning, Disability and Health (ICF) should be used as the framework for the development of a clinical assessment schedule for clinical quality management of health-related rehabilitation services. For the description of rehabilitation services a working group of the ISPRM-WHO-Liaison Committee proposed an instrument called "International Classification System for Service Organization in Health-related Rehabilitation" or ICSO-R. To test the applicability and feasibility of ICSO-R to describe rehabilitation services and to propose further improvements. A workshop was held. SPF (Swiss Paraplegic Research) in Nottwil, January 2016. Six working groups, composed of delegates from UEMS PRM (Physical and Rehabilitation Medicine Section and Board of the European Union of Medical Specialists) and experts from other rehabilitation professions. Each working group selected an existing service of a predefined category (one acute, three post-acute and two long-term rehabilitation services). The instructions were: 1) make a narrative description of an exemplary service; 2) describe the exemplary service using the dimensions and categories of ICSO-R; 3) comment on feasibility of the ICSO-R table, on shortcomings, and make suggestions for improvement. The narrative and ICSO-R descriptions were analyzed and compared, and recommendations were made for modification of ICSO-R. The narratives were very heterogeneous and none comparable. ICSO-R use was feasible and significantly increased precision and comparability of the descriptions of existing rehabilitation services. Proposals for improvement were made, for example the addition of lacking categories. Suggestions were made for clarification of a number of characteristics, including a taxonomy with value sets. The UEMS PRM workshop on the description of health-related rehabilitation services for use in a clinical quality management schedule clearly demonstrated feasibility and applicability of ICSO-R, showing more precise and comparable descriptions as compared to the narratives. However, in a next version some modifications should be made to improve clarity. It is recommended to use ICSO-R to describe and compare existing as well as model rehabilitation services for benchmarking and implementation into health systems worldwide. The ISPRM-WHO Liaison committee working group will further modify and improve ICSO-R.

How should children with speech sound disorders be classified? A review and critical evaluation of current classification systems.

PubMed

Waring, R; Knight, R

2013-01-01

Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of theoretically differing classification systems have been proposed based on either an aetiological (medical) approach, a descriptive-linguistic approach or a processing approach. To describe and review the supporting evidence, and to provide a critical evaluation of the current childhood SSD classification systems. Descriptions of the major specific approaches to classification are reviewed and research papers supporting the reliability and validity of the systems are evaluated. Three specific paediatric SSD classification systems; the aetiologic-based Speech Disorders Classification System, the descriptive-linguistic Differential Diagnosis system, and the processing-based Psycholinguistic Framework are identified as potentially useful in classifying children with SSD into homogeneous subgroups. The Differential Diagnosis system has a growing body of empirical support from clinical population studies, across language error pattern studies and treatment efficacy studies. The Speech Disorders Classification System is currently a research tool with eight proposed subgroups. The Psycholinguistic Framework is a potential bridge to linking cause and surface level speech errors. There is a need for a universally agreed-upon classification system that is useful to clinicians and researchers. The resulting classification system needs to be robust, reliable and valid. A universal classification system would allow for improved tailoring of treatments to subgroups of SSD which may, in turn, lead to improved treatment efficacy. © 2012 Royal College of Speech and Language Therapists.

Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals.

PubMed

Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Mubin, Marizan; Saad, Ismail

2016-01-01

In the existing electroencephalogram (EEG) signals peak classification research, the existing models, such as Dumpala, Acir, Liu, and Dingle peak models, employ different set of features. However, all these models may not be able to offer good performance for various applications and it is found to be problem dependent. Therefore, the objective of this study is to combine all the associated features from the existing models before selecting the best combination of features. A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. Also, the neural network random weight method is utilized in the proposed AMSKF technique as a classifier. In the conducted experiment, 11,781 samples of peak candidate are employed in this study for the validation purpose. The samples are collected from three different peak event-related EEG signals of 30 healthy subjects; (1) single eye blink, (2) double eye blink, and (3) eye movement signals. The experimental results have shown that the proposed AMSKF feature selector is able to find the best combination of features and performs at par with the existing related studies of epileptic EEG events classification.

5 CFR 9701.231 - Conversion of positions and employees to the DHS classification system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... the DHS classification system. 9701.231 Section 9701.231 Administrative Personnel DEPARTMENT OF... MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Transitional Provisions § 9701.231 Conversion of positions and employees to the DHS classification system. (a) This...

A proposed classification scheme for Ada-based software products

NASA Technical Reports Server (NTRS)

Cernosek, Gary J.

1986-01-01

As the requirements for producing software in the Ada language become a reality for projects such as the Space Station, a great amount of Ada-based program code will begin to emerge. Recognizing the potential for varying levels of quality to result in Ada programs, what is needed is a classification scheme that describes the quality of a software product whose source code exists in Ada form. A 5-level classification scheme is proposed that attempts to decompose this potentially broad spectrum of quality which Ada programs may possess. The number of classes and their corresponding names are not as important as the mere fact that there needs to be some set of criteria from which to evaluate programs existing in Ada. An exact criteria for each class is not presented, nor are any detailed suggestions of how to effectively implement this quality assessment. The idea of Ada-based software classification is introduced and a set of requirements from which to base further research and development is suggested.

Cases of Coastal Zone Change and Land Use/Land Cover Change: a learning module that goes beyond the "how" of doing image processing and change detection to asking the "why" about what are the "driving forces" of global change.

NASA Astrophysics Data System (ADS)

Ford, R. E.

2006-12-01

In 2006 the Loma Linda University ESSE21 Mesoamerican Project (Earth System Science Education for the 21st Century) along with partners such as the University of Redlands and California State University, Pomona, produced an online learning module that is designed to help students learn critical remote sensing skills-- specifically: ecosystem characterization, i.e. doing a supervised or unsupervised classification of satellite imagery in a tropical coastal environment. And, it would teach how to measure land use / land cover change (LULC) over time and then encourage students to use that data to assess the Human Dimensions of Global Change (HDGC). Specific objectives include: 1. Learn where to find remote sensing data and practice downloading, pre-processing, and "cleaning" the data for image analysis. 2. Use Leica-Geosystems ERDAS Imagine or IDRISI Kilimanjaro to analyze and display the data. 3. Do an unsupervised classification of a LANDSAT image of a protected area in Honduras, i.e. Cuero y Salado, Pico Bonito, or Isla del Tigre. 4. Virtually participate in a ground-validation exercise that would allow one to re-classify the image into a supervised classification using the FAO Global Land Cover Network (GLCN) classification system. 5. Learn more about each protected area's landscape, history, livelihood patterns and "sustainability" issues via virtual online tours that provide ground and space photos of different sites. This will help students in identifying potential "training sites" for doing a supervised classification. 6. Study other global, US, Canadian, and European land use/land cover classification systems and compare their advantages and disadvantages over the FAO/GLCN system. 7. Learn to appreciate the advantages and disadvantages of existing LULC classification schemes and adapt them to local-level user needs. 8. Carry out a change detection exercise that shows how land use and/or land cover has changed over time for the protected area of your choice. The presenter will demonstrate the module, assess the collaborative process which created it, and describe how it has been used so far by users in the US as well as in Honduras and elsewhere via a series joint workshops held in Mesoamerica. Suggestions for improvement will be requested. See the module and related content resources at: http://resweb.llu.edu/rford/ESSE21/LUCCModule/

12 CFR 403.7 - Mandatory review for declassification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... of a request by a United States citizen or permanent resident alien, a Federal agency, or a State or... material on grounds other than classification. (i) The Bank shall refuse to confirm or deny the existence or non-existence of requested information whenever the fact of its existence or non-existence is...

12 CFR 403.7 - Mandatory review for declassification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... of a request by a United States citizen or permanent resident alien, a Federal agency, or a State or... material on grounds other than classification. (i) The Bank shall refuse to confirm or deny the existence or non-existence of requested information whenever the fact of its existence or non-existence is...

12 CFR 403.7 - Mandatory review for declassification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... of a request by a United States citizen or permanent resident alien, a Federal agency, or a State or... material on grounds other than classification. (i) The Bank shall refuse to confirm or deny the existence or non-existence of requested information whenever the fact of its existence or non-existence is...

12 CFR 403.7 - Mandatory review for declassification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... of a request by a United States citizen or permanent resident alien, a Federal agency, or a State or... material on grounds other than classification. (i) The Bank shall refuse to confirm or deny the existence or non-existence of requested information whenever the fact of its existence or non-existence is...

Email recruitment to use web decision support tools for pneumonia.

PubMed

Flanagan, James R; Peterson, Michael; Dayton, Charles; Strommer Pace, Lori; Plank, Andrew; Walker, Kristy; Carlson, William S

2002-01-01

Application of guidelines to improve clinical decisions for Community Acquired Pneumonia (CAP) patients depends on accurate information about specific facts of each case and on presenting guideline support at the time decisions are being made. We report here on a system designed to solicit information from physicians about their CAP patients in order to classify CAP and present appropriate guidelines for type of care, length of stay, and use of antibiotics. We used elements of three existing information systems to create a achieve these goals: professionals coding diagnoses captured by the existing clinical information system (CIS), email, and web-based decision support tools including a pneumonia severity evaluation tool (SET). The non-secure IS components (email and web) were able to link to information in the CIS using tokens that do not reveal confidential patient-identifiable information. We examined their response to this strategy and the accuracy of pneumonia classification using this approach compared to chart review as a gold standard. On average physicians responded to email solicitations 50% of the time over the 14 month study. Also using this standard, we examined various information triggers for case finding. Professional coding of the primary reason for admission as pneumonia was fairly sensitive as an indicator of CAP. Physician use of the web SET was insensitive but fairly specific. Pneumonia classification using the SET was very reliable compared to experts' chart review using the same algorithm. We examined the distribution of severity of pneumonia for cases of pneumonia found by the various information triggers and for each severity the average length of stay. The distribution found by both chart review and by SET has demonstrated a shift toward more severe cases being admitted compared to only 3 years ago. The length of stay for level of severity is above expectations published by guidelines even for cases of true CAP by chart review. We suggest that the Fine classification system may not adequately describe patients in this setting. Physicians frequently responded that the guidelines presented did not fit their patients.

Efficient Multi-Concept Visual Classifier Adaptation in Changing Environments

DTIC Science & Technology

2016-09-01

yet to be discussed in existing supervised multi-concept visual perception systems used in robotics applications.1,5–7 Anno - tation of images is...Autonomous robot navigation in highly populated pedestrian zones. J Field Robotics. 2015;32(4):565–589. 3. Milella A, Reina G, Underwood J . A self...learning framework for statistical ground classification using RADAR and monocular vision. J Field Robotics. 2015;32(1):20–41. 4. Manjanna S, Dudek G

Empirical Evaluation of Advanced Electromagnetic Induction Systems - Factors Affecting Classification Effectiveness in Challenging Geologic Environments

DTIC Science & Technology

2017-02-01

because of a variety of challenging conditions including (but not limited to) dense woods, long travel times to and from the site, and TEMTADS software...the following reasons: • Approximately 1.5 hours of travel time was needed after reaching the site each day to access the collection grids. • Daily...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining

Classification of Martian deltas

NASA Technical Reports Server (NTRS)

Dehon, R. A.

