Advances in Risk Classification and Treatment Strategies for Neuroblastoma

PubMed Central

Pinto, Navin R.; Applebaum, Mark A.; Volchenboum, Samuel L.; Matthay, Katherine K.; London, Wendy B.; Ambros, Peter F.; Nakagawara, Akira; Berthold, Frank; Schleiermacher, Gudrun; Park, Julie R.; Valteau-Couanet, Dominique; Pearson, Andrew D.J.

2015-01-01

Risk-based treatment approaches for neuroblastoma have been ongoing for decades. However, the criteria used to define risk in various institutional and cooperative groups were disparate, limiting the ability to compare clinical trial results. To mitigate this problem and enhance collaborative research, homogenous pretreatment patient cohorts have been defined by the International Neuroblastoma Risk Group classification system. During the past 30 years, increasingly intensive, multimodality approaches have been developed to treat patients who are classified as high risk, whereas patients with low- or intermediate-risk neuroblastoma have received reduced therapy. This treatment approach has resulted in improved outcome, although survival for high-risk patients remains poor, emphasizing the need for more effective treatments. Increased knowledge regarding the biology and genetic basis of neuroblastoma has led to the discovery of druggable targets and promising, new therapeutic approaches. Collaborative efforts of institutions and international cooperative groups have led to advances in our understanding of neuroblastoma biology, refinements in risk classification, and stratified treatment strategies, resulting in improved outcome. International collaboration will be even more critical when evaluating therapies designed to treat small cohorts of patients with rare actionable mutations. PMID:26304901

Projet de classification de spectres stellaires IUE à basse résolution par système expert.

NASA Astrophysics Data System (ADS)

Imadache, A.

Le project d'étude porte sur l'utilisation de l'intelligence artificielle en vue d'établir une classification de spectres IUE. Pour la réalisation de ce projet, des liens de collaboration ont été établis entre l'Observatoire Astronomique de Strasbourg et l'équipe ST-ECF à l'ESO.

Optimization and simplification of the Allergic and Hypersensitivity conditions classification for the ICD-11.

PubMed

Tanno, L K; Calderon, M A; Demoly, P

2016-05-01

Since 2013, an international collaboration of Allergy Academies, including first the World Allergy Organization (WAO), the American Academy of Allergy Asthma and Immunology (AAAAI), and the European Academy of Allergy and Clinical Immunology (EAACI), and then the American College of Allergy, Asthma and Immunology (ACAAI), the Latin American Society of Allergy, Asthma and Immunology (SLAAI), and the Asia Pacific Association of Allergy, Asthma and Clinical Immunology (APAAACI), has spent tremendous efforts to have a better and updated classification of allergic and hypersensitivity conditions in the forthcoming International Classification of Diseases (ICD)-11 version by providing evidences and promoting actions for the need for changes. The latest action was the implementation of a classification proposal of hypersensitivity/allergic diseases built by crowdsourcing the Allergy Academy leaderships. Following bilateral discussions with the representatives of the ICD-11 revision, a face-to-face meeting was held at the United Nations Office in Geneva and a simplification process of the hypersensitivity/allergic disorders classification was carried out to better fit the ICD structure. We are here presenting the end result of what we consider to be a model of good collaboration between the World Health Organization and a specialty. We strongly believe that the outcomes of all past and future actions will impact positively the recognition of the allergy specialty as well as the quality improvement of healthcare system for allergic and hypersensitivity conditions worldwide. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Advances in Risk Classification and Treatment Strategies for Neuroblastoma.

PubMed

Pinto, Navin R; Applebaum, Mark A; Volchenboum, Samuel L; Matthay, Katherine K; London, Wendy B; Ambros, Peter F; Nakagawara, Akira; Berthold, Frank; Schleiermacher, Gudrun; Park, Julie R; Valteau-Couanet, Dominique; Pearson, Andrew D J; Cohn, Susan L

2015-09-20

Risk-based treatment approaches for neuroblastoma have been ongoing for decades. However, the criteria used to define risk in various institutional and cooperative groups were disparate, limiting the ability to compare clinical trial results. To mitigate this problem and enhance collaborative research, homogenous pretreatment patient cohorts have been defined by the International Neuroblastoma Risk Group classification system. During the past 30 years, increasingly intensive, multimodality approaches have been developed to treat patients who are classified as high risk, whereas patients with low- or intermediate-risk neuroblastoma have received reduced therapy. This treatment approach has resulted in improved outcome, although survival for high-risk patients remains poor, emphasizing the need for more effective treatments. Increased knowledge regarding the biology and genetic basis of neuroblastoma has led to the discovery of druggable targets and promising, new therapeutic approaches. Collaborative efforts of institutions and international cooperative groups have led to advances in our understanding of neuroblastoma biology, refinements in risk classification, and stratified treatment strategies, resulting in improved outcome. International collaboration will be even more critical when evaluating therapies designed to treat small cohorts of patients with rare actionable mutations. © 2015 by American Society of Clinical Oncology.

Developing a case mix classification for child and adolescent mental health services: the influence of presenting problems, complexity factors and service providers on number of appointments.

PubMed

Martin, Peter; Davies, Roger; Macdougall, Amy; Ritchie, Benjamin; Vostanis, Panos; Whale, Andy; Wolpert, Miranda

2017-09-01

Case-mix classification is a focus of international attention in considering how best to manage and fund services, by providing a basis for fairer comparison of resource utilization. Yet there is little evidence of the best ways to establish case mix for child and adolescent mental health services (CAMHS). To develop a case mix classification for CAMHS that is clinically meaningful and predictive of number of appointments attended and to investigate the influence of presenting problems, context and complexity factors and provider variation. We analysed 4573 completed episodes of outpatient care from 11 English CAMHS. Cluster analysis, regression trees and a conceptual classification based on clinical best practice guidelines were compared regarding their ability to predict number of appointments, using mixed effects negative binomial regression. The conceptual classification is clinically meaningful and did as well as data-driven classifications in accounting for number of appointments. There was little evidence for effects of complexity or context factors, with the possible exception of school attendance problems. Substantial variation in resource provision between providers was not explained well by case mix. The conceptually-derived classification merits further testing and development in the context of collaborative decision making.

Analysis of Leading Edge and Trailing Edge Cover Glass Samples Before and After Treatment with Advanced Satellite Contamination Removal Techniques

DTIC Science & Technology

1993-04-01

surface analysis, 40 contamination control, ANCC ( Aerogel Mesh Contamination Collector) iPRICECODE 17. SECURITY CLASSIFICATION 1 & SECURITY CLASSIFICATION...operational parameter space (temperature, vibration, radiation, vacuum and micrometorite environments). One embodiment of this device, the Aerogel Mesh...Lippey and Dan Demeo of Hughes Aircraft Corporation for their kind hospitality and research collaboration on the contamination removal phase of this work

From Classification to Epilepsy Ontology and Informatics

PubMed Central

Zhang, Guo-Qiang; Sahoo, Satya S; Lhatoo, Samden D

2012-01-01

Summary The 2010 International League Against Epilepsy (ILAE) classification and terminology commission report proposed a much needed departure from previous classifications to incorporate advances in molecular biology, neuroimaging, and genetics. It proposed an interim classification and defined two key requirements that need to be satisfied. The first is the ability to classify epilepsy in dimensions according to a variety of purposes including clinical research, patient care, and drug discovery. The second is the ability of the classification system to evolve with new discoveries. Multi-dimensionality and flexibility are crucial to the success of any future classification. In addition, a successful classification system must play a central role in the rapidly growing field of epilepsy informatics. An epilepsy ontology, based on classification, will allow information systems to facilitate data-intensive studies and provide a proven route to meeting the two foregoing key requirements. Epilepsy ontology will be a structured terminology system that accommodates proposed and evolving ILAE classifications, the NIH/NINDS Common Data Elements, the ICD systems and explicitly specifies all known relationships between epilepsy concepts in a proper framework. This will aid evidence based epilepsy diagnosis, investigation, treatment and research for a diverse community of clinicians and researchers. Benefits range from systematization of electronic patient records to multi-modal data repositories for research and training manuals for those involved in epilepsy care. Given the complexity, heterogeneity and pace of research advances in the epilepsy domain, such an ontology must be collaboratively developed by key stakeholders in the epilepsy community and experts in knowledge engineering and computer science. PMID:22765502

A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features

NASA Astrophysics Data System (ADS)

Srinivasan, Yeshwanth; Hernes, Dana; Tulpule, Bhakti; Yang, Shuyu; Guo, Jiangling; Mitra, Sunanda; Yagneswaran, Sriraja; Nutter, Brian; Jeronimo, Jose; Phillips, Benny; Long, Rodney; Ferris, Daron

2005-04-01

Automated segmentation and classification of diagnostic markers in medical imagery are challenging tasks. Numerous algorithms for segmentation and classification based on statistical approaches of varying complexity are found in the literature. However, the design of an efficient and automated algorithm for precise classification of desired diagnostic markers is extremely image-specific. The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating an archive of 60,000 digitized color images of the uterine cervix. NLM is developing tools for the analysis and dissemination of these images over the Web for the study of visual features correlated with precancerous neoplasia and cancer. To enable indexing of images of the cervix, it is essential to develop algorithms for the segmentation of regions of interest, such as acetowhitened regions, and automatic identification and classification of regions exhibiting mosaicism and punctation. Success of such algorithms depends, primarily, on the selection of relevant features representing the region of interest. We present color and geometric features based statistical classification and segmentation algorithms yielding excellent identification of the regions of interest. The distinct classification of the mosaic regions from the non-mosaic ones has been obtained by clustering multiple geometric and color features of the segmented sections using various morphological and statistical approaches. Such automated classification methodologies will facilitate content-based image retrieval from the digital archive of uterine cervix and have the potential of developing an image based screening tool for cervical cancer.