1993-01-01

Water-borne sediments in streams are deposited, upon eventual cessation of flow, either as deltas or as alluvial fans or plains. Deltas and alluvial fans share a common characteristic; both may be described as deposition Al plains at the mouth of a river or stream. A delta is formed where a stream or river deposits its sedimentary load into a standing body of water such as an ocean or lake. An alluvial fan is produced where a stream loses capacity by a greatly decreased gradient. A delta has subaerial and subaqueous components, but an alluvial fan is entirely subaerial. In terrestrial conditions, deltas and alluvial fans are reasonably distinct landforms. The juxtaposition of concomitant features composition and internal structure are sufficiently explicit as to avoid any confusion regarding their proper identification on Mars, the recognition of deltas and their distinction from alluvial fans is made difficult by low resolution imaging. Further, although it may be demonstrated that standing bodies of water existed on the surface of Mars, many of these bodies may have existed for extremely short periods of time (a few days to months); hence, distinctive shoreline features were not developed. Thus, in an attempt to derive a Martian classification of deltas, the inclusion of wholly subaerial deposits may be unavoidable. A simple, broad, morphological classification of Martian deltas, primarily on planimetric shape, includes digitate deltas, fan-shaped deltas, and re-entrant deltas. A fourth, somewhat problematical class includes featureless plains at the end of many valley systems.

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives.

PubMed

Algamal, Z Y; Lee, M H

2017-01-01

A high-dimensional quantitative structure-activity relationship (QSAR) classification model typically contains a large number of irrelevant and redundant descriptors. In this paper, a new design of descriptor selection for the QSAR classification model estimation method is proposed by adding a new weight inside L1-norm. The experimental results of classifying the anti-hepatitis C virus activity of thiourea derivatives demonstrate that the proposed descriptor selection method in the QSAR classification model performs effectively and competitively compared with other existing penalized methods in terms of classification performance on both the training and the testing datasets. Moreover, it is noteworthy that the results obtained in terms of stability test and applicability domain provide a robust QSAR classification model. It is evident from the results that the developed QSAR classification model could conceivably be employed for further high-dimensional QSAR classification studies.

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing.

PubMed

Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina

2016-12-01

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning.

PubMed

Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-01-01

This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the diseased region in brain MR images. Two-dimensional stationary wavelet transform is harnessed to extract features from the preprocessed images. The feature vector is constructed using the energy and entropy values, computed from the level- 2 SWT coefficients. Then, the relevant and uncorrelated features are selected using symmetric uncertainty ranking filter. Subsequently, the selected features are given input to the proposed AdaBoost with support vector machine classifier, where SVM is used as the base classifier of AdaBoost algorithm. To validate the proposed system, three standard MR image datasets, Dataset-66, Dataset-160, and Dataset- 255 have been utilized. The 5 runs of k-fold stratified cross validation results indicate the suggested scheme offers better performance than other existing schemes in terms of accuracy and number of features. The proposed system earns ideal classification over Dataset-66 and Dataset-160; whereas, for Dataset- 255, an accuracy of 99.45% is achieved. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Investigation of cloud/water vapor motion winds from geostationary satellite

NASA Technical Reports Server (NTRS)

Nieman, Steve; Velden, Chris; Hayden, Kit; Menzel, Paul

1993-01-01

Work has been primarily focussed on three tasks: (1) comparison of wind fields produced at MSFC with the CO2 autowind/autoeditor system newly installed in NESDIS operations; (2) evaluation of techniques for improved tracer selection through use of cloud classification predictors; and (3) development of height assignment algorithm with water vapor channel radiances. The contract goal is to improve the CIMSS wind system by developing new techniques and assimilating better existing techniques. The work reported here was done in collaboration with the NESDIS scientists working on the operational winds software, so that NASA funded research can benefit NESDIS operational algorithms.

Performance Evaluation of State of the Art Systems for Physical Activity Classification of Older Subjects Using Inertial Sensors in a Real Life Scenario: A Benchmark Study

PubMed Central

Awais, Muhammad; Palmerini, Luca; Bourke, Alan K.; Ihlen, Espen A. F.; Helbostad, Jorunn L.; Chiari, Lorenzo

2016-01-01

The popularity of using wearable inertial sensors for physical activity classification has dramatically increased in the last decade due to their versatility, low form factor, and low power requirements. Consequently, various systems have been developed to automatically classify daily life activities. However, the scope and implementation of such systems is limited to laboratory-based investigations. Furthermore, these systems are not directly comparable, due to the large diversity in their design (e.g., number of sensors, placement of sensors, data collection environments, data processing techniques, features set, classifiers, cross-validation methods). Hence, the aim of this study is to propose a fair and unbiased benchmark for the field-based validation of three existing systems, highlighting the gap between laboratory and real-life conditions. For this purpose, three representative state-of-the-art systems are chosen and implemented to classify the physical activities of twenty older subjects (76.4 ± 5.6 years). The performance in classifying four basic activities of daily life (sitting, standing, walking, and lying) is analyzed in controlled and free living conditions. To observe the performance of laboratory-based systems in field-based conditions, we trained the activity classification systems using data recorded in a laboratory environment and tested them in real-life conditions in the field. The findings show that the performance of all systems trained with data in the laboratory setting highly deteriorates when tested in real-life conditions, thus highlighting the need to train and test the classification systems in the real-life setting. Moreover, we tested the sensitivity of chosen systems to window size (from 1 s to 10 s) suggesting that overall accuracy decreases with increasing window size. Finally, to evaluate the impact of the number of sensors on the performance, chosen systems are modified considering only the sensing unit worn at the lower back. The results, similarly to the multi-sensor setup, indicate substantial degradation of the performance when laboratory-trained systems are tested in the real-life setting. This degradation is higher than in the multi-sensor setup. Still, the performance provided by the single-sensor approach, when trained and tested with real data, can be acceptable (with an accuracy above 80%). PMID:27973434

High-performance computer aided detection system for polyp detection in CT colonography with fluid and fecal tagging

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Wang, Shijun; Kabadi, Suraj; Summers, Ronald M.

2009-02-01

CT colonography (CTC) is a feasible and minimally invasive method for the detection of colorectal polyps and cancer screening. Computer-aided detection (CAD) of polyps has improved consistency and sensitivity of virtual colonoscopy interpretation and reduced interpretation burden. A CAD system typically consists of four stages: (1) image preprocessing including colon segmentation; (2) initial detection generation; (3) feature selection; and (4) detection classification. In our experience, three existing problems limit the performance of our current CAD system. First, highdensity orally administered contrast agents in fecal-tagging CTC have scatter effects on neighboring tissues. The scattering manifests itself as an artificial elevation in the observed CT attenuation values of the neighboring tissues. This pseudo-enhancement phenomenon presents a problem for the application of computer-aided polyp detection, especially when polyps are submerged in the contrast agents. Second, general kernel approach for surface curvature computation in the second stage of our CAD system could yield erroneous results for thin structures such as small (6-9 mm) polyps and for touching structures such as polyps that lie on haustral folds. Those erroneous curvatures will reduce the sensitivity of polyp detection. The third problem is that more than 150 features are selected from each polyp candidate in the third stage of our CAD system. These high dimensional features make it difficult to learn a good decision boundary for detection classification and reduce the accuracy of predictions. Therefore, an improved CAD system for polyp detection in CTC data is proposed by introducing three new techniques. First, a scale-based scatter correction algorithm is applied to reduce pseudo-enhancement effects in the image pre-processing stage. Second, a cubic spline interpolation method is utilized to accurately estimate curvatures for initial detection generation. Third, a new dimensionality reduction classifier, diffusion map and local linear embedding (DMLLE), is developed for classification and false positives (FP) reduction. Performance of the improved CAD system is evaluated and compared with our existing CAD system (without applying those techniques) using CT scans of 1186 patients. These scans are divided into a training set and a test set. The sensitivity of the improved CAD system increased 18% on training data at a rate of 5 FPs per patient and 15% on test data at a rate of 5 FPs per patient. Our results indicated that the improved CAD system achieved significantly better performance on medium-sized colonic adenomas with higher sensitivity and lower FP rate in CTC.

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes

PubMed Central

2012-01-01

Background Precise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification. Results On the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc. Conclusions Our results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information. PMID:22800292

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes.

PubMed

Malhotra, Sony; Sowdhamini, Ramanathan

2012-07-16

Precise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification. On the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc. Our results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information.

Evaluation of Hydrometeor Classification for Winter Mixed-Phase Precipitation Events

NASA Astrophysics Data System (ADS)

Hickman, B.; Troemel, S.; Ryzhkov, A.; Simmer, C.

2016-12-01

Hydrometeor classification algorithms (HCL) typically discriminate radar echoes into several classes including rain (light, medium, heavy), hail, dry snow, wet snow, ice crystals, graupel and rain-hail mixtures. Despite the strength of HCL for precipitation dominated by a single phase - especially warm-season classification - shortcomings exist for mixed-phase precipitation classification. Properly identifying mixed-phase can lead to more accurate precipitation estimates, and better forecasts for aviation weather and ground warnings. Cold season precipitation classification is also highly important due to their potentially high impact on society (e.g. black ice, ice accumulation, snow loads), but due to the varying nature of the hydrometeor - density, dielectric constant, shape - reliable classification via radar alone is not capable. With the addition of thermodynamic information of the atmosphere, either from weather models or sounding data, it has been possible to extend more and more into winter time precipitation events. Yet, inaccuracies still exist in separating more benign (ice pellets) from more the more hazardous (freezing rain) events. We have investigated winter mixed-phase precipitation cases which include freezing rain, ice pellets, and rain-snow transitions from several events in Germany in order to move towards a reliable nowcasting of winter precipitation in hopes to provide faster, more accurate winter time warnings. All events have been confirmed to have the specified precipitation from ground reports. Classification of the events is achieved via a combination of inputs from a bulk microphysics numerical weather prediction model and the German dual-polarimetric C-band radar network, into a 1D spectral bin microphysical model (SBC) which explicitly treats the processes of melting, refreezing, and ice nucleation to predict four near-surface precipitation types: rain, snow, freezing rain, ice pellets, rain/snow mixture, and freezing rain/pellet mixture. Evaluation of the classification is performed by means of disdrometer data, in-situ ground observations, and eye-witness reports from the European Severe Weather Database (ESWD). Additionally, a comparison to an existing radar based HCL is performed as a sanity check and a performance evaluator.

Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection

NASA Astrophysics Data System (ADS)

Sakuma, Jun; Wright, Rebecca N.