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

ERIC Educational Resources Information Center

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

Inventory and comparative evaluation of seabed mapping, classification and modeling activities in the Northwest Atlantic, USA to support regional ocean planning

NASA Astrophysics Data System (ADS)

Shumchenia, Emily J.; Guarinello, Marisa L.; Carey, Drew A.; Lipsky, Andrew; Greene, Jennifer; Mayer, Larry; Nixon, Matthew E.; Weber, John

2015-06-01

Efforts are in motion globally to address coastal and marine management needs through spatial planning and concomitant seabed habitat mapping. Contrasting strategies are often evident in these processes among local, regional, national and international scientific approaches and policy needs. In answer to such contrasts among its member states, the United States Northeast Regional Ocean Council formed a Habitat Working Group to conduct a regional inventory and comparative evaluation of seabed characterization, classification, and modeling activities in New England. The goals of this effort were to advance regional understanding of ocean habitats and identify opportunities for collaboration. Working closely with the Habitat Working Group, we organized and led the inventory and comparative analysis with a focus on providing processes and tools that can be used by scientists and managers, updated and adapted for future use, and applied in other ocean management regions throughout the world. Visual schematics were a critical component of the comparative analysis and aided discussion among scientists and managers. Regional consensus was reached on a common habitat classification scheme (U.S. Coastal and Marine Ecological Classification Standard) for regional seabed maps. Results and schematics were presented at a region-wide workshop where further steps were taken to initiate collaboration among projects. The workshop culminated in an agreement on a set of future seabed mapping goals for the region. The work presented here may serve as an example to other ocean planning regions in the U.S., Europe or elsewhere seeking to integrate a variety of seabed characterization, classification and modeling activities.

International Classification for Nursing Practice (ICNP)

PubMed Central

Warren, Judith J.; Coenen, Amy

1998-01-01

The International Classification for Nursing Practice (ICNP) is a collaborative project under the auspices of the International Council of Nurses. The alpha version ia available online for comment in preparation for the release of the beta version in 1999. The authors answer the most-frequently asked questions about the ICNP and encourage nurses in the United States to participate in the revision by sending comments and suggestions to the American Nurses Association. PMID:9670130

Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains

PubMed Central

Walk, Simon; Singer, Philipp; Strohmaier, Markus; Tudorache, Tania; Musen, Mark A.; Noy, Natalya F.

2014-01-01

Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the International Classification of Diseases, which is currently under active development by the World Health Organization contains nearly 50, 000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding the way these different stakeholders collaborate will enable us to improve editing environments that support such collaborations. In this paper, we uncover how large ontology-engineering projects, such as the International Classification of Diseases in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users frequently change after specific given ones) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology-engineering projects and tools in the biomedical domain. PMID:24953242

Discovering beaten paths in collaborative ontology-engineering projects using Markov chains.

PubMed

Walk, Simon; Singer, Philipp; Strohmaier, Markus; Tudorache, Tania; Musen, Mark A; Noy, Natalya F

2014-10-01

Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the International Classification of Diseases, which is currently under active development by the World Health Organization contains nearly 50,000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding the way these different stakeholders collaborate will enable us to improve editing environments that support such collaborations. In this paper, we uncover how large ontology-engineering projects, such as the International Classification of Diseases in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users frequently change after specific given ones) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology-engineering projects and tools in the biomedical domain. Copyright © 2014 Elsevier Inc. All rights reserved.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

Nursing's next advance: an internal classification for nursing practice.

PubMed

Clark, J; Lang, N

1992-01-01

An International Classification of Nursing Practice (ICNP) is needed to support the processes of nursing practice and advance the knowledge necessary for cost-effective delivery of quality nursing care. Below, the authors present their case for developing such a system that will provide nursing with a nomenclature, a language and a classification that can be used to describe and organize nursing data. It is their belief that this landmark project is achievable and that ICN should lead the work in collaboration with its member associations, the World Health Organization and key national, international, governmental and nongovernmental groups. But to ensure that the system will be adaptable across borders, nurses and organizations are being encouraged to share their ideas and research on such a system.

Analyzing Collaborative Learning Processes Automatically: Exploiting the Advances of Computational Linguistics in Computer-Supported Collaborative Learning

ERIC Educational Resources Information Center

Rose, Carolyn; Wang, Yi-Chia; Cui, Yue; Arguello, Jaime; Stegmann, Karsten; Weinberger, Armin; Fischer, Frank

2008-01-01

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners' interactions is a…

Harnessing user generated multimedia content in the creation of collaborative classification structures and retrieval learning games

NASA Astrophysics Data System (ADS)

Borchert, Otto Jerome

This paper describes a software tool to assist groups of people in the classification and identification of real world objects called the Classification, Identification, and Retrieval-based Collaborative Learning Environment (CIRCLE). A thorough literature review identified current pedagogical theories that were synthesized into a series of five tasks: gathering, elaboration, classification, identification, and reinforcement through game play. This approach is detailed as part of an included peer reviewed paper. Motivation is increased through the use of formative and summative gamification; getting points completing important portions of the tasks and playing retrieval learning based games, respectively, which is also included as a peer-reviewed conference proceedings paper. Collaboration is integrated into the experience through specific tasks and communication mediums. Implementation focused on a REST-based client-server architecture. The client is a series of web-based interfaces to complete each of the tasks, support formal classroom interaction through faculty accounts and student tracking, and a module for peers to help each other. The server, developed using an in-house JavaMOO platform, stores relevant project data and serves data through a series of messages implemented as a JavaScript Object Notation Application Programming Interface (JSON API). Through a series of two beta tests and two experiments, it was discovered the second, elaboration, task requires considerable support. While students were able to properly suggest experiments and make observations, the subtask involving cleaning the data for use in CIRCLE required extra support. When supplied with more structured data, students were enthusiastic about the classification and identification tasks, showing marked improvement in usability scores and in open ended survey responses. CIRCLE tracks a variety of educationally relevant variables, facilitating support for instructors and researchers. Future work will revolve around material development, software refinement, and theory building. Curricula, lesson plans, instructional materials need to be created to seamlessly integrate CIRCLE in a variety of courses. Further refinement of the software will focus on improving the elaboration interface and developing further game templates to add to the motivation and retrieval learning aspects of the software. Data gathered from CIRCLE experiments can be used to develop and strengthen theories on teaching and learning.

Spatial-temporal discriminant analysis for ERP-based brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Zhao, Qibin; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2013-03-01

Linear discriminant analysis (LDA) has been widely adopted to classify event-related potential (ERP) in brain-computer interface (BCI). Good classification performance of the ERP-based BCI usually requires sufficient data recordings for effective training of the LDA classifier, and hence a long system calibration time which however may depress the system practicability and cause the users resistance to the BCI system. In this study, we introduce a spatial-temporal discriminant analysis (STDA) to ERP classification. As a multiway extension of the LDA, the STDA method tries to maximize the discriminant information between target and nontarget classes through finding two projection matrices from spatial and temporal dimensions collaboratively, which reduces effectively the feature dimensionality in the discriminant analysis, and hence decreases significantly the number of required training samples. The proposed STDA method was validated with dataset II of the BCI Competition III and dataset recorded from our own experiments, and compared to the state-of-the-art algorithms for ERP classification. Online experiments were additionally implemented for the validation. The superior classification performance in using few training samples shows that the STDA is effective to reduce the system calibration time and improve the classification accuracy, thereby enhancing the practicability of ERP-based BCI.

2015 Gout classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative

PubMed Central

Neogi, Tuhina; Jansen, Tim L Th A; Dalbeth, Nicola; Fransen, Jaap; Schumacher, H Ralph; Berendsen, Dianne; Brown, Melanie; Choi, Hyon; Edwards, N Lawrence; Janssens, Hein J E M; Lioté, Frédéric; Naden, Raymond P; Nuki, George; Ogdie, Alexis; Perez-Ruiz, Fernando; Saag, Kenneth; Singh, Jasvinder A; Sundy, John S; Tausche, Anne-Kathrin; Vaquez-Mellado, Janitzia; Yarows, Steven A; Taylor, William J

2015-01-01

Objective Existing criteria for the classification of gout have suboptimal sensitivity and/or specificity, and were developed at a time when advanced imaging was not available. The current effort was undertaken to develop new classification criteria for gout. Methods An international group of investigators, supported by the American College of Rheumatology and the European League Against Rheumatism, conducted a systematic review of the literature on advanced imaging of gout, a diagnostic study in which the presence of monosodium urate monohydrate (MSU) crystals in synovial fluid or tophus was the gold standard, a ranking exercise of paper patient cases, and a multi-criterion decision analysis exercise. These data formed the basis for developing the classification criteria, which were tested in an independent data set. Results The entry criterion for the new classification criteria requires the occurrence of at least one episode of peripheral joint or bursal swelling, pain, or tenderness. The presence of MSU crystals in a symptomatic joint/bursa (ie, synovial fluid) or in a tophus is a sufficient criterion for classification of the subject as having gout, and does not require further scoring. The domains of the new classification criteria include clinical (pattern of joint/bursa involvement, characteristics and time course of symptomatic episodes), laboratory (serum urate, MSU-negative synovial fluid aspirate), and imaging (double-contour sign on ultrasound or urate on dual-energy CT, radiographic gout-related erosion). The sensitivity and specificity of the criteria are high (92% and 89%, respectively). Conclusions The new classification criteria, developed using a data-driven and decision-analytic approach, have excellent performance characteristics and incorporate current state-of-the-art evidence regarding gout. PMID:26359487

2015 Gout Classification Criteria: An American College of Rheumatology/European League Against Rheumatism Collaborative Initiative

PubMed Central

Jansen, Tim L. Th. A.; Dalbeth, Nicola; Fransen, Jaap; Schumacher, H. Ralph; Berendsen, Dianne; Brown, Melanie; Choi, Hyon; Edwards, N. Lawrence; Janssens, Hein J. E. M.; Lioté, Frédéric; Naden, Raymond P.; Nuki, George; Ogdie, Alexis; Perez‐Ruiz, Fernando; Saag, Kenneth; Singh, Jasvinder A.; Sundy, John S.; Tausche, Anne‐Kathrin; Vaquez‐Mellado, Janitzia; Yarows, Steven A.; Taylor, William J.

2015-01-01

Objective Existing criteria for the classification of gout have suboptimal sensitivity and/or specificity, and were developed at a time when advanced imaging was not available. The current effort was undertaken to develop new classification criteria for gout. Methods An international group of investigators, supported by the American College of Rheumatology and the European League Against Rheumatism, conducted a systematic review of the literature on advanced imaging of gout, a diagnostic study in which the presence of monosodium urate monohydrate (MSU) crystals in synovial fluid or tophus was the gold standard, a ranking exercise of paper patient cases, and a multicriterion decision analysis exercise. These data formed the basis for developing the classification criteria, which were tested in an independent data set. Results The entry criterion for the new classification criteria requires the occurrence of at least 1 episode of peripheral joint or bursal swelling, pain, or tenderness. The presence of MSU crystals in a symptomatic joint/bursa (i.e., synovial fluid) or in a tophus is a sufficient criterion for classification of the subject as having gout, and does not require further scoring. The domains of the new classification criteria include clinical (pattern of joint/bursa involvement, characteristics and time course of symptomatic episodes), laboratory (serum urate, MSU‐negative synovial fluid aspirate), and imaging (double‐contour sign on ultrasound or urate on dual‐energy computed tomography, radiographic gout‐related erosion). The sensitivity and specificity of the criteria are high (92% and 89%, respectively). Conclusion The new classification criteria, developed using a data‐driven and decision analytic approach, have excellent performance characteristics and incorporate current state‐of‐the‐art evidence regarding gout. PMID:26352873

Evaluation of the ACR and SLICC classification criteria in juvenile-onset systemic lupus erythematosus: a longitudinal analysis.

PubMed

Lythgoe, H; Morgan, T; Heaf, E; Lloyd, O; Al-Abadi, E; Armon, K; Bailey, K; Davidson, J; Friswell, M; Gardner-Medwin, J; Haslam, K; Ioannou, Y; Leahy, A; Leone, V; Pilkington, C; Rangaraj, S; Riley, P; Tizard, E J; Wilkinson, N; Beresford, M W

2017-10-01

Objectives The Systemic Lupus International Collaborating Clinics (SLICC) group proposed revised classification criteria for systemic lupus erythematosus (SLICC-2012 criteria). This study aimed to compare these criteria with the well-established American College of Rheumatology classification criteria (ACR-1997 criteria) in a national cohort of juvenile-onset systemic lupus erythematosus (JSLE) patients and evaluate how patients' classification criteria evolved over time. Methods Data from patients in the UK JSLE Cohort Study with a senior clinician diagnosis of probable evolving, or definite JSLE, were analyzed. Patients were assessed using both classification criteria within 1 year of diagnosis and at latest follow up (following a minimum 12-month follow-up period). Results A total of 226 patients were included. The SLICC-2012 was more sensitive than ACR-1997 at diagnosis (92.9% versus 84.1% p < 0.001) and after follow up (100% versus 92.0% p < 0.001). Most patients meeting the SLICC-2012 criteria and not the ACR-1997 met more than one additional criterion on the SLICC-2012. Conclusions The SLICC-2012 was better able to classify patients with JSLE than the ACR-1997 and did so at an earlier stage in their disease course. SLICC-2012 should be considered for classification of JSLE patients in observational studies and clinical trial eligibility.

Sleep versus wake classification from heart rate variability using computational intelligence: consideration of rejection in classification models.

PubMed

Lewicke, Aaron; Sazonov, Edward; Corwin, Michael J; Neuman, Michael; Schuckers, Stephanie

2008-01-01

Reliability of classification performance is important for many biomedical applications. A classification model which considers reliability in the development of the model such that unreliable segments are rejected would be useful, particularly, in large biomedical data sets. This approach is demonstrated in the development of a technique to reliably determine sleep and wake using only the electrocardiogram (ECG) of infants. Typically, sleep state scoring is a time consuming task in which sleep states are manually derived from many physiological signals. The method was tested with simultaneous 8-h ECG and polysomnogram (PSG) determined sleep scores from 190 infants enrolled in the collaborative home infant monitoring evaluation (CHIME) study. Learning vector quantization (LVQ) neural network, multilayer perceptron (MLP) neural network, and support vector machines (SVMs) are tested as the classifiers. After systematic rejection of difficult to classify segments, the models can achieve 85%-87% correct classification while rejecting only 30% of the data. This corresponds to a Kappa statistic of 0.65-0.68. With rejection, accuracy improves by about 8% over a model without rejection. Additionally, the impact of the PSG scored indeterminate state epochs is analyzed. The advantages of a reliable sleep/wake classifier based only on ECG include high accuracy, simplicity of use, and low intrusiveness. Reliability of the classification can be built directly in the model, such that unreliable segments are rejected.

Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223

Single-Trial Classification of Multi-User P300-Based Brain-Computer Interface Using Riemannian Geometry.

PubMed

Korczowski, L; Congedo, M; Jutten, C

2015-08-01

The classification of electroencephalographic (EEG) data recorded from multiple users simultaneously is an important challenge in the field of Brain-Computer Interface (BCI). In this paper we compare different approaches for classification of single-trials Event-Related Potential (ERP) on two subjects playing a collaborative BCI game. The minimum distance to mean (MDM) classifier in a Riemannian framework is extended to use the diversity of the inter-subjects spatio-temporal statistics (MDM-hyper) or to merge multiple classifiers (MDM-multi). We show that both these classifiers outperform significantly the mean performance of the two users and analogous classifiers based on the step-wise linear discriminant analysis. More importantly, the MDM-multi outperforms the performance of the best player within the pair.

Classification of High Spatial Resolution, Hyperspectral ...

EPA Pesticide Factsheets

EPA announced the availability of the final report,

Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field

ERIC Educational Resources Information Center

Magnisalis, I.; Demetriadis, S.; Karakostas, A.

2011-01-01

This study critically reviews the recently published scientific literature on the design and impact of adaptive and intelligent systems for collaborative learning support (AICLS) systems. The focus is threefold: 1) analyze critical design issues of AICLS systems and organize them under a unifying classification scheme, 2) present research evidence…

YTPdb: a wiki database of yeast membrane transporters.

PubMed

Brohée, Sylvain; Barriot, Roland; Moreau, Yves; André, Bruno

2010-10-01

Membrane transporters constitute one of the largest functional categories of proteins in all organisms. In the yeast Saccharomyces cerevisiae, this represents about 300 proteins ( approximately 5% of the proteome). We here present the Yeast Transport Protein database (YTPdb), a user-friendly collaborative resource dedicated to the precise classification and annotation of yeast transporters. YTPdb exploits an evolution of the MediaWiki web engine used for popular collaborative databases like Wikipedia, allowing every registered user to edit the data in a user-friendly manner. Proteins in YTPdb are classified on the basis of functional criteria such as subcellular location or their substrate compounds. These classifications are hierarchical, allowing queries to be performed at various levels, from highly specific (e.g. ammonium as a substrate or the vacuole as a location) to broader (e.g. cation as a substrate or inner membranes as location). Other resources accessible for each transporter via YTPdb include post-translational modifications, K(m) values, a permanently updated bibliography, and a hierarchical classification into families. The YTPdb concept can be extrapolated to other organisms and could even be applied for other functional categories of proteins. YTPdb is accessible at http://homes.esat.kuleuven.be/ytpdb/. Copyright © 2010 Elsevier B.V. All rights reserved.

Parents' Experiences and Perceptions when Classifying their Children with Cerebral Palsy: Recommendations for Service Providers.