Privacy-preserving classification is the task of learning or training a classifier on the union of privately distributed datasets without sharing the datasets. The emphasis of existing studies in privacy-preserving classification has primarily been put on the design of privacy-preserving versions of particular data mining algorithms, However, in classification problems, preprocessing and postprocessing— such as model selection or attribute selection—play a prominent role in achieving higher classification accuracy. In this paper, we show generalization error of classifiers in privacy-preserving classification can be securely evaluated without sharing prediction results. Our main technical contribution is a new generalized Hamming distance protocol that is universally applicable to preprocessing and postprocessing of various privacy-preserving classification problems, such as model selection in support vector machine and attribute selection in naive Bayes classification.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

75 FR 23824 - New Postal Products

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-04

... of Classification Change to Add Existing Shipping Charges to the Mail Classification Schedule for... Form 3202-X, October 2009). Id., Attachment A. The Postal Service states further its belief that the... MCS.\\2\\ Attachment B to the Notice shows the proposed changes to the Stamped Envelope MCS language in...

40 CFR 256.23 - Requirements for closing or upgrading open dumps.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) SOLID WASTES GUIDELINES FOR DEVELOPMENT AND IMPLEMENTATION OF STATE SOLID WASTE MANAGEMENT PLANS Solid... classification of existing solid waste disposal facilities according to the criteria. This classification shall... solid waste disposal facility; (2) The availability of State regulatory and enforcement powers; and (3...

40 CFR 256.23 - Requirements for closing or upgrading open dumps.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) SOLID WASTES GUIDELINES FOR DEVELOPMENT AND IMPLEMENTATION OF STATE SOLID WASTE MANAGEMENT PLANS Solid... classification of existing solid waste disposal facilities according to the criteria. This classification shall... solid waste disposal facility; (2) The availability of State regulatory and enforcement powers; and (3...

Comparative study of classification algorithms for immunosignaturing data

PubMed Central

2012-01-01

Background High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data. Results We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy. Conclusions ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties. PMID:22720696

Application of Neural Networks for classification of Patau, Edwards, Down, Turner and Klinefelter Syndrome based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics.

PubMed

Catic, Aida; Gurbeta, Lejla; Kurtovic-Kozaric, Amina; Mehmedbasic, Senad; Badnjevic, Almir

2018-02-13

The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good approximates of complex functions, so classification can be performed without the need for explicitly defined input-output model. This engineering tool can be applied for optimization of existing methods for disease/syndrome classification. Cytogenetic and molecular analyses are the most frequent tests used in prenatal diagnostic for the early detection of Turner, Klinefelter, Patau, Edwards and Down syndrome. These procedures can be lengthy, repetitive; and often employ invasive techniques so a robust automated method for classifying and reporting prenatal diagnostics would greatly help the clinicians with their routine work. The database consisted of data collected from 2500 pregnant woman that came to the Institute of Gynecology, Infertility and Perinatology "Mehmedbasic" for routine antenatal care between January 2000 and December 2016. During first trimester all women were subject to screening test where values of maternal serum pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotropin (β-hCG) were measured. Also, fetal nuchal translucency thickness and the presence or absence of the nasal bone was observed using ultrasound. The architectures of linear feedforward and feedback neural networks were investigated for various training data distributions and number of neurons in hidden layer. Feedback neural network architecture out performed feedforward neural network architecture in predictive ability for all five aneuploidy prenatal syndrome classes. Feedforward neural network with 15 neurons in hidden layer achieved classification sensitivity of 92.00%. Classification sensitivity of feedback (Elman's) neural network was 99.00%. Average accuracy of feedforward neural network was 89.6% and for feedback was 98.8%. The results presented in this paper prove that an expert diagnostic system based on neural networks can be efficiently used for classification of five aneuploidy syndromes, covered with this study, based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics. Developed Expert System proved to be simple, robust, and powerful in properly classifying prenatal aneuploidy syndromes.

Employing the International Classification of Functioning, Disability and Health framework to capture user feedback in the design and testing stage of development of home-based arm rehabilitation technology.

PubMed

Sivan, Manoj; Gallagher, Justin; Holt, Ray; Weightman, Andrew; O'Connor, Rory; Levesley, Martin

2016-01-01

The purpose of this study was to evaluate the International Classification of Functioning, Disability and Health (ICF) as a framework to ensure that key aspects of user feedback are identified in the design and testing stages of development of a home-based upper limb rehabilitation system. Seventeen stroke survivors with residual upper limb weakness, and seven healthcare professionals with expertise in stroke rehabilitation, were enrolled in the user-centered design process. Through semi-structured interviews, they provided feedback on the hardware, software and impact of a home-based rehabilitation device to facilitate self-managed arm exercise. Members of the multidisciplinary clinical and engineering research team, based on previous experience and existing literature in user-centred design, developed the topic list for the interviews. Meaningful concepts were extracted from participants' interviews based on existing ICF linking rules and matched to categories within the ICF Comprehensive Core Set for stroke. Most of the interview concepts (except personal factors) matched the existing ICF Comprehensive Core Set categories. Personal factors that emerged from interviews e.g. gender, age, interest, compliance, motivation, choice and convenience that might determine device usability are yet to be categorised within the ICF framework and hence could not be matched to a specific Core Set category.

The Semantic Management of Environmental Resources within the Interoperable Context of the EuroGEOSS: Alignment of GEMET and the GEOSS SBAs

NASA Astrophysics Data System (ADS)

Cialone, Claudia; Stock, Kristin

2010-05-01

EuroGEOSS is a European Commission funded project. It aims at improving a scientific understanding of the complex mechanisms which drive changes affecting our planet, identifying and establishing interoperable arrangements between environmental information systems. These systems would be sustained and operated by organizations with a clear mandate and resources and rendered available following the specifications of already existent frameworks such as GEOSS (the Global Earth Observation System of systems)1 and INSPIRE (the Infrastructure for Spatial Information in the European Community)2. The EuroGEOSS project's infrastructure focuses on three thematic areas: forestry, drought and biodiversity. One of the important activities in the project is the retrieval, parsing and harmonization of the large amount of heterogeneous environmental data available at local, regional and global levels between these strategic areas. The challenge is to render it semantically and technically interoperable in a simple way. An initial step in achieving this semantic and technical interoperability involves the selection of appropriate classification schemes (for example, thesauri, ontologies and controlled vocabularies) to describe the resources in the EuroGEOSS framework. These classifications become a crucial part of the interoperable framework scaffolding because they allow data providers to describe their resources and thus support resource discovery, execution and orchestration of varying levels of complexity. However, at present, given the diverse range of environmental thesauri, controlled vocabularies and ontologies and the large number of resources provided by project participants, the selection of appropriate classification schemes involves a number of considerations. First of all, there is the semantic difficulty of selecting classification schemes that contain concepts that are relevant to each thematic area. Secondly, EuroGEOSS is intended to accommodate a number of existing environmental projects (for example, GEOSS and INSPIRE). This requirement imposes constraints on the selection. Thirdly, the selected classification scheme or group of schemes (if more than one) must be capable of alignment (establishing different kinds of mappings between concepts, hence preserving intact the original knowledge schemes) or merging (the creation of another unique ontology from the original ontological sources) (Pérez-Gómez et al., 2004). Last but not least, there is the issue of including multi-lingual schemes that are based on free, open standards (non-proprietary). Using these selection criteria, we aim to support open and convenient data discovery and exchange for users who speak different languages (particularly the European ones for the broad scopes of EuroGEOSS). In order to support the project, we have developed a solution that employs two classification schemes: the Societal Benefit Areas (SBAs)3: the upper-level environmental categorization developed for the GEOSS project and the GEneral Multilingual Environmental Thesaurus (GEMET)4: a general environmental thesaurus whose conceptual structure has already been integrated with the spatial data themes proposed by the INSPIRE project. The former seems to provide the spatial data keywords relevant to the INSPIRE's Directive (JRC, 2008). In this way, we provide users with a basic set of concepts to support resource description and discovery in the thematic areas while supporting the requirements of INSPIRE and GEOSS. Furthermore, the use of only two classification schemes together with the fact that the SBAs are very general categories while GEMET includes much more detailed, yet still top-level, concepts, makes alignment an achievable task. Alignment was selected over merging because it leaves the existing classification schemes intact and requires only a simple activity of defining mappings from GEMET to the SBAs. In order to accomplish this task we are developing a simple, automated, open-source application to assist thematic experts in defining the mappings between concepts in the two classification schemes. The application will then generate SKOS mappings (exactMatch, closeMatch, broadMatch, narrowMatch, relatedMatch) based on thematic expert selections between the concepts in GEMET with the SBAs (including both the general Societal Benefit Areas and their subcategories). Once these mappings are defined and the SKOS files generated, resource providers will be able to select concepts from either GEMET or the SBAs (or a mixture) to describe their resources, and discovery approaches will support selection of concepts from either classification scheme, also returning results classified using the other scheme. While the focus of our work has been on the SBAs and GEMET, we also plan to provide a method for resource providers to further extend the semantic infrastructure by defining alignments to new classification schemes if these are required to support particular specialized thematic areas that are not covered by GEMET. In this way, the approach is flexible and suited to the general scope of EuroGEOSS, allowing specialists to increase at will the level of semantic quality and specificity of data to the initial infrastructural skeleton of the project. References ____________________________________________ Joint research Centre (JRC), 2008. INSPIRE Metadata Editor User Guide Pérez-Gómez A., Fernandez-Lopez M., Corcho O. Ontological engineering: With Examples from the Areas of Knowledge Management, e-Commerce and the Semantic Web.Spinger: London, 2004

The ABAG biogenic emissions inventory project

NASA Technical Reports Server (NTRS)

Carson-Henry, C. (Editor)

1982-01-01

The ability to identify the role of biogenic hydrocarbon emissions in contributing to overall ozone production in the Bay Area, and to identify the significance of that role, were investigated in a joint project of the Association of Bay Area Governments (ABAG) and NASA/Ames Research Center. Ozone, which is produced when nitrogen oxides and hydrocarbons combine in the presence of sunlight, is a primary factor in air quality planning. In investigating the role of biogenic emissions, this project employed a pre-existing land cover classification to define areal extent of land cover types. Emission factors were then derived for those cover types. The land cover data and emission factors were integrated into an existing geographic information system, where they were combined to form a Biogenic Hydrocarbon Emissions Inventory. The emissions inventory information was then integrated into an existing photochemical dispersion model.

Creating a behavioural classification module for acceleration data: using a captive surrogate for difficult to observe species.

PubMed

Campbell, Hamish A; Gao, Lianli; Bidder, Owen R; Hunter, Jane; Franklin, Craig E

2013-12-15

Distinguishing specific behavioural modes from data collected by animal-borne tri-axial accelerometers can be a time-consuming and subjective process. Data synthesis can be further inhibited when the tri-axial acceleration data cannot be paired with the corresponding behavioural mode through direct observation. Here, we explored the use of a tame surrogate (domestic dog) to build a behavioural classification module, and then used that module to accurately identify and quantify behavioural modes within acceleration collected from other individuals/species. Tri-axial acceleration data were recorded from a domestic dog whilst it was commanded to walk, run, sit, stand and lie-down. Through video synchronisation, each tri-axial acceleration sample was annotated with its associated behavioural mode; the feature vectors were extracted and used to build the classification module through the application of support vector machines (SVMs). This behavioural classification module was then used to identify and quantify the same behavioural modes in acceleration collected from a range of other species (alligator, badger, cheetah, dingo, echidna, kangaroo and wombat). Evaluation of the module performance, using a binary classification system, showed there was a high capacity (>90%) for behaviour recognition between individuals of the same species. Furthermore, a positive correlation existed between SVM capacity and the similarity of the individual's spinal length-to-height above the ground ratio (SL:SH) to that of the surrogate. The study describes how to build a behavioural classification module and highlights the value of using a surrogate for studying cryptic, rare or endangered species.