PubMed

Scime, Natalie V; Bartlett, Doreen J; Brunton, Laura K; Palisano, Robert J

2017-08-01

This study investigated the experiences and perceptions of parents of children with cerebral palsy (CP) when classifying their children using the Gross Motor Function Classification System (GMFCS), the Manual Ability Classification System (MACS), and the Communication Function Classification System (CFCS). The second aim was to collate parents' recommendations for service providers on how to interact and communicate with families. A purposive sample of seven parents participating in the On Track study was recruited. Semi-structured interviews were conducted orally and were audiotaped, transcribed, and coded openly. A descriptive interpretive approach within a pragmatic perspective was used during analysis. Seven themes encompassing parents' experiences and perspectives reflect a process of increased understanding when classifying their children, with perceptions of utility evident throughout this process. Six recommendations for service providers emerged, including making the child a priority and being a dependable resource. Knowledge of parents' experiences when using the GMFCS, MACS, and CFCS can provide useful insight for service providers collaborating with parents to classify function in children with CP. Using the recommendations from these parents can facilitate family-provider collaboration for goal setting and intervention planning.

The IASLC/ITMIG thymic malignancies staging project: development of a stage classification for thymic malignancies.

PubMed

Detterbeck, Frank C; Asamura, Hisao; Crowley, John; Falkson, Conrad; Giaccone, Giuseppe; Giroux, Dori; Huang, James; Kim, Jhingook; Kondo, Kazuya; Lucchi, Marco; Marino, Mirella; Marom, Edith M; Nicholson, Andrew; Okumura, Meinoshin; Ruffini, Enrico; van Schil, Paul; Stratton, Kelly

2013-12-01

The lack of an official-stage classification system for thymic malignancies is an issue that hampers progress in this rare disease. A collaborative effort by the International Association for the Study of Lung Cancer and the International Thymic Malignancies Interest Group is underway to develop proposals for such a system. A database of more than 10,000 cases worldwide has been assembled to provide a solid basis for analysis. This report outlines the structure of the effort and the process that has been designed.

Investigation of Three-Group Classifiers to Fully Automate Detection and Classification of Breast Lesions in an Intelligent CAD Mammography Workstation

DTIC Science & Technology

2007-05-01

evaluation of approximations,” tech. rep., Dep. Sistemes Informàtics i Computació, Univ. Politècnica de València (Spain), 2003. [7] D. C. Edwards, C. E...Maryellen L. Giger, scientific collaborator • Lorenzo Pesce, computer programmer 16 C The Hypervolume under the ROC Hypersurface of “Near-Guessing...the simple model we have just described corresponds in the two-class classification task to ROC analysis performed ‘‘per ARTICLE IN PRESS

An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises

NASA Astrophysics Data System (ADS)

Jokar Arsanjani, Jamal; Vaz, Eric

2015-03-01

Until recently, land surveys and digital interpretation of remotely sensed imagery have been used to generate land use inventories. These techniques however, are often cumbersome and costly, allocating large amounts of technical and temporal costs. The technological advances of web 2.0 have brought a wide array of technological achievements, stimulating the participatory role in collaborative and crowd sourced mapping products. This has been fostered by GPS-enabled devices, and accessible tools that enable visual interpretation of high resolution satellite images/air photos provided in collaborative mapping projects. Such technologies offer an integrative approach to geography by means of promoting public participation and allowing accurate assessment and classification of land use as well as geographical features. OpenStreetMap (OSM) has supported the evolution of such techniques, contributing to the existence of a large inventory of spatial land use information. This paper explores the introduction of this novel participatory phenomenon for land use classification in Europe's metropolitan regions. We adopt a positivistic approach to assess comparatively the accuracy of these contributions of OSM for land use classifications in seven large European metropolitan regions. Thematic accuracy and degree of completeness of OSM data was compared to available Global Monitoring for Environment and Security Urban Atlas (GMESUA) datasets for the chosen metropolises. We further extend our findings of land use within a novel framework for geography, justifying that volunteered geographic information (VGI) sources are of great benefit for land use mapping depending on location and degree of VGI dynamism and offer a great alternative to traditional mapping techniques for metropolitan regions throughout Europe. Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification. These classes are highly accurate and can be integrated into planning decisions for stakeholders and policymakers.

Unlocking the full potential of open innovation in the life sciences through a classification system.

PubMed

Nilsson, Niclas; Minssen, Timo

2018-04-01

A common understanding of expectations and requirements is critical for boosting research-driven business opportunities in open innovation (OI) settings. Transparent communication requires common definitions and standards for OI to align the expectations of both parties. Here, we suggest a five-level classification system for OI models, reflecting the degree of openness. The aim of this classification system is to reduce contract negotiation complexity and times between two parties looking to engage in OI. Systematizing definitions and contractual terms for OI in the life sciences helps to reduce entry barriers and boosts collaborative value generation. By providing a contractual framework with predefined rules, science will be allowed to move more freely, thus maximizing the potential of OI. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Deciphering Suicide and Other Manners of Death Associated with Drug Intoxication: A Centers for Disease Control and Prevention Consultation Meeting Summary.

PubMed

Stone, Deborah M; Holland, Kristin M; Bartholow, Brad; E Logan, Joseph; LiKamWa McIntosh, Wendy; Trudeau, Aimee; Rockett, Ian R H

2017-08-01

Manner of death (MOD) classification (i.e., natural, accident, suicide, homicide, or undetermined cause) affects mortality surveillance and public health research, policy, and practice. Determination of MOD in deaths caused by drug intoxication is challenging, with marked variability across states. The Centers for Disease Control and Prevention hosted a multidisciplinary meeting to discuss drug intoxication deaths as they relate to suicide and other MOD. The meeting objectives were to identify individual-level, system-level, and place-based factors affecting MOD classification and identify potential solutions to classification barriers. Suggested strategies included improved standardization in death scene investigation, toxicology, and autopsy practice; greater accountability; and creation of job aids for investigators. Continued collaboration and coordination of activities are needed among stakeholders to affect prevention efforts.

Reliability of classification for post-traumatic ankle osteoarthritis.

PubMed

Claessen, Femke M A P; Meijer, Diederik T; van den Bekerom, Michel P J; Gevers Deynoot, Barend D J; Mallee, Wouter H; Doornberg, Job N; van Dijk, C Niek

2016-04-01

The purpose of this study was to identify the most reliable classification system for clinical outcome studies to categorize post-traumatic-fracture-osteoarthritis. A total of 118 orthopaedic surgeons and residents-gathered in the Ankle Platform Study Collaborative Science of Variation Group-evaluated 128 anteroposterior and lateral radiographs of patients after a bi- or trimalleolar ankle fracture on a Web-based platform in order to rate post-traumatic osteoarthritis according to the classification systems coined by (1) van Dijk, (2) Kellgren, and (3) Takakura. Reliability was evaluated with the use of the Siegel and Castellan's multirater kappa measure. Differences between classification systems were compared using the two-sample Z-test. Interobserver agreement of surgeons who participated in the survey was fair for the van Dijk osteoarthritis scale (k = 0.24), and poor for the Takakura (k = 0.19) and the Kellgren systems (k = 0.18) according to the categorical rating of Landis and Koch. This difference in one categorical rating was found to be significant (p < 0.001, CI 0.046-0.053) with the high numbers of observers and cases available. This study documents fair interobserver agreement for the van Dijk osteoarthritis scale, and poor interobserver agreement for the Takakura and Kellgren osteoarthritis classification systems. Because of the low interobserver agreement for the van Dijk, Kellgren, and Takakura classification systems, those systems cannot be used for clinical decision-making. Development of diagnostic criteria on basis of consecutive patients, Level II.

A machine learning approach for viral genome classification.

PubMed

Remita, Mohamed Amine; Halioui, Ahmed; Malick Diouara, Abou Abdallah; Daigle, Bruno; Kiani, Golrokh; Diallo, Abdoulaye Baniré

2017-04-11

Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristics and disease mechanisms. Existing classification methods are often designed for specific well-studied family of viruses. Thus, the viral comparative genomic studies could benefit from more generic, fast and accurate tools for classifying and typing newly sequenced strains of diverse virus families. Here, we introduce a virus classification platform, CASTOR, based on machine learning methods. CASTOR is inspired by a well-known technique in molecular biology: restriction fragment length polymorphism (RFLP). It simulates, in silico, the restriction digestion of genomic material by different enzymes into fragments. It uses two metrics to construct feature vectors for machine learning algorithms in the classification step. We benchmark CASTOR for the classification of distinct datasets of human papillomaviruses (HPV), hepatitis B viruses (HBV) and human immunodeficiency viruses type 1 (HIV-1). Results reveal true positive rates of 99%, 99% and 98% for HPV Alpha species, HBV genotyping and HIV-1 M subtyping, respectively. Furthermore, CASTOR shows a competitive performance compared to well-known HIV-1 specific classifiers (REGA and COMET) on whole genomes and pol fragments. The performance of CASTOR, its genericity and robustness could permit to perform novel and accurate large scale virus studies. The CASTOR web platform provides an open access, collaborative and reproducible machine learning classifiers. CASTOR can be accessed at http://castor.bioinfo.uqam.ca .

A robust probabilistic collaborative representation based classification for multimodal biometrics

NASA Astrophysics Data System (ADS)

Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

2018-04-01

Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

Categorization of allergic disorders in the new World Health Organization International Classification of Diseases.

PubMed

Tanno, Luciana Kase; Calderon, Moises A; Goldberg, Bruce J; Akdis, Cezmi A; Papadopoulos, Nikolaos G; Demoly, Pascal

2014-01-01

Although efforts to improve the classification of hypersensitivity/allergic diseases have been made, they have not been considered a top-level category in the International Classification of Diseases (ICD)-10 and still are not in the ICD-11 beta phase linearization. ICD-10 is the most used classification system by the allergy community worldwide but it is not considered as appropriate for clinical practice. The Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) on the other hand contains a tightly integrated classification of hypersensitivity/allergic disorders based on the EAACI/WAO nomenclature and the World Health Organization (WHO) may plan to align ICD-11 with SNOMED CT so that they share a common ontological basis. With the aim of actively supporting the ongoing ICD-11 revision and the optimal practice of Allergology, we performed a careful comparison of ICD-10 and 11 beta phase linearization codes to identify gaps, areas of regression in allergy coding and possibly reach solutions, in collaboration with committees in charge of the ICD-11 revision. We have found a significant degree of misclassification of terms in the allergy-related hierarchies. This stems not only from unclear definitions of these conditions but also the use of common names that falsely imply allergy. The lack of understanding of the immune mechanisms underlying some of the conditions contributes to the difficulty in classification. More than providing data to support specific changes into the ongoing linearization, these results highlight the need for either a new chapter entitled Hypersensitivity/Allergic Disorders as in SNOMED CT or a high level structure in the Immunology chapter in order to make classification more appropriate and usable.

2016 Classification Criteria for Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis: A European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation Collaborative Initiative.

PubMed

Ravelli, Angelo; Minoia, Francesca; Davì, Sergio; Horne, AnnaCarin; Bovis, Francesca; Pistorio, Angela; Aricò, Maurizio; Avcin, Tadej; Behrens, Edward M; De Benedetti, Fabrizio; Filipovic, Lisa; Grom, Alexei A; Henter, Jan-Inge; Ilowite, Norman T; Jordan, Michael B; Khubchandani, Raju; Kitoh, Toshiyuki; Lehmberg, Kai; Lovell, Daniel J; Miettunen, Paivi; Nichols, Kim E; Ozen, Seza; Pachlopnik Schmid, Jana; Ramanan, Athimalaipet V; Russo, Ricardo; Schneider, Rayfel; Sterba, Gary; Uziel, Yosef; Wallace, Carol; Wouters, Carine; Wulffraat, Nico; Demirkaya, Erkan; Brunner, Hermine I; Martini, Alberto; Ruperto, Nicolino; Cron, Randy Q

2016-03-01

To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ = 0.76). We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies. © 2015, American College of Rheumatology.

Cooperative Autonomous Robots for Reconnaissance

DTIC Science & Technology

2009-03-06

REPORT Cooperative Autonomous Robots for Reconnaissance 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Collaborating mobile robots equipped with WiFi ...Cooperative Autonomous Robots for Reconnaissance Report Title ABSTRACT Collaborating mobile robots equipped with WiFi transceivers are configured as a mobile...equipped with WiFi transceivers are configured as a mobile ad-hoc network. Algorithms are developed to take advantage of the distributed processing

Decentralized asset management for collaborative sensing

NASA Astrophysics Data System (ADS)

Malhotra, Raj P.; Pribilski, Michael J.; Toole, Patrick A.; Agate, Craig

2017-05-01

There has been increased impetus to leverage Small Unmanned Aerial Systems (SUAS) for collaborative sensing applications in which many platforms work together to provide critical situation awareness in dynamic environments. Such applications require critical sensor observations to be made at the right place and time to facilitate the detection, tracking, and classification of ground-based objects. This further requires rapid response to real-world events and the balancing of multiple, competing mission objectives. In this context, human operators become overwhelmed with management of many platforms. Further, current automated planning paradigms tend to be centralized and don't scale up well to many collaborating platforms. We introduce a decentralized approach based upon information-theory and distributed fusion which enable us to scale up to large numbers of collaborating Small Unmanned Aerial Systems (SUAS) platforms. This is exercised against a military application involving the autonomous detection, tracking, and classification of critical mobile targets. We further show that, based upon monte-carlo simulation results, our decentralized approach out-performs more static management strategies employed by human operators and achieves similar results to a centralized approach while being scalable and robust to degradation of communication. Finally, we describe the limitations of our approach and future directions for our research.

Gout Classification Criteria: Update and Implications

PubMed Central

Vargas-Santos, Ana Beatriz; Taylor, William J.

2016-01-01

Gout is the most common inflammatory arthritis, with a rising prevalence and incidence worldwide. There has been a resurgence in gout research, fueled, in part, by a number of advances in pharmacologic therapy for gout. The conduct of clinical trials and other observational research in gout requires a standardized and validated means of assembling well-defined groups of patients with gout for such research purposes. Recently, an international collaborative effort that involved a data-driven process with state-of-the art methodology supported by the American College of Rheumatology and the European League Against Rheumatism led to publication of new gout classification criteria. PMID:27342957

A Web-Based Framework For a Time-Domain Warehouse

NASA Astrophysics Data System (ADS)

Brewer, J. M.; Bloom, J. S.; Kennedy, R.; Starr, D. L.

2009-09-01

The Berkeley Transients Classification Pipeline (TCP) uses a machine-learning classifier to automatically categorize transients from large data torrents and provide automated notification of astronomical events of scientific interest. As part of the training process, we created a large warehouse of light-curve sources with well-labelled classes that serve as priors to the classification engine. This web-based interactive framework, which we are now making public via DotAstro.org (http://dotastro.org/), allows us to ingest time-variable source data in a wide variety of formats and store it in a common internal data model. Data is passed between pipeline modules in a prototype XML representation of time-series format (VOTimeseries), which can also be emitted to collaborators through dotastro.org. After import, the sources can be visualized using Google Sky, light curves can be inspected interactively, and classifications can be manually adjusted.

A Scalable, Collaborative, Interactive Light-field Display System

DTIC Science & Technology

2014-06-01

displays, 3D display, holographic video, integral photography, plenoptic , computed photography 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...light-field, holographic displays, 3D display, holographic video, integral photography, plenoptic , computed photography 1 Distribution A: Approved

Collaborating with the Private Sector

DTIC Science & Technology

2009-08-01

private sector, laws, Patriot Act, FISA, FAR, Intellectual Property, Antitrust Law, Title 10, Title 50, FOIA, FACA, data classification, culture...33 Intellectual Property...Patriot Act) Foreign Intelligence Surveillance Act (FISA) Federal Acquisition Regulation (FAR) Intellectual Property Antitrust Law Title 10

Children's Interstitial and Diffuse Lung Disease. Progress and Future Horizons.

PubMed

Deterding, Robin R

2015-10-01

Children's interstitial and diffuse lung disease (chILD) is a term that encompasses a large and diverse group of rare pediatric diseases and disorders. Significant progress has been made over the last 2 decades in classification, clinical care, research, and organizational structure to enhance the care of children with these high-morbidity and -mortality diseases. New diseases have been defined clinically and genetically, classification systems developed and applied, organizations formed such as the chILD Research Network (chILDRN) and chILD Foundation, and basic and translational science expanded to focus on chILD diseases. Multidisciplinary collaborations and efforts to advance understanding and treatment of chILD have been extended worldwide. The future horizon holds great promise to expand scientific discoveries, collaborate more broadly, and bring new treatment to these children. An overview of key historical past developments, major clinical and research updates, and opportunities for the future in chILD is reviewed in this Perspective.

Reference Architecture for MNE 5 Technical System

DTIC Science & Technology

2007-05-30

of being available in most experiments. Core Services A core set of applications whi directories, web portal and collaboration applications etc. A...classifications Messages (xml, JMS, content level…) Meta data filtering, who can initiate services Web browsing Collaboration & messaging Border...Exchange Ref Architecture for MNE5 Tech System.doc 9 of 21 audit logging Person and machine Data lev objects, web services, messages rification el

Preclinical Mouse Models of Neurofibromatosis

DTIC Science & Technology

2004-10-01

collaborated closely and have shared expertise and reagents extensively. This NF Consortium is a member of the Moue Models of Human Cancer Consortium...of the National Cancer Institute and is participating fully in the activities of the group. The current award will support these collaborative...studies through 2005. 14. SUBJECT TERMS 15. NUMBER OF PAGES Neurofibromatosis, cancer , mouse models 48 16. PRICE CODE 17. SECURITY CLASSIFICATION 78

A comparative study: classification vs. user-based collaborative filtering for clinical prediction.