Challenges in congenital syphilis surveillance: how are congenital syphilis investigations classified?

PubMed

Introcaso, Camille E; Gruber, DeAnn; Bradley, Heather; Peterman, Thomas A; Ewell, Joy; Wendell, Debbie; Foxhood, Joseph; Su, John R; Weinstock, Hillard S; Markowitz, Lauri E

2013-09-01

Congenital syphilis is a serious, preventable, and nationally notifiable disease. Despite the existence of a surveillance case definition, congenital syphilis is sometimes classified differently using an algorithm on the Centers for Disease Control and Prevention's case reporting form. We reviewed Louisiana's congenital syphilis electronic reporting system for investigations of infants born from January 2010 to October 2011, abstracted data required for classification, and applied the surveillance definition and the algorithm. We calculated the sensitivities and specificities of the algorithm and Louisiana's classification using the surveillance definition as the surveillance gold standard. Among 349 congenital syphilis investigations, the surveillance definition identified 62 cases. The algorithm had a sensitivity of 91.9% and a specificity of 64.1%. Louisiana's classification had a sensitivity of 50% and a specificity of 91.3% compared with the surveillance definition. The differences between the algorithm and the surveillance definition led to misclassification of congenital syphilis cases. The algorithm should match the surveillance definition. Other state and local health departments should assure that their reported cases meet the surveillance definition.

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging.

PubMed

Ravi, Daniele; Fabelo, Himar; Callic, Gustavo Marrero; Yang, Guang-Zhong

2017-09-01

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.

Combining machine learning and ontological data handling for multi-source classification of nature conservation areas

NASA Astrophysics Data System (ADS)

Moran, Niklas; Nieland, Simon; Tintrup gen. Suntrup, Gregor; Kleinschmit, Birgit

2017-02-01

Manual field surveys for nature conservation management are expensive and time-consuming and could be supplemented and streamlined by using Remote Sensing (RS). RS is critical to meet requirements of existing laws such as the EU Habitats Directive (HabDir) and more importantly to meet future challenges. The full potential of RS has yet to be harnessed as different nomenclatures and procedures hinder interoperability, comparison and provenance. Therefore, automated tools are needed to use RS data to produce comparable, empirical data outputs that lend themselves to data discovery and provenance. These issues are addressed by a novel, semi-automatic ontology-based classification method that uses machine learning algorithms and Web Ontology Language (OWL) ontologies that yields traceable, interoperable and observation-based classification outputs. The method was tested on European Union Nature Information System (EUNIS) grasslands in Rheinland-Palatinate, Germany. The developed methodology is a first step in developing observation-based ontologies in the field of nature conservation. The tests show promising results for the determination of the grassland indicators wetness and alkalinity with an overall accuracy of 85% for alkalinity and 76% for wetness.

A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

PubMed

Fan, Ming; Zheng, Bin; Li, Lihua

2015-10-01

Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2004-01-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2003-12-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Observation of three-component fermions in the topological semimetal molybdenum phosphide.

PubMed

Lv, B Q; Feng, Z-L; Xu, Q-N; Gao, X; Ma, J-Z; Kong, L-Y; Richard, P; Huang, Y-B; Strocov, V N; Fang, C; Weng, H-M; Shi, Y-G; Qian, T; Ding, H

2017-06-29

In quantum field theory, Lorentz invariance leads to three types of fermion-Dirac, Weyl and Majorana. Although the existence of Weyl and Majorana fermions as elementary particles in high-energy physics is debated, all three types of fermion have been proposed to exist as low-energy, long-wavelength quasiparticle excitations in condensed-matter systems. The existence of Dirac and Weyl fermions in condensed-matter systems has been confirmed experimentally, and that of Majorana fermions is supported by various experiments. However, in condensed-matter systems, fermions in crystals are constrained by the symmetries of the 230 crystal space groups rather than by Lorentz invariance, giving rise to the possibility of finding other types of fermionic excitation that have no counterparts in high-energy physics. Here we use angle-resolved photoemission spectroscopy to demonstrate the existence of a triply degenerate point in the electronic structure of crystalline molybdenum phosphide. Quasiparticle excitations near a triply degenerate point are three-component fermions, beyond the conventional Dirac-Weyl-Majorana classification, which attributes Dirac and Weyl fermions to four- and two-fold degenerate points, respectively. We also observe pairs of Weyl points in the bulk electronic structure of the crystal that coexist with the three-component fermions. This material thus represents a platform for studying the interplay between different types of fermions. Our experimental discovery opens up a way of exploring the new physics of unconventional fermions in condensed-matter systems.

Observation of three-component fermions in the topological semimetal molybdenum phosphide

NASA Astrophysics Data System (ADS)

Lv, B. Q.; Feng, Z.-L.; Xu, Q.-N.; Gao, X.; Ma, J.-Z.; Kong, L.-Y.; Richard, P.; Huang, Y.-B.; Strocov, V. N.; Fang, C.; Weng, H.-M.; Shi, Y.-G.; Qian, T.; Ding, H.

2017-06-01

In quantum field theory, Lorentz invariance leads to three types of fermion—Dirac, Weyl and Majorana. Although the existence of Weyl and Majorana fermions as elementary particles in high-energy physics is debated, all three types of fermion have been proposed to exist as low-energy, long-wavelength quasiparticle excitations in condensed-matter systems. The existence of Dirac and Weyl fermions in condensed-matter systems has been confirmed experimentally, and that of Majorana fermions is supported by various experiments. However, in condensed-matter systems, fermions in crystals are constrained by the symmetries of the 230 crystal space groups rather than by Lorentz invariance, giving rise to the possibility of finding other types of fermionic excitation that have no counterparts in high-energy physics. Here we use angle-resolved photoemission spectroscopy to demonstrate the existence of a triply degenerate point in the electronic structure of crystalline molybdenum phosphide. Quasiparticle excitations near a triply degenerate point are three-component fermions, beyond the conventional Dirac-Weyl-Majorana classification, which attributes Dirac and Weyl fermions to four- and two-fold degenerate points, respectively. We also observe pairs of Weyl points in the bulk electronic structure of the crystal that coexist with the three-component fermions. This material thus represents a platform for studying the interplay between different types of fermions. Our experimental discovery opens up a way of exploring the new physics of unconventional fermions in condensed-matter systems.

The Australian National Sub-Acute and Non-Acute Patient casemix classification.

PubMed

Eagar, K

1999-01-01

The Australian National Sub-Acute and Non-Acute Patient (AN-SNAP) Version 1 casemix classification was completed in 1997. AN-SNAP is designed for the classification of sub-acute and non-acute care provided in both inpatient and ambulatory settings and is intended to be useful for both funding and clinical management purposes. The National Sub-Acute and Non-Acute Casemix Classification study has produced the first version of a national classification of sub-acute and non-acute care. Ongoing refinement (leading to Version 2) will be possible through further analysis of the existing data set in combination with analysis of the results of a carefully planned and phased implementation.

VTOL shipboard letdown guidance system analysis

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Karmali, M. S.

1983-01-01

Alternative letdown guidance strategies are examined for landing of a VTOL aircraft onboard a small aviation ship under adverse environmental conditions. Off line computer simulation of shipboard landing task is utilized for assessing the relative merits of the proposed guidance schemes. The touchdown performance of a nominal constant rate of descent (CROD) letdown strategy serves as a benchmark for ranking the performance of the alternative letdown schemes. Analysis of ship motion time histories indicates the existence of an alternating sequence of quiescent and rough motions called lulls and swells. A real time algorithms lull/swell classification based upon ship motion pattern features is developed. The classification algorithm is used to command a go/no go signal to indicate the initiation and termination of an acceptable landing window. Simulation results show that such a go/no go pattern based letdown guidance strategy improves touchdown performance.

Knowledge Modeling in Prior Art Search

NASA Astrophysics Data System (ADS)

Graf, Erik; Frommholz, Ingo; Lalmas, Mounia; van Rijsbergen, Keith

This study explores the benefits of integrating knowledge representations in prior art patent retrieval. Key to the introduced approach is the utilization of human judgment available in the form of classifications assigned to patent documents. The paper first outlines in detail how a methodology for the extraction of knowledge from such an hierarchical classification system can be established. Further potential ways of integrating this knowledge with existing Information Retrieval paradigms in a scalable and flexible manner are investigated. Finally based on these integration strategies the effectiveness in terms of recall and precision is evaluated in the context of a prior art search task for European patents. As a result of this evaluation it can be established that in general the proposed knowledge expansion techniques are particularly beneficial to recall and, with respect to optimizing field retrieval settings, further result in significant precision gains.

German guidelines for the diagnosis and therapy of localized scleroderma.

PubMed

Kreuter, Alexander; Krieg, Thomas; Worm, Margitta; Wenzel, Jörg; Moinzadeh, Pia; Kuhn, Annegret; Aberer, Elisabeth; Scharffetter-Kochanek, Karin; Horneff, Gerd; Reil, Emma; Weberschock, Tobias; Hunzelmann, Nicolas

2016-02-01

Localized scleroderma designates a heterogeneous group of sclerotic skin disorders. Depending on the subtype, severity, and site affected, adjacent structures such as adipose tissue, muscles, joints, and bones may be involved. This is an update of the existing German AWMF (Association of the Scientific Medical Societies in Germany) guidelines (classification: S2k). These guidelines provide an overview of the definition, epidemiology, classification, pathogenesis, laboratory workup, histopathology, clinical scoring systems, as well as imaging and device-based workup of localized scleroderma. Moreover, consensus-based recommendations are given on the management of localized scleroderma depending on its clinical subtype. Treatment recommendations are presented in a therapeutic algorithm. No financial support was given by any pharmaceutical company. The guidelines are valid until July 2019. © 2016 The Authors | Journal compilation © Blackwell Verlag GmbH, Berlin.

Neopositivism and the DSM psychiatric classification. An epistemological history. Part 1: Theoretical comparison.

PubMed

Aragona, Massimiliano

2013-06-01

Recent research suggests that the DSM psychiatric classification is in a paradigmatic crisis and that the DSM-5 will be unable to overcome it. One possible reason is that the DSM is based on a neopositivist epistemology which is inadequate for the present-day needs of psychopathology. However, in which sense is the DSM a neopositivist system? This paper will explore the theoretical similarities between the DSM structure and the neopositivist basic assumptions. It is shown that the DSM has the following neopositivist features: (a) a sharp distinction between scientific and non-scientific diagnoses; (b) the exclusion of the latter as nonsensical; (c) the faith on the existence of a purely observable basis (the description of reliable symptoms); (d) the introduction of the operative diagnostic criteria as rules of correspondence linking the observational level to the diagnostic concept.