PubMed

Hao, Fang; Blair, Rachael Hageman

2016-12-08

Recommender systems have shown tremendous value for the prediction of personalized item recommendations for individuals in a variety of settings (e.g., marketing, e-commerce, etc.). User-based collaborative filtering is a popular recommender system, which leverages an individuals' prior satisfaction with items, as well as the satisfaction of individuals that are "similar". Recently, there have been applications of collaborative filtering based recommender systems for clinical risk prediction. In these applications, individuals represent patients, and items represent clinical data, which includes an outcome. Application of recommender systems to a problem of this type requires the recasting a supervised learning problem as unsupervised. The rationale is that patients with similar clinical features carry a similar disease risk. As the "Big Data" era progresses, it is likely that approaches of this type will be reached for as biomedical data continues to grow in both size and complexity (e.g., electronic health records). In the present study, we set out to understand and assess the performance of recommender systems in a controlled yet realistic setting. User-based collaborative filtering recommender systems are compared to logistic regression and random forests with different types of imputation and varying amounts of missingness on four different publicly available medical data sets: National Health and Nutrition Examination Survey (NHANES, 2011-2012 on Obesity), Study to Understand Prognoses Preferences Outcomes and Risks of Treatment (SUPPORT), chronic kidney disease, and dermatology data. We also examined performance using simulated data with observations that are Missing At Random (MAR) or Missing Completely At Random (MCAR) under various degrees of missingness and levels of class imbalance in the response variable. Our results demonstrate that user-based collaborative filtering is consistently inferior to logistic regression and random forests with different imputations on real and simulated data. The results warrant caution for the collaborative filtering for the purpose of clinical risk prediction when traditional classification is feasible and practical. CF may not be desirable in datasets where classification is an acceptable alternative. We describe some natural applications related to "Big Data" where CF would be preferred and conclude with some insights as to why caution may be warranted in this context.

Supervised classification of continental shelf sediment off western Donegal, Ireland

NASA Astrophysics Data System (ADS)

Monteys, X.; Craven, K.; McCarron, S. G.

2017-12-01

Managing human impacts on marine ecosystems requires natural regions to be identified and mapped over a range of hierarchically nested scales. In recent years (2000-present) the Irish National Seabed Survey (INSS) and Integrated Mapping for the Sustainable Development of Ireland's Marine Resources programme (INFOMAR) (Geological Survey Ireland and Marine Institute collaborations) has provided unprecedented quantities of high quality data on Ireland's offshore territories. The increasing availability of large, detailed digital representations of these environments requires the application of objective and quantitative analyses. This study presents results of a new approach for sea floor sediment mapping based on an integrated analysis of INFOMAR multibeam bathymetric data (including the derivatives of slope and relative position), backscatter data (including derivatives of angular response analysis) and sediment groundtruthing over the continental shelf, west of Donegal. It applies a Geographic-Object-Based Image Analysis software package to provide a supervised classification of the surface sediment. This approach can provide a statistically robust, high resolution classification of the seafloor. Initial results display a differentiation of sediment classes and a reduction in artefacts from previously applied methodologies. These results indicate a methodology that could be used during physical habitat mapping and classification of marine environments.

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

Men who have sex with men and women (MSMW), biphobia and the CDC: A bridge ignored?!

PubMed

Fernando, Daniel

2017-12-01

This is a letter to the editor on a Short Communication by a group of CDC researchers. It speaks of the importance of bisexual behavior in the transmission of HIV to heterosexual females. In this letter, I demonstrate that the differences between MSM only and MSMW have been discussed by CDC researchers and CDC collaborative researchers previously, although the CDC continues to maintain its original risk category classification, which undermines the role of bisexuals in HIV transmission to heterosexual females. In the CDC risk category classification where men who have sex with men and women (MSMW) are subsumed under the MSM category, it is impossible to know the extent of HIV transmission from MSMW to heterosexual women. Since more Blacks and Hispanics admit to bisexual behavior, the original CDC risk category classification has had a more serious adverse impact on minority communities. I argue that the CDC should change its risk category classification to include MSM only and MSMW as well as women who have sex with men only (WSM) and women who have sex with men and women (WSMW), even at this late stage. Copyright © 2017 Elsevier Inc. All rights reserved.

Controversial Issues Confronting Special Education: Divergent Perspectives.

ERIC Educational Resources Information Center

Stainback, William; Stainback, Susan

This book of 24 papers presents divergent views on 12 issues in special education: organizational strategies, classroom service delivery approaches, maximizing the talents and gifts of students, classification and labeling, assessment, instructional strategies, classroom management, collaboration/consultation, research practices, higher education,…

Spectroscopic classification of supernova SN 2018Z by NUTS (NOT Un-biased Transient Survey)

NASA Astrophysics Data System (ADS)

Kuncarayakti, H.; Mattila, S.; Kotak, R.; Harmanen, J.; Reynolds, T.; Pastorello, A.; Benetti, S.; Stritzinger, M.; Onori, F.; Somero, A.; Kangas, T.; Lundqvist, P.; Taddia, F.; Ergon, M.

2018-01-01

The NOT Unbiased Transient Survey (NUTS; ATel #8992) collaboration reports the spectroscopic classification of supernova SN 2018Z in host galaxy SDSS J231809.76+212553.5 The observations were performed with the 2.56 m Nordic Optical Telescope equipped with ALFOSC (range 350-950 nm; resolution 1.6 nm) on 2018-01-09.9 UT. Survey Name | IAU Name | Discovery (UT) | Discovery mag | Observation (UT) | Redshift | Type | Phase | Notes PS18ao | SN 2018Z | 2018-01-01.2 | 19.96 | 2018-01-09.9 | 0.102 | Ia | post-maximum? | (1) (1) Redshift was derived from the SN and host absorption features.

A Standardised Vocabulary for Identifying Benthic Biota and Substrata from Underwater Imagery: The CATAMI Classification Scheme

PubMed Central

Jordan, Alan; Rees, Tony; Gowlett-Holmes, Karen

2015-01-01

Imagery collected by still and video cameras is an increasingly important tool for minimal impact, repeatable observations in the marine environment. Data generated from imagery includes identification, annotation and quantification of biological subjects and environmental features within an image. To be long-lived and useful beyond their project-specific initial purpose, and to maximize their utility across studies and disciplines, marine imagery data should use a standardised vocabulary of defined terms. This would enable the compilation of regional, national and/or global data sets from multiple sources, contributing to broad-scale management studies and development of automated annotation algorithms. The classification scheme developed under the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI) project provides such a vocabulary. The CATAMI classification scheme introduces Australian-wide acknowledged, standardised terminology for annotating benthic substrates and biota in marine imagery. It combines coarse-level taxonomy and morphology, and is a flexible, hierarchical classification that bridges the gap between habitat/biotope characterisation and taxonomy, acknowledging limitations when describing biological taxa through imagery. It is fully described, documented, and maintained through curated online databases, and can be applied across benthic image collection methods, annotation platforms and scoring methods. Following release in 2013, the CATAMI classification scheme was taken up by a wide variety of users, including government, academia and industry. This rapid acceptance highlights the scheme’s utility and the potential to facilitate broad-scale multidisciplinary studies of marine ecosystems when applied globally. Here we present the CATAMI classification scheme, describe its conception and features, and discuss its utility and the opportunities as well as challenges arising from its use. PMID:26509918

Consensus classification of posterior cortical atrophy

PubMed Central

Crutch, Sebastian J.; Schott, Jonathan M.; Rabinovici, Gil D.; Murray, Melissa; Snowden, Julie S.; van der Flier, Wiesje M.; Dickerson, Bradford C.; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H.; Boeve, Bradley F.; Butler, Christopher; Cappa, Stefano F.; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R.; Hof, Patrick R.; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F.; Nestor, Peter J.; Onyike, Chiadi U.; Pelak, Victoria S.; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N.; Ryan, Natalie S.; Scheltens, Philip; Shakespeare, Timothy J.; González, Aida Suárez; Tang-Wai, David F.; Yong, Keir X. X.; Carrillo, Maria; Fox, Nick C.

2017-01-01

Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. PMID:28259709

Consensus classification of posterior cortical atrophy.

PubMed

Crutch, Sebastian J; Schott, Jonathan M; Rabinovici, Gil D; Murray, Melissa; Snowden, Julie S; van der Flier, Wiesje M; Dickerson, Bradford C; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H; Boeve, Bradley F; Butler, Christopher; Cappa, Stefano F; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R; Hof, Patrick R; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F; Nestor, Peter J; Onyike, Chiadi U; Pelak, Victoria S; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N; Ryan, Natalie S; Scheltens, Philip; Shakespeare, Timothy J; Suárez González, Aida; Tang-Wai, David F; Yong, Keir X X; Carrillo, Maria; Fox, Nick C

2017-08-01

A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Classifying clinical decision making: interpreting nursing intuition, heuristics and medical diagnosis.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.

Methods of classification for women undergoing induction of labour: a systematic review and novel classification system.

PubMed

Nippita, T A; Khambalia, A Z; Seeho, S K; Trevena, J A; Patterson, J A; Ford, J B; Morris, J M; Roberts, C L

2015-09-01

A lack of reproducible methods for classifying women having an induction of labour (IOL) has led to controversies regarding IOL and related maternal and perinatal health outcomes. To evaluate articles that classify IOL and to develop a novel IOL classification system. Electronic searches using CINAHL, EMBASE, WEB of KNOWLEDGE, and reference lists. Two reviewers independently assessed studies that classified women having an IOL. For the systematic review, data were extracted on study characteristics, quality, and results. Pre-specified criteria were used for evaluation. A multidisciplinary collaboration developed a new classification system using a clinically logical model and stakeholder feedback, demonstrating applicability in a population cohort of 909 702 maternities in New South Wales, Australia, over the period 2002-2011. All seven studies included in the systematic review categorised women according to the presence or absence of varying medical indications for IOL. Evaluation identified uncertainties or deficiencies across all studies, related to the criteria of total inclusivity, reproducibility, clinical utility, implementability, and data availability. A classification system of ten groups was developed based on parity, previous caesarean, gestational age, number, and presentation of the fetus. Nulliparous and parous women at full term were the largest groups (21.2 and 24.5%, respectively), and accounted for the highest proportion of all IOL (20.7 and 21.5%, respectively). Current methods of classifying women undertaking IOL based on medical indications are inadequate. We propose a classification system that has the attributes of simplicity and clarity, uses information that is readily and reliably collected, and enables the standard characterisation of populations of women having an IOL across and within jurisdictions. © 2015 Royal College of Obstetricians and Gynaecologists.

Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage.

PubMed

Kimura, Shinya; Sato, Toshihiko; Ikeda, Shunya; Noda, Mitsuhiko; Nakayama, Takeo

2010-01-01

Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the utility of these receipts. However, technical problems, including standardization of disease names and classifications, and anonymous linkage of individual receipts, must be addressed. In collaboration with health insurance societies, all information from receipts (inpatient, outpatient, and pharmacy) was collected. To standardize disease names and classifications, we developed a computer-aided post-entry standardization method using a disease name dictionary based on International Classification of Diseases (ICD)-10 classifications. We also developed an anonymous linkage system by using an encryption code generated from a combination of hash values and stream ciphers. Using different sets of the original data (data set 1: insurance certificate number, name, and sex; data set 2: insurance certificate number, date of birth, and relationship status), we compared the percentage of successful record matches obtained by using data set 1 to generate key codes with the percentage obtained when both data sets were used. The dictionary's automatic conversion of disease names successfully standardized 98.1% of approximately 2 million new receipts entered into the database. The percentage of anonymous matches was higher for the combined data sets (98.0%) than for data set 1 (88.5%). The use of standardized disease classifications and anonymous record linkage substantially contributed to the construction of a large, chronologically organized database of receipts. This database is expected to aid in epidemiologic and health services research using receipt information.

2016 Classification Criteria for Macrophage Activation Syndrome Complicating Systemic Juvenile Idiopathic Arthritis: A European League Against Rheumatism/American College of Rheumatology/Paediatric Rheumatology International Trials Organisation Collaborative Initiative.

PubMed

Ravelli, Angelo; Minoia, Francesca; Davì, Sergio; Horne, AnnaCarin; Bovis, Francesca; Pistorio, Angela; Aricò, Maurizio; Avcin, Tadej; Behrens, Edward M; De Benedetti, Fabrizio; Filipovic, Lisa; Grom, Alexei A; Henter, Jan-Inge; Ilowite, Norman T; Jordan, Michael B; Khubchandani, Raju; Kitoh, Toshiyuki; Lehmberg, Kai; Lovell, Daniel J; Miettunen, Paivi; Nichols, Kim E; Ozen, Seza; Pachlopnik Schmid, Jana; Ramanan, Athimalaipet V; Russo, Ricardo; Schneider, Rayfel; Sterba, Gary; Uziel, Yosef; Wallace, Carol; Wouters, Carine; Wulffraat, Nico; Demirkaya, Erkan; Brunner, Hermine I; Martini, Alberto; Ruperto, Nicolino; Cron, Randy Q

2016-03-01

To develop criteria for the classification of macrophage activation syndrome (MAS) in patients with systemic juvenile idiopathic arthritis (JIA). A multistep process, based on a combination of expert consensus and analysis of real patient data, was conducted. A panel of 28 experts was first asked to classify 428 patient profiles as having or not having MAS, based on clinical and laboratory features at the time of disease onset. The 428 profiles comprised 161 patients with systemic JIA-associated MAS and 267 patients with a condition that could potentially be confused with MAS (active systemic JIA without evidence of MAS, or systemic infection). Next, the ability of candidate criteria to classify individual patients as having MAS or not having MAS was assessed by evaluating the agreement between the classification yielded using the criteria and the consensus classification of the experts. The final criteria were selected in a consensus conference. Experts achieved consensus on the classification of 391 of the 428 patient profiles (91.4%). A total of 982 candidate criteria were tested statistically. The 37 best-performing criteria and 8 criteria obtained from the literature were evaluated at the consensus conference. During the conference, 82% consensus among experts was reached on the final MAS classification criteria. In validation analyses, these criteria had a sensitivity of 0.73 and a specificity of 0.99. Agreement between the classification (MAS or not MAS) obtained using the criteria and the original diagnosis made by the treating physician was high (κ=0.76). We have developed a set of classification criteria for MAS complicating systemic JIA and provided preliminary evidence of its validity. Use of these criteria will potentially improve understanding of MAS in systemic JIA and enhance efforts to discover effective therapies, by ensuring appropriate patient enrollment in studies. 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/

A European Humus Forms Reference Base

NASA Astrophysics Data System (ADS)

Zanella, A.; Englisch, M.; Ponge, J.-F.; Jabiol, B.; Sartori, G.; Gardi, C.

2012-04-01

From 2003 on, a panel of experts in humus and humus dynamics (Humus group) has been working about a standardisation and improvement of existing national humus classifications. Some important goals have been reached, in order to share data and experiences: a) definition of specific terms; b) description of 15 types of diagnostic horizons; c) of 10 basic humus forms references; d) subdivision of each main reference in 2-4 sub-unities; e) elaboration of a general European Humus Form Reference Base (http://hal-agroparistech.archives-ouvertes.fr/docs/00/56/17/95/PDF/Humus_Forms_ERB_31_01_2011.pdf); f) publication of the scientific significance of this base of classification as an article [A European morpho-functional classification of humus forms. Geoderma, 164 (3-4), 138-145]. The classification will be updated every 2 years and presently the Humus group is assessing biological (general: soil, vegetation, biome; specific: fungi, bacteria, pedofauna), physical (air temperature, rainfall) and chemical (pH, mineral elements, organic matter, quality and quantity of humic components…) factors which characterize basic humus forms and their varieties. The content of the new version of the classification is planned to be more "practical", like an ecological manual which lists associated humus forms and environmental data in the aim to contribute to a more precise environmental diagnosis of every analysed terrestrial and semiterrestrial European ecosystem. The Humus group is also involved in an endeavour to include humus forms in the World Reference Base for Soils (WRB-FAO) according to nomenclatural principles erected for soil profiles. Thirty basic references have been defined, complemented by a set of qualifiers (prefixes and suffixes), allowing to classify European humus forms and probably a large majority of humus forms known worldwide. The principles of the classification, the diagnostic horizons and humus forms main references are presented at the General Assembly of the European Geosciences Union with the aim to stimulate members' curiosity. Interested people are invited to test the classification system in various field areas and to collaborate with the Humus group. Critical observations and field data/impressions are welcome as every other suggestions which can help in elaborating the 2013 version of the European humus forms classification.

Incidence of Systemic Lupus Erythematosus in a Population Based Cohort using Revised 1997 American College of Rheumatology and the 2012 Systemic Lupus International Collaborating Clinic Classification Criteria

PubMed Central

Ungprasert, Patompong; Sagar, Vinay; Crowson, Cynthia S.; Amin, Shreyasee; Makol, Ashima; Ernste, Floranne C.; Osborn, Thomas G.; Moder, Kevin G.; Niewold, Timothy B.; Maradit-Kremers, Hilal; Ramsey-Goldman, Rosalind; Chowdhary, Vaidehi R.

2016-01-01

In 2012, the Systemic Lupus International Collaborating Clinic (SLICC) group published a new set of classification criteria for systemic lupus erythematosus (SLE). Studies applying these criteria to real life scenarios have found either equal or greater sensitivity and equal or lower specificity to the 1997 ACR classification criteria (ACR 97). Nonetheless, there are no studies that have used the SLICC 12 criteria to investigate the incidence of lupus. We utilized the resource of the Rochetser Epidemiology Project to identify incident cases of SLE in Olmsted County, Minnesota from 1993-2005 who fulfilled the ACR 97 or SLICC 12 criteria. A total of 58 patients met criteria by SLICC 12 and 44 patients met criteria by ACR 97. The adjusted incidence of 4.9 per 100,000 person-years by SLICC 12 was higher than that by ACR 97 (3.7 per 100,000 person-years, p=0.04). The median duration from the appearance of first criteria to fulfillment of the criteria was shorter for the SLICC 12 than for ACR 97 (3.9 months vs 8.1 months). The higher incidence by SLICC 12 criteria came primarily from the ability to classify patients with renal-limited disease, the expansion of the immunologic criteria and the expansion of neurologic criteria. PMID:27365370

Incidence of systemic lupus erythematosus in a population-based cohort using revised 1997 American College of Rheumatology and the 2012 Systemic Lupus International Collaborating Clinics classification criteria.