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

Classification of matrix-product ground states corresponding to one-dimensional chains of two-state sites of nearest neighbor interactions

NASA Astrophysics Data System (ADS)

Fatollahi, Amir H.; Khorrami, Mohammad; Shariati, Ahmad; Aghamohammadi, Amir

2011-04-01

A complete classification is given for one-dimensional chains with nearest-neighbor interactions having two states in each site, for which a matrix product ground state exists. The Hamiltonians and their corresponding matrix product ground states are explicitly obtained.

Le Predicat Adjectif en Esperanto (The Predicate Adjective in Esperanto)

ERIC Educational Resources Information Center

Lo Jocomo, Francois

1977-01-01

A study of the predicate adjective in Esperanto based on the opposition established between the complementary classifications, monemes and words. Because morphological complications do not exist in Esperanto, study of the two classifications could proceed to the benefit of the study of other languages. (Text is in French.) (AMH)

9 CFR 145.44 - Terminology and classification; States.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Special Provisions for Turkey Breeding Flocks and Products § 145.44 Terminology and classification; States... State, Turkeys. (1) A State will be declared a U.S. Pullorum-Typhoid Clean State, Turkeys, when it has... existed in turkey hatchery supply flocks within the State during the preceding 24 months. (2...

9 CFR 145.44 - Terminology and classification; States.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Special Provisions for Turkey Breeding Flocks and Products § 145.44 Terminology and classification; States... State, Turkeys. (1) A State will be declared a U.S. Pullorum-Typhoid Clean State, Turkeys, when it has... existed in turkey hatchery supply flocks within the State during the preceding 24 months. (2...

9 CFR 145.44 - Terminology and classification; States.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Special Provisions for Turkey Breeding Flocks and Products § 145.44 Terminology and classification; States... State, Turkeys. (1) A State will be declared a U.S. Pullorum-Typhoid Clean State, Turkeys, when it has... existed in turkey hatchery supply flocks within the State during the preceding 24 months. (2...

Structure D'Ensemble, Multiple Classification, Multiple Seriation and Amount of Irrelevant Information

ERIC Educational Resources Information Center

Hamel, B. Remmo; Van Der Veer, M. A. A.

1972-01-01

A significant positive correlation between multiple classification was found, in testing 65 children aged 6 to 8 years, at the stage of concrete operations. This is interpreted as support for the existence of a structure d'ensemble of operational schemes in the period of concrete operations. (Authors)

Earthquake-Related Injuries in the Pediatric Population: A Systematic Review

PubMed Central

Jacquet, Gabrielle A.; Hansoti, Bhakti; Vu, Alexander; Bayram, Jamil D.

2013-01-01

Background: Children are a special population, particularly susceptible to injury. Registries for various injury types in the pediatric population are important, not only for epidemiological purposes but also for their implications on intervention programs. Although injury registries already exist, there is no uniform injury classification system for traumatic mass casualty events such as earthquakes. Objective: To systematically review peer-reviewed literature on the patterns of earthquake-related injuries in the pediatric population. Methods: On May 14, 2012, the authors performed a systematic review of literature from 1950 to 2012 indexed in Pubmed, EMBASE, Scopus, Web of Science, and Cochrane Library. Articles written in English, providing a quantitative description of pediatric injuries were included. Articles focusing on other types of disasters, geological, surgical, conceptual, psychological, indirect injuries, injury complications such as wound infections and acute kidney injury, case reports, reviews, and non-English articles were excluded. Results: A total of 2037 articles were retrieved, of which only 10 contained quantitative earthquake-related pediatric injury data. All studies were retrospective, had different age categorization, and reported injuries heterogeneously. Only 2 studies reported patterns of injury for all pediatric patients, including patients admitted and discharged. Seven articles described injuries by anatomic location, 5 articles described injuries by type, and 2 articles described injuries using both systems. Conclusions: Differences in age categorization of pediatric patients, and in the injury classification system make quantifying the burden of earthquake-related injuries in the pediatric population difficult. A uniform age categorization and injury classification system are paramount for drawing broader conclusions, enhancing disaster preparation for future disasters, and decreasing morbidity and mortality. PMID:24761308

SkICAT: A cataloging and analysis tool for wide field imaging surveys

NASA Technical Reports Server (NTRS)

Weir, N.; Fayyad, U. M.; Djorgovski, S. G.; Roden, J.

1992-01-01

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Medulloblastoma in the Molecular Era

PubMed Central

Miranda Kuzan-Fischer, Claudia; Juraschka, Kyle; Taylor, Michael D.

2018-01-01

Medulloblastoma is the most common malignant brain tumor of childhood and remains a major cause of cancer related mortality in children. Significant scientific advancements have transformed the understanding of medulloblastoma, leading to the recognition of four distinct clinical and molecular subgroups, namely wingless (WNT), sonic hedgehog, group 3, and group 4. Subgroup classification combined with the recognition of subgroup specific molecular alterations has also led to major changes in risk stratification of medulloblastoma patients and these changes have begun to alter clinical trial design, in which the newly recognized subgroups are being incorporated as individualized treatment arms. Despite these recent advancements, identification of effective targeted therapies remains a challenge for several reasons. First, significant molecular heterogeneity exists within the four subgroups, meaning this classification system alone may not be sufficient to predict response to a particular therapy. Second, the majority of novel agents are currently tested at the time of recurrence, after which significant selective pressures have been exerted by radiation and chemotherapy. Recent studies demonstrate selection of tumor sub-clones that exhibit genetic divergence from the primary tumor, exist within metastatic and recurrent tumor populations. Therefore, tumor resampling at the time of recurrence may become necessary to accurately select patients for personalized therapy. PMID:29742881

Medulloblastoma in the Molecular Era.

PubMed

Miranda Kuzan-Fischer, Claudia; Juraschka, Kyle; Taylor, Michael D

2018-05-01

Medulloblastoma is the most common malignant brain tumor of childhood and remains a major cause of cancer related mortality in children. Significant scientific advancements have transformed the understanding of medulloblastoma, leading to the recognition of four distinct clinical and molecular subgroups, namely wingless (WNT), sonic hedgehog, group 3, and group 4. Subgroup classification combined with the recognition of subgroup specific molecular alterations has also led to major changes in risk stratification of medulloblastoma patients and these changes have begun to alter clinical trial design, in which the newly recognized subgroups are being incorporated as individualized treatment arms. Despite these recent advancements, identification of effective targeted therapies remains a challenge for several reasons. First, significant molecular heterogeneity exists within the four subgroups, meaning this classification system alone may not be sufficient to predict response to a particular therapy. Second, the majority of novel agents are currently tested at the time of recurrence, after which significant selective pressures have been exerted by radiation and chemotherapy. Recent studies demonstrate selection of tumor sub-clones that exhibit genetic divergence from the primary tumor, exist within metastatic and recurrent tumor populations. Therefore, tumor resampling at the time of recurrence may become necessary to accurately select patients for personalized therapy.

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Changes in the DRG classification system. 412.10... § 412.10 Changes in the DRG classification system. (a) General rule. CMS issues changes in the DRG classification system in a Federal Register notice at least annually. Except as specified in paragraphs (c) and...

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Changes in the DRG classification system. 412.10... § 412.10 Changes in the DRG classification system. (a) General rule. CMS issues changes in the DRG classification system in a Federal Register notice at least annually. Except as specified in paragraphs (c) and...

Inter-Relationships of Functional Status in Cerebral Palsy: Analyzing Gross Motor Function, Manual Ability, and Communication Function Classification Systems in Children

ERIC Educational Resources Information Center

Hidecker, Mary Jo Cooley; Ho, Nhan Thi; Dodge, Nancy; Hurvitz, Edward A.; Slaughter, Jaime; Workinger, Marilyn Seif; Kent, Ray D.; Rosenbaum, Peter; Lenski, Madeleine; Messaros, Bridget M.; Vanderbeek, Suzette B.; Deroos, Steven; Paneth, Nigel

2012-01-01

Aim: To investigate the relationships among the Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) in children with cerebral palsy (CP). Method: Using questionnaires describing each scale, mothers reported GMFCS, MACS, and CFCS levels in 222…

Correlation of the Rock Mass Rating (RMR) System with the Unified Soil Classification System (USCS): Introduction of the Weak Rock Mass Rating System (W-RMR)

NASA Astrophysics Data System (ADS)

Warren, Sean N.; Kallu, Raj R.; Barnard, Chase K.

2016-11-01

Underground gold mines in Nevada are exploiting increasingly deeper ore bodies comprised of weak to very weak rock masses. The Rock Mass Rating (RMR) classification system is widely used at underground gold mines in Nevada and is applicable in fair to good-quality rock masses, but is difficult to apply and loses reliability in very weak rock mass to soil-like material. Because very weak rock masses are transition materials that border engineering rock mass and soil classification systems, soil classification may sometimes be easier and more appropriate to provide insight into material behavior and properties. The Unified Soil Classification System (USCS) is the most likely choice for the classification of very weak rock mass to soil-like material because of its accepted use in tunnel engineering projects and its ability to predict soil-like material behavior underground. A correlation between the RMR and USCS systems was developed by comparing underground geotechnical RMR mapping to laboratory testing of bulk samples from the same locations, thereby assigning a numeric RMR value to the USCS classification that can be used in spreadsheet calculations and geostatistical analyses. The geotechnical classification system presented in this paper including a USCS-RMR correlation, RMR rating equations, and the Geo-Pick Strike Index is collectively introduced as the Weak Rock Mass Rating System (W-RMR). It is the authors' hope that this system will aid in the classification of weak rock masses and more usable design tools based on the RMR system. More broadly, the RMR-USCS correlation and the W-RMR system help define the transition between engineering soil and rock mass classification systems and may provide insight for geotechnical design in very weak rock masses.

Overweight and Obesity Prevalence Among School-Aged Nunavik Inuit Children According to Three Body Mass Index Classification Systems.

PubMed

Medehouenou, Thierry Comlan Marc; Ayotte, Pierre; St-Jean, Audray; Meziou, Salma; Roy, Cynthia; Muckle, Gina; Lucas, Michel

2015-07-01

Little is known about the suitability of three commonly used body mass index (BMI) classification system for Indigenous children. This study aims to estimate overweight and obesity prevalence among school-aged Nunavik Inuit children according to International Obesity Task Force (IOTF), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO) BMI classification systems, to measure agreement between those classification systems, and to investigate whether BMI status as defined by these classification systems is associated with levels of metabolic and inflammatory biomarkers. Data were collected on 290 school-aged children (aged 8-14 years; 50.7% girls) from the Nunavik Child Development Study with data collected in 2005-2010. Anthropometric parameters were measured and blood sampled. Participants were classified as normal weight, overweight, and obese according to BMI classification systems. Weighted kappa (κw) statistics assessed agreement between different BMI classification systems, and multivariate analysis of variance ascertained their relationship with metabolic and inflammatory biomarkers. The combined prevalence rate of overweight/obesity was 26.9% (with 6.6% obesity) with IOTF, 24.1% (11.0%) with CDC, and 40.4% (12.8%) with WHO classification systems. Agreement was the highest between IOTF and CDC (κw = .87) classifications, and substantial for IOTF and WHO (κw = .69) and for CDC and WHO (κw = .73). Insulin and high-sensitivity C-reactive protein plasma levels were significantly higher from normal weight to obesity, regardless of classification system. Among obese subjects, higher insulin level was observed with IOTF. Compared with other systems, IOTF classification appears to be more specific to identify overweight and obesity in Inuit children. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Defining functional biomes and monitoring their change globally.

PubMed

Higgins, Steven I; Buitenwerf, Robert; Moncrieff, Glenn R

2016-11-01

Biomes are important constructs for organizing understanding of how the worlds' major terrestrial ecosystems differ from one another and for monitoring change in these ecosystems. Yet existing biome classification schemes have been criticized for being overly subjective and for explicitly or implicitly invoking climate. We propose a new biome map and classification scheme that uses information on (i) an index of vegetation productivity, (ii) whether the minimum of vegetation activity is in the driest or coldest part of the year, and (iii) vegetation height. Although biomes produced on the basis of this classification show a strong spatial coherence, they show little congruence with existing biome classification schemes. Our biome map provides an alternative classification scheme for comparing the biogeochemical rates of terrestrial ecosystems. We use this new biome classification scheme to analyse the patterns of biome change observed over recent decades. Overall, 13% to 14% of analysed pixels shifted in biome state over the 30-year study period. A wide range of biome transitions were observed. For example, biomes with tall vegetation and minimum vegetation activity in the cold season shifted to higher productivity biome states. Biomes with short vegetation and low seasonality shifted to seasonally moisture-limited biome states. Our findings and method provide a new source of data for rigorously monitoring global vegetation change, analysing drivers of vegetation change and for benchmarking models of terrestrial ecosystem function. © 2016 John Wiley & Sons Ltd.

Hierarchical trie packet classification algorithm based on expectation-maximization clustering

PubMed Central

Bi, Xia-an; Zhao, Junxia

2017-01-01

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. PMID:28704476

[Diagnosis-related groups as an instrument to develop suitable case-based lump sums in hematology and oncology].

PubMed

Thalheimer, Markus

2011-01-01

In 2003 a new reimbursement system was established for German hospitals. The approximately 17 million inpatient cases per year are now reimbursed based on a per-case payment regarding diagnoses and procedures, which was developed from an internationally approved system. The aim was a better conformity of costs and efforts in in-patient cases. In the first 2 years after implementation, the German diagnosis-related group (DRG) system was not able to adequately represent the complex structures of treatment in hematological and oncological in-patients. By creating new diagnoses and procedures (International Classification of Diseases 10 (ICD-10) and Surgical Operations and Procedures Classification System (OPS) catalogues), generating new DRGs and better splitting of existing ones, the hematology and oncology field could be much better described in the following years. The implementation of about 70 'co-payment structures' for new and expensive drugs and procedures in oncology was also crucial. To reimburse innovations, an additional system of co-payments for innovations was established to bridge the time until innovations are represented within the DRG system itself. In summary, hematological and oncological in-patients, including cases with extraordinary costs, are meanwhile well mapped in the German reimbursement system. Any tendencies to rationing could thereby be avoided, as most of the established procedures and costly drugs are adequately represented in the DRG system. Copyright © 2011 S. Karger AG, Basel.

Joint Concept Correlation and Feature-Concept Relevance Learning for Multilabel Classification.

PubMed

Zhao, Xiaowei; Ma, Zhigang; Li, Zhi; Li, Zhihui

2018-02-01

In recent years, multilabel classification has attracted significant attention in multimedia annotation. However, most of the multilabel classification methods focus only on the inherent correlations existing among multiple labels and concepts and ignore the relevance between features and the target concepts. To obtain more robust multilabel classification results, we propose a new multilabel classification method aiming to capture the correlations among multiple concepts by leveraging hypergraph that is proved to be beneficial for relational learning. Moreover, we consider mining feature-concept relevance, which is often overlooked by many multilabel learning algorithms. To better show the feature-concept relevance, we impose a sparsity constraint on the proposed method. We compare the proposed method with several other multilabel classification methods and evaluate the classification performance by mean average precision on several data sets. The experimental results show that the proposed method outperforms the state-of-the-art methods.

Pseudo-simple heteroclinic cycles in R4

NASA Astrophysics Data System (ADS)

Chossat, Pascal; Lohse, Alexander; Podvigina, Olga

2018-06-01

We study pseudo-simple heteroclinic cycles for a Γ-equivariant system in R4 with finite Γ ⊂ O(4) , and their nearby dynamics. In particular, in a first step towards a full classification - analogous to that which exists already for the class of simple cycles - we identify all finite subgroups of O(4) admitting pseudo-simple cycles. To this end we introduce a constructive method to build equivariant dynamical systems possessing a robust heteroclinic cycle. Extending a previous study we also investigate the existence of periodic orbits close to a pseudo-simple cycle, which depends on the symmetry groups of equilibria in the cycle. Moreover, we identify subgroups Γ ⊂ O(4) , Γ ⊄ SO(4) , admitting fragmentarily asymptotically stable pseudo-simple heteroclinic cycles. (It has been previously shown that for Γ ⊂ SO(4) pseudo-simple cycles generically are completely unstable.) Finally, we study a generalized heteroclinic cycle, which involves a pseudo-simple cycle as a subset.

Exotic topological density waves in cold atomic Rydberg-dressed fermions

PubMed Central

Li, Xiaopeng; Sarma, S Das

2015-01-01

Versatile controllability of interactions in ultracold atomic and molecular gases has now reached an era where quantum correlations and unconventional many-body phases can be studied with no corresponding analogues in solid-state systems. Recent experiments in Rydberg atomic gases have achieved exquisite control over non-local interactions, allowing novel quantum phases unreachable with the usual local interactions in atomic systems. Here we study Rydberg-dressed atomic fermions in a three-dimensional optical lattice predicting the existence of hitherto unheard-of exotic mixed topological density wave phases. By varying the spatial range of the non-local interaction, we find various chiral density waves with spontaneous time-reversal symmetry breaking, whose quasiparticles form three-dimensional quantum Hall and Weyl semimetal states. Remarkably, certain density waves even exhibit mixed topologies beyond the existing topological classification. Our results suggest gapless fermionic states could exhibit far richer topology than previously expected. PMID:25972134

Extensions to the Speech Disorders Classification System (SDCS)

ERIC Educational Resources Information Center

Shriberg, Lawrence D.; Fourakis, Marios; Hall, Sheryl D.; Karlsson, Heather B.; Lohmeier, Heather L.; McSweeny, Jane L.; Potter, Nancy L.; Scheer-Cohen, Alison R.; Strand, Edythe A.; Tilkens, Christie M.; Wilson, David L.

2010-01-01

This report describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). Part I describes a classification extension to the SDCS to differentiate motor speech disorders from speech delay and to differentiate among three sub-types of motor speech disorders.…

Automatic Detection and Vulnerability Analysis of Areas Endangered by Heavy Rain

NASA Astrophysics Data System (ADS)

Krauß, Thomas; Fischer, Peter

2016-08-01

In this paper we present a new method for fully automatic detection and derivation of areas endangered by heavy rainfall based only on digital elevation models. Tracking news show that the majority of occuring natural hazards are flood events. So already many flood prediction systems were developed. But most of these existing systems for deriving areas endangered by flooding events are based only on horizontal and vertical distances to existing rivers and lakes. Typically such systems take not into account dangers arising directly from heavy rain events. In a study conducted by us together with a german insurance company a new approach for detection of areas endangered by heavy rain was proven to give a high correlation of the derived endangered areas and the losses claimed at the insurance company. Here we describe three methods for classification of digital terrain models and analyze their usability for automatic detection and vulnerability analysis for areas endangered by heavy rainfall and analyze the results using the available insurance data.

"Ordinary men" or "evil monsters"? An action systems model of genocidal actions and characteristics of perpetrators.

PubMed

Hollows, Kerrilee; Fritzon, Katarina

2012-10-01

This study aimed to address the limitations of the existing genocide literature with the development of an empirically based classification system. Using Shye's (1985) action systems model, it was hypothesized that four types of perpetrators would exist and would be distinguishable by differences in the sources and target of individual criminal actions. Court transcripts from 80 perpetrators sentenced by the international courts were subject to content analysis and revealed 39 offense action variables, 17 perpetrator characteristic variables, and 6 perpetrator motive variables. A smallest space analysis using the Jaccard coefficient of association was conducted on the offense variables. The results supported the proposed framework, producing four distinct types of genocidal perpetrators. Correlational analyses were then conducted to examine the relationships between each of the perpetrator types and the remaining variables. The results of those correlations provided further support for the proposed framework. The implications of these findings are discussed. PsycINFO Database Record (c) 2012 APA, all rights reserved.

High-level intuitive features (HLIFs) for intuitive skin lesion description.

PubMed

Amelard, Robert; Glaister, Jeffrey; Wong, Alexander; Clausi, David A

2015-03-01

A set of high-level intuitive features (HLIFs) is proposed to quantitatively describe melanoma in standard camera images. Melanoma is the deadliest form of skin cancer. With rising incidence rates and subjectivity in current clinical detection methods, there is a need for melanoma decision support systems. Feature extraction is a critical step in melanoma decision support systems. Existing feature sets for analyzing standard camera images are comprised of low-level features, which exist in high-dimensional feature spaces and limit the system's ability to convey intuitive diagnostic rationale. The proposed HLIFs were designed to model the ABCD criteria commonly used by dermatologists such that each HLIF represents a human-observable characteristic. As such, intuitive diagnostic rationale can be conveyed to the user. Experimental results show that concatenating the proposed HLIFs with a full low-level feature set increased classification accuracy, and that HLIFs were able to separate the data better than low-level features with statistical significance. An example of a graphical interface for providing intuitive rationale is given.

RAIRS2 a new expert system for diagnosing tuberculosis with real-world tournament selection mechanism inside artificial immune recognition system.

PubMed

Saybani, Mahmoud Reza; Shamshirband, Shahaboddin; Golzari, Shahram; Wah, Teh Ying; Saeed, Aghabozorgi; Mat Kiah, Miss Laiha; Balas, Valentina Emilia

2016-03-01

Tuberculosis is a major global health problem that has been ranked as the second leading cause of death from an infectious disease worldwide, after the human immunodeficiency virus. Diagnosis based on cultured specimens is the reference standard; however, results take weeks to obtain. Slow and insensitive diagnostic methods hampered the global control of tuberculosis, and scientists are looking for early detection strategies, which remain the foundation of tuberculosis control. Consequently, there is a need to develop an expert system that helps medical professionals to accurately diagnose the disease. The objective of this study is to diagnose tuberculosis using a machine learning method. Artificial immune recognition system (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy. In order to increase the classification accuracy, this study introduces a new hybrid system that incorporates real tournament selection mechanism into the AIRS. This mechanism is used to control the population size of the model and to overcome the existing selection pressure. Patient epacris reports obtained from the Pasteur laboratory in northern Iran were used as the benchmark data set. The sample consisted of 175 records, from which 114 (65 %) were positive for TB, and the remaining 61 (35 %) were negative. The classification performance was measured through tenfold cross-validation, root-mean-square error, sensitivity, and specificity. With an accuracy of 100 %, RMSE of 0, sensitivity of 100 %, and specificity of 100 %, the proposed method was able to successfully classify tuberculosis cases. In addition, the proposed method is comparable with top classifiers used in this research.

Factors affecting general practitioners' decisions about plain radiography for back pain: implications for classification of guideline barriers--a qualitative study.

PubMed

Espeland, Ansgar; Baerheim, Anders

2003-03-24

General practitioners often diverge from clinical guidelines regarding spine radiography. This study aimed to identify and describe A) factors general practitioners consider may affect their decisions about ordering plain radiography for back pain and B) barriers to guideline adherence suggested by such factors. Focus group interviews regarding factors affecting ordering decisions were carried out on a diverse sample of Norwegian general practitioners and were analysed qualitatively. Results of this study and two qualitative studies from the Netherlands and USA on use of spine radiography were interpreted for barriers to guideline adherence. These were compared with an existing barrier classification system described by Dr Cabana's group. The factors which Norwegian general practitioners considered might affect their decisions about ordering plain radiography for back pain concerned the following broader issues: clinical ordering criteria, patients' wishes for radiography and the general practitioner's response, uncertainty, professional dignity, access to radiology services, perception of whether the patient really was ill, sense of pressure from other health care providers/social security, and expectations about the consequences of ordering radiography. The three studies suggested several attitude-related and external barriers as classified in a previously reported system described by Dr Cabana in another study. Identified barriers not listed in this system were: lack of expectancy that guideline adherence will lead to desired health care process, emotional difficulty with adherence, improper access to actual/alternative health care services, and pressure from health care providers/organisations. Our findings may help implement spine radiography guidelines. They also indicate that Cabana et al.'s barrier classification system needs extending. A revised system is proposed.

Factors affecting general practitioners' decisions about plain radiography for back pain: implications for classification of guideline barriers – a qualitative study

PubMed Central

Espeland, Ansgar; Baerheim, Anders

2003-01-01

Background General practitioners often diverge from clinical guidelines regarding spine radiography. This study aimed to identify and describe A) factors general practitioners consider may affect their decisions about ordering plain radiography for back pain and B) barriers to guideline adherence suggested by such factors. Methods Focus group interviews regarding factors affecting ordering decisions were carried out on a diverse sample of Norwegian general practitioners and were analysed qualitatively. Results of this study and two qualitative studies from the Netherlands and USA on use of spine radiography were interpreted for barriers to guideline adherence. These were compared with an existing barrier classification system described by Dr Cabana's group. Results The factors which Norwegian general practitioners considered might affect their decisions about ordering plain radiography for back pain concerned the following broader issues: clinical ordering criteria, patients' wishes for radiography and the general practitioner's response, uncertainty, professional dignity, access to radiology services, perception of whether the patient really was ill, sense of pressure from other health care providers/social security, and expectations about the consequences of ordering radiography. The three studies suggested several attitude-related and external barriers as classified in a previously reported system described by Dr Cabana in another study. Identified barriers not listed in this system were: lack of expectancy that guideline adherence will lead to desired health care process, emotional difficulty with adherence, improper access to actual/alternative health care services, and pressure from health care providers/organisations. Conclusions Our findings may help implement spine radiography guidelines. They also indicate that Cabana et al.'s barrier classification system needs extending. A revised system is proposed. PMID:12659640

Comparison of Danish dichotomous and BI-RADS classifications of mammographic density.

PubMed

Hodge, Rebecca; Hellmann, Sophie Sell; von Euler-Chelpin, My; Vejborg, Ilse; Andersen, Zorana Jovanovic

2014-06-01

In the Copenhagen mammography screening program from 1991 to 2001, mammographic density was classified either as fatty or mixed/dense. This dichotomous mammographic density classification system is unique internationally, and has not been validated before. To compare the Danish dichotomous mammographic density classification system from 1991 to 2001 with the density BI-RADS classifications, in an attempt to validate the Danish classification system. The study sample consisted of 120 mammograms taken in Copenhagen in 1991-2001, which tested false positive, and which were in 2012 re-assessed and classified according to the BI-RADS classification system. We calculated inter-rater agreement between the Danish dichotomous mammographic classification as fatty or mixed/dense and the four-level BI-RADS classification by the linear weighted Kappa statistic. Of the 120 women, 32 (26.7%) were classified as having fatty and 88 (73.3%) as mixed/dense mammographic density, according to Danish dichotomous classification. According to BI-RADS density classification, 12 (10.0%) women were classified as having predominantly fatty (BI-RADS code 1), 46 (38.3%) as having scattered fibroglandular (BI-RADS code 2), 57 (47.5%) as having heterogeneously dense (BI-RADS 3), and five (4.2%) as having extremely dense (BI-RADS code 4) mammographic density. The inter-rater variability assessed by weighted kappa statistic showed a substantial agreement (0.75). The dichotomous mammographic density classification system utilized in early years of Copenhagen's mammographic screening program (1991-2001) agreed well with the BI-RADS density classification system.

Assessing biodiversity on the farm scale as basis for ecosystem service payments.

PubMed

von Haaren, Christina; Kempa, Daniela; Vogel, Katrin; Rüter, Stefan

2012-12-30

Ecosystem services payments must be based on a standardised transparent assessment of the goods and services provided. This is especially relevant in the context of EU agri-environmental programs, but also for organic-food companies that foster environmental services on their contractor farms. Addressing the farm scale is important because land users/owners are major recipients of payments and they could be more involved in data generation and conservation management. A standardised system for measuring on-farm biodiversity does not yet exist that concentrates on performance indicators and includes farmers in generating information. A method is required that produces ordinal or metric scaled assessment results as well as management measures. Another requirement is the ease of application, which includes the ease of gathering input data and understandability. In order to respond to this need, we developed a method which is designed for automated application in an open source farm assessment system named MANUELA. The method produces an ordinal scale assessment of biodiversity that includes biotopes, species, biotope connectivity and the influence of land use. In addition, specific measures for biotope types are proposed. The open source geographical information system OpenJump is used for the implementation of MANUELA. The results of the trial applications and robustness tests show that the assessment can be implemented, for the most part, using existing information as well as data available from farmers or advisors. The results are more sensitive for showing on-farm achievements and changes than existing biotope-type classifications. Such a differentiated classification is needed as a basis for ecosystem service payments and for designing effective measures. The robustness of the results with respect to biotope connectivity is comparable to that of complex models, but it should be further improved. Interviews with the test farmers substantiate that the assessment methods can be implemented on farms and they are understood by farmers. Copyright © 2012 Elsevier Ltd. All rights reserved.

Prototype Expert System for Climate Classification.

ERIC Educational Resources Information Center

Harris, Clay

Many students find climate classification laborious and time-consuming, and through their lack of repetition fail to grasp the details of classification. This paper describes an expert system for climate classification that is being developed at Middle Tennessee State University. Topics include: (1) an introduction to the nature of classification,…

A color-coded vision scheme for robotics

NASA Technical Reports Server (NTRS)

Johnson, Kelley Tina

1991-01-01

Most vision systems for robotic applications rely entirely on the extraction of information from gray-level images. Humans, however, regularly depend on color to discriminate between objects. Therefore, the inclusion of color in a robot vision system seems a natural extension of the existing gray-level capabilities. A method for robot object recognition using a color-coding classification scheme is discussed. The scheme is based on an algebraic system in which a two-dimensional color image is represented as a polynomial of two variables. The system is then used to find the color contour of objects. In a controlled environment, such as that of the in-orbit space station, a particular class of objects can thus be quickly recognized by its color.

Naive Bayes as opinion classifier to evaluate students satisfaction based on student sentiment in Twitter Social Media

NASA Astrophysics Data System (ADS)

Candra Permana, Fahmi; Rosmansyah, Yusep; Setiawan Abdullah, Atje

2017-10-01

Students activity on social media can provide implicit knowledge and new perspectives for an educational system. Sentiment analysis is a part of text mining that can help to analyze and classify the opinion data. This research uses text mining and naive Bayes method as opinion classifier, to be used as an alternative methods in the process of evaluating studentss satisfaction for educational institution. Based on test results, this system can determine the opinion classification in Bahasa Indonesia using naive Bayes as opinion classifier with accuracy level of 84% correct, and the comparison between the existing system and the proposed system to evaluate students satisfaction in learning process, there is only a difference of 16.49%.

5 CFR 9901.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9901.221 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

The Bellevue Classification System: nursing's voice upon the library shelves*†

PubMed Central

Mages, Keith C

2011-01-01

This article examines the inspiration, construction, and meaning of the Bellevue Classification System (BCS), created during the 1930s for use in the Bellevue School of Nursing Library. Nursing instructor Ann Doyle, with assistance from librarian Mary Casamajor, designed the BCS after consulting with library leaders and examining leading contemporary classification systems, including the Dewey Decimal Classification and Library of Congress, Ballard, and National Health Library classification systems. A close textual reading of the classes, subclasses, and subdivisions of these classification systems against those of the resulting BCS, reveals Doyle's belief that the BCS was created not only to organize the literature, but also to promote the burgeoning intellectualism and professionalism of early twentieth-century American nursing. PMID:21243054

Coordination of Local Road Classification with the State Highway System Classification: Impact and Clarification of Related Language in the LVR Manual

DOT National Transportation Integrated Search

1996-02-01

This study reviewed the low volume road (LVR) classifications in Kansas in conjunction with the State A, B, C, D, E road classification system and addressed alignment of these differences. As an extension to the State system, an F, G, H classificatio...

The research on medical image classification algorithm based on PLSA-BOW model.

PubMed

Cao, C H; Cao, H L

2016-04-29

With the rapid development of modern medical imaging technology, medical image classification has become more important for medical diagnosis and treatment. To solve the existence of polysemous words and synonyms problem, this study combines the word bag model with PLSA (Probabilistic Latent Semantic Analysis) and proposes the PLSA-BOW (Probabilistic Latent Semantic Analysis-Bag of Words) model. In this paper we introduce the bag of words model in text field to image field, and build the model of visual bag of words model. The method enables the word bag model-based classification method to be further improved in accuracy. The experimental results show that the PLSA-BOW model for medical image classification can lead to a more accurate classification.

Contour classification in thermographic images for detection of breast cancer

NASA Astrophysics Data System (ADS)

Okuniewski, Rafał; Nowak, Robert M.; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Oleszkiewicz, Witold

2016-09-01

Thermographic images of breast taken by the Braster device are uploaded into web application which uses different classification algorithms to automatically decide whether a patient should be more thoroughly examined. This article presents the approach to the task of classifying contours visible on thermographic images of breast taken by the Braster device in order to make the decision about the existence of cancerous tumors in breast. It presents the results of the researches conducted on the different classification algorithms.

Applications of Location Similarity Measures and Conceptual Spaces to Event Coreference and Classification

ERIC Educational Resources Information Center

McConky, Katie Theresa

2013-01-01

This work covers topics in event coreference and event classification from spoken conversation. Event coreference is the process of identifying descriptions of the same event across sentences, documents, or structured databases. Existing event coreference work focuses on sentence similarity models or feature based similarity models requiring slot…

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Toward unification of taxonomy databases in a distributed computer environment

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

Kitakami, Hajime; Tateno, Yoshio; Gojobori, Takashi

1994-12-31

All the taxonomy databases constructed with the DNA databases of the international DNA data banks are powerful electronic dictionaries which aid in biological research by computer. The taxonomy databases are, however not consistently unified with a relational format. If we can achieve consistent unification of the taxonomy databases, it will be useful in comparing many research results, and investigating future research directions from existent research results. In particular, it will be useful in comparing relationships between phylogenetic trees inferred from molecular data and those constructed from morphological data. The goal of the present study is to unify the existent taxonomymore » databases and eliminate inconsistencies (errors) that are present in them. Inconsistencies occur particularly in the restructuring of the existent taxonomy databases, since classification rules for constructing the taxonomy have rapidly changed with biological advancements. A repair system is needed to remove inconsistencies in each data bank and mismatches among data banks. This paper describes a new methodology for removing both inconsistencies and mismatches from the databases on a distributed computer environment. The methodology is implemented in a relational database management system, SYBASE.« less

Application of Wavelet Transform for PDZ Domain Classification

PubMed Central

Daqrouq, Khaled; Alhmouz, Rami; Balamesh, Ahmed; Memic, Adnan

2015-01-01

PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III), that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain's primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT) and Shannon entropy denoted by wavelet entropy (WE) feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%), which outperformed our occurrence rearrangements based method. The recognition rate was (81.41%) with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification. PMID:25860375

Evaluation of potential emission spectra for the reliable classification of fluorescently coded materials

NASA Astrophysics Data System (ADS)

Brunner, Siegfried; Kargel, Christian

2011-06-01

The conservation and efficient use of natural and especially strategic resources like oil and water have become global issues, which increasingly initiate environmental and political activities for comprehensive recycling programs. To effectively reutilize oil-based materials necessary in many industrial fields (e.g. chemical and pharmaceutical industry, automotive, packaging), appropriate methods for a fast and highly reliable automated material identification are required. One non-contacting, color- and shape-independent new technique that eliminates the shortcomings of existing methods is to label materials like plastics with certain combinations of fluorescent markers ("optical codes", "optical fingerprints") incorporated during manufacture. Since time-resolved measurements are complex (and expensive), fluorescent markers must be designed that possess unique spectral signatures. The number of identifiable materials increases with the number of fluorescent markers that can be reliably distinguished within the limited wavelength band available. In this article we shall investigate the reliable detection and classification of fluorescent markers with specific fluorescence emission spectra. These simulated spectra are modeled based on realistic fluorescence spectra acquired from material samples using a modern VNIR spectral imaging system. In order to maximize the number of materials that can be reliably identified, we evaluate the performance of 8 classification algorithms based on different spectral similarity measures. The results help guide the design of appropriate fluorescent markers, optical sensors and the overall measurement system.

Low-Power Analog Processing for Sensing Applications: Low-Frequency Harmonic Signal Classification

PubMed Central

White, Daniel J.; William, Peter E.; Hoffman, Michael W.; Balkir, Sina

2013-01-01

A low-power analog sensor front-end is described that reduces the energy required to extract environmental sensing spectral features without using Fast Fouriér Transform (FFT) or wavelet transforms. An Analog Harmonic Transform (AHT) allows selection of only the features needed by the back-end, in contrast to the FFT, where all coefficients must be calculated simultaneously. We also show that the FFT coefficients can be easily calculated from the AHT results by a simple back-substitution. The scheme is tailored for low-power, parallel analog implementation in an integrated circuit (IC). Two different applications are tested with an ideal front-end model and compared to existing studies with the same data sets. Results from the military vehicle classification and identification of machine-bearing fault applications shows that the front-end suits a wide range of harmonic signal sources. Analog-related errors are modeled to evaluate the feasibility of and to set design parameters for an IC implementation to maintain good system-level performance. Design of a preliminary transistor-level integrator circuit in a 0.13 μm complementary metal-oxide-silicon (CMOS) integrated circuit process showed the ability to use online self-calibration to reduce fabrication errors to a sufficiently low level. Estimated power dissipation is about three orders of magnitude less than similar vehicle classification systems that use commercially available FFT spectral extraction. PMID:23892765

Thermal bioaerosol cloud tracking with Bayesian classification

NASA Astrophysics Data System (ADS)

Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

2017-05-01

The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

Existence Regions of Shock Wave Triple Configurations

ERIC Educational Resources Information Center

Bulat, Pavel V.; Chernyshev, Mikhail V.

2016-01-01

The aim of the research is to create the classification for shock wave triple configurations and their existence regions of various types: type 1, type 2, type 3. Analytical solutions for limit Mach numbers and passing shock intensity that define existence region of every type of triple configuration have been acquired. The ratios that conjugate…

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Emphasis has been given to an inventory of land resource types and land use at the ten Great Plains Corridor test sites. A resource and land use classification system was developed which uses available soil survey information and interpretations from NASA obtained high flight aerial photography to locate discrete areas of similar rangeland vegetation. Existing classification systems, even those developed for use with remote sensor data, were found to be inadequate for this project. This system is expected to be of general use for remote sensing related to land use and management. It has specific applicability to any effort aimed at regional use of ERTS-1 MSS digital data products. A preliminary assessment of the relative importance of rangelands in the Great Plains Corridor states indicates that the value of the livestock industry supported by this resource exceeds 23 billion dollars. The development of a Rangeland Feed Conditions index for this region could be used by more than 400,000 farm and ranch operators involved in the production of more than 40% of the nation's beef and much of the country's grain.

Developing applications of the ICF in education systems: addressing issues of knowledge creation, management and transfer.

PubMed

Hollenweger, Judith

2013-06-01

Since its endorsement, the International Classification of Functioning, Disability and Health (ICF) has been applied in many policy contexts, including education. While so far the focus has been on showing ways in which it can be used to describe functioning and disability, this article seeks to focus on its value to represent knowledge. Two applications of the ICF and ICF-CY in the context of the Swiss education system highlight ways in which the classification can be used to assist multidisciplinary teams in acquiring and mapping existing knowledge, in creating new knowledge and in applying it for specific purposes. The conceptual analysis illustrates that "disability in education" is a hybrid conceptual world that needs to bridge disability-related information with information relevant for learning and education. The ICF can be used to adequately map such knowledge in complex social settings. More attention needs to be paid to the ICF as an information system to help negotiate between different views on reality and different areas of expertise. The selection of content and ways of representing it need to be considered in the light of the specific purposes during collaborative knowledge creation processes.

Minimization of annotation work: diagnosis of mammographic masses via active learning

NASA Astrophysics Data System (ADS)

Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

2018-06-01

The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the particularities of mammographic images, the proposed AL method can indeed reduce the manual annotation work to a great extent without sacrificing the performance of the prediction system for mammographic diagnosis.

Minimization of annotation work: diagnosis of mammographic masses via active learning.

PubMed

Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

2018-05-22

The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the particularities of mammographic images, the proposed AL method can indeed reduce the manual annotation work to a great extent without sacrificing the performance of the prediction system for mammographic diagnosis.

A practical classification schema incorporating consideration of possible asphyxia in cases of sudden unexpected infant death

PubMed Central

Randall, Brad B.; Wadee, Sabbir A.; Sens, Mary Ann; Kinney, Hannah C.; Folkerth, Rebecca D.; Odendaal, Hein J.; Dempers, Johan J.

2012-01-01

Although the rate of the sudden infant death syndrome (SIDS) has decreased over the last two decades, medical examiners and coroners are increasingly unwilling to use the SIDS diagnosis, particularly when there is an unsafe sleeping environment that might pose a risk for asphyxia. In order to reliably classify the infant deaths studied in a research setting in the mixed ancestory population in Cape Town, South Africa, we tested a classification system devised by us that incorporates the uncertainty of asphyxial risks at an infant death scene. We classified sudden infant deaths as: A) SIDS (where only a trivial potential for an overt asphyxial event existed); B) Unclassified—Possibly Asphyxial-Related (when any potential for an asphyxial death existed); C) Unclassified—Non-Asphyxial-Related (e.g., hyperthermia); D) Unclassified—No autopsy and/or death scene investigation; and E) Known Cause of Death. Ten infant deaths were classified according to the proposed schema as: SIDS, n = 2; Unclassified—Possibly Asphyxial-Related, n = 4; and Known Cause, n = 4. A conventional schema categorized the deaths as 6 cases, SIDS, and 4 cases, Known Cause, indicating that 4/6 (67%) of deaths previously classified as SIDS are considered related importantly to asphyxia and warrant their own subgroup. This new classification schema applies a simpler, more qualitative approach to asphyxial risk in infant deaths. It also allows us to test hypotheses about the role of asphyxia in sudden infant deaths, such as in brainstem defects in a range of asphyxial challenges. PMID:19484508

Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data.

PubMed

MacAlister, Charlotte; Mahaxay, Manithaphone

2009-05-01

The Mekong River Basin is considered to be the second most species rich river basin in the world. The 795,000 km(2) catchment encompasses several ecoregions, incorporating biodiverse and productive wetland systems. Eighty percent of the rapidly expanding population of the Lower Mekong Basin (LMB), made up in part by Lao PDR, Thailand, Cambodia and Viet Nam, live in rural areas and are heavily reliant on wetland resources. As the populations of Cambodia and Lao PDR will double in the next 20 years, pressure on natural resources and particularly wetlands can only increase. For development planning, resource and conservation management to incorporate wetland issues, information on the distribution and character of Mekong wetlands is essential. The existing but outdated wetland maps were compiled from secondary landuse-landcover data, have limited coverage, poor thematic accuracy and no meta-data. Therefore the Mekong River Commission (MRC) undertook to produce new wetland coverage for the LMB. As resources, funding and regional capacity are limited, it was determined that the method applied should use existing facilities, be easily adaptable, and replicable locally. For the product to be useful it must be accepted by local governments and decision makers. The results must be of acceptable accuracy (>75%) and the methodology should be relatively understandable to non-experts. In the first stage of this exercise, field survey was conducted at five pilot sites covering a range of typical wetland habitats (MRC wetland classification) to supply data for a supervised classification of Landsat ETM images from the existing MRC archive. Images were analysed using ERDAS IMAGINE and applying Maximum Likelihood Classification. Field data were reserved to apply formal accuracy assessment to the final wetland habitat maps, with resulting accuracy ranging from 77 to 94%. The maps produced are now in use at a Provincial and National level in three countries for resource and conservation planning and management applications, including designation of a Ramsar wetland site of international importance.