PubMed

Ungprasert, P; Sagar, V; Crowson, C S; Amin, S; Makol, A; Ernste, F C; Osborn, T G; Moder, K G; Niewold, T B; Maradit-Kremers, H; Ramsey-Goldman, R; Chowdhary, V R

2017-03-01

In 2012, the Systemic Lupus International Collaborating Clinics (SLICC) group published a new set of classification criteria for systemic lupus erythematosus (SLE). Studies applying these criteria to real-life scenarios have found either equal or greater sensitivity and equal or lower specificity to the 1997 ACR classification criteria (ACR 97). Nonetheless, there are no studies that have used the SLICC 12 criteria to investigate the incidence of lupus. We used the resource of the Rochester Epidemiology Project to identify incident SLE patients in Olmsted County, Minnesota, from 1993 to 2005, who fulfilled the ACR 97 or SLICC 12 criteria. A total of 58 patients met criteria by SLICC 12 and 44 patients met criteria by ACR 97. The adjusted incidence of 4.9 per 100,000 person-years by SLICC 12 was higher than that by ACR 97 (3.7 per 100,000 person-years, p = 0.04). The median duration from the appearance of first criterion to fulfillment of the criteria was shorter for the SLICC 12 than for ACR 97 (3.9 months vs 8.1 months). The higher incidence by SLICC 12 criteria came primarily from the ability to classify patients with renal-limited disease, the expansion of the immunologic criteria and the expansion of neurologic criteria.

Analysis of failure in patients with adenoid cystic carcinoma of the head and neck. An international collaborative study.

PubMed

Amit, Moran; Binenbaum, Yoav; Sharma, Kanika; Ramer, Naomi; Ramer, Ilana; Agbetoba, Abib; Miles, Brett; Yang, Xinjie; Lei, Delin; Bjøerndal, Kristine; Godballe, Christian; Mücke, Thomas; Wolff, Klaus-Dietrich; Fliss, Dan; Eckardt, André M; Copelli, Chiara; Sesenna, Enrico; Palmer, Frank; Patel, Snehal; Gil, Ziv

2014-07-01

Adenoid cystic carcinoma (ACC) is a locally aggressive tumor with a high prevalence of distant metastases. The purpose of this study was to identify independent predictors of outcome and to characterize the patterns of failure. An international retrospective review was conducted of 489 patients with ACC treated between 1985 and 2011 in 9 cancer centers worldwide. Five-year overall-survival (OS), disease-specific survival (DSS), and disease-free survival (DFS) were 76%, 80%, and 68%, respectively. Independent predictors of OS and DSS were: age, site, N classification, and presence of distant metastases. N classification, age, and bone invasion were associated with DFS on multivariate analysis. Age, tumor site, orbital invasion, and N classification were independent predictors of distant metastases. The clinical course of ACC is slow but persistent. Paranasal sinus origin is associated with the lowest distant metastases rate but with the poorest outcome. These prognostic estimates should be considered when tailoring treatment for patients with ACC. Copyright © 2013 Wiley Periodicals, Inc.

Networking Foundations for Collaborative Computing at Internet Scope

DTIC Science & Technology

2006-01-01

network-supported synchronous multime- dia groupwork at Internet scope and for large user groups. Contributions entail an novel classification for...multimedia resources in interactive groupwork , generalized to the domain of CSCW from the “right to speak” [26]. A floor control protocol mediates access to

Beyond Information Retrieval: Ways To Provide Content in Context.

ERIC Educational Resources Information Center

Wiley, Deborah Lynne

1998-01-01

Provides an overview of information retrieval from mainframe systems to Web search engines; discusses collaborative filtering, data extraction, data visualization, agent technology, pattern recognition, classification and clustering, and virtual communities. Argues that rather than huge data-storage centers and proprietary software, we need…

Real-time Automatic Search for Multi-wavelength Counterparts of DWF Transients

NASA Astrophysics Data System (ADS)

Murphy, Christopher; Cucchiara, Antonino; Andreoni, Igor; Cooke, Jeff; Hegarty, Sarah

2018-01-01

The Deeper Wider Faster (DWF) survey aims to find and classify the fastest transients in the Universe. DWF utilizes the Dark Energy Camera (DECam), collecting a continuous sequence of 20s images over a 3 square degree field of view.Once an interesting transient is detected during DWF observations, the DWF collaboration has access to several facilities for rapid follow-up in multiple wavelengths (from gamma to radio).An online web tool has been designed to help with real-time visual classification of possible astrophysical transients in data collected by the DWF observing program. The goal of this project is to create a python-based code to improve the classification process by querying several existing archive databases. Given the DWF transient location and search radius, the developed code will extract a list of possible counterparts and all available information (e.g. magnitude, radio fluxes, distance separation).Thanks to this tool, the human classifier can make a quicker decision in order to trigger the collaboration rapid-response resources.

Structural action recognition in body sensor networks: distributed classification based on string matching.

PubMed

Ghasemzadeh, Hassan; Loseu, Vitali; Jafari, Roozbeh

2010-03-01

Mobile sensor-based systems are emerging as promising platforms for healthcare monitoring. An important goal of these systems is to extract physiological information about the subject wearing the network. Such information can be used for life logging, quality of life measures, fall detection, extraction of contextual information, and many other applications. Data collected by these sensor nodes are overwhelming, and hence, an efficient data processing technique is essential. In this paper, we present a system using inexpensive, off-the-shelf inertial sensor nodes that constructs motion transcripts from biomedical signals and identifies movements by taking collaboration between the nodes into consideration. Transcripts are built of motion primitives and aim to reduce the complexity of the original data. We then label each primitive with a unique symbol and generate a sequence of symbols, known as motion template, representing a particular action. This model leads to a distributed algorithm for action recognition using edit distance with respect to motion templates. The algorithm reduces the number of active nodes during every classification decision. We present our results using data collected from five normal subjects performing transitional movements. The results clearly illustrate the effectiveness of our framework. In particular, we obtain a classification accuracy of 84.13% with only one sensor node involved in the classification process.

Design of Cancelable Palmprint Templates Based on Look Up Table

NASA Astrophysics Data System (ADS)

Qiu, Jian; Li, Hengjian; Dong, Jiwen

2018-03-01

A novel cancelable palmprint templates generation scheme is proposed in this paper. Firstly, the Gabor filter and chaotic matrix are used to extract palmprint features. It is then arranged into a row vector and divided into equal size blocks. These blocks are converted to corresponding decimals and mapped to look up tables, forming final cancelable palmprint features based on the selected check bits. Finally, collaborative representation based classification with regularized least square is used for classification. Experimental results on the Hong Kong PolyU Palmprint Database verify that the proposed cancelable templates can achieve very high performance and security levels. Meanwhile, it can also satisfy the needs of real-time applications.

Geomorphic classification of rivers

Treesearch

J. M. Buffington; D. R. Montgomery

2013-01-01

Over the last several decades, environmental legislation and a growing awareness of historical human disturbance to rivers worldwide (Schumm, 1977; Collins et al., 2003; Surian and Rinaldi, 2003; Nilsson et al., 2005; Chin, 2006; Walter and Merritts, 2008) have fostered unprecedented collaboration among scientists, land managers, and stakeholders to better understand,...

Collaborative Supervised Learning for Sensor Networks

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Rebbapragada, Umaa; Lane, Terran

2011-01-01

Collaboration methods for distributed machine-learning algorithms involve the specification of communication protocols for the learners, which can query other learners and/or broadcast their findings preemptively. Each learner incorporates information from its neighbors into its own training set, and they are thereby able to bootstrap each other to higher performance. Each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. After being seeded with an initial labeled training set, each learner proceeds to learn in an iterative fashion. New data is collected and classified. The learner can then either broadcast its most confident classifications for use by other learners, or can query neighbors for their classifications of its least confident items. As such, collaborative learning combines elements of both passive (broadcast) and active (query) learning. It also uses ideas from ensemble learning to combine the multiple responses to a given query into a single useful label. This approach has been evaluated against current non-collaborative alternatives, including training a single classifier and deploying it at all nodes with no further learning possible, and permitting learners to learn from their own most confident judgments, absent interaction with their neighbors. On several data sets, it has been consistently found that active collaboration is the best strategy for a distributed learner network. The main advantages include the ability for learning to take place autonomously by collaboration rather than by requiring intervention from an oracle (usually human), and also the ability to learn in a distributed environment, permitting decisions to be made in situ and to yield faster response time.

Electron Microscopy of Intracellular Protozoa.

DTIC Science & Technology

1982-08-01

8217 COMMiM M revee u0d& N n8e1eep1 didentify by block ntmnber) Summary * During this fiscal year, in collaboration with Col. Hendricks and his ft...CLASSIFICATION OF THIS PAGEfWPen Dats EntIer.d) -% %.. SSummary During this fiscal year, in collaboration with Col. Hendricks and his associates we...Larry D. Hendricks , PhD2 , Yoshihiro Ito, PhD 1 , and Martin Jagusiak 2 C Institute of Pathology, Case Western Reserve University, Cleveland,Ohio 441061

Performance of the 2012 Systemic Lupus International Collaborating Clinics classification criteria versus the 1997 American College of Rheumatology classification criteria in adult and juvenile systemic lupus erythematosus. A systematic review and meta-analysis.

PubMed

Hartman, Esther A R; van Royen-Kerkhof, Annet; Jacobs, Johannes W G; Welsing, Paco M J; Fritsch-Stork, Ruth D E

2018-03-01

To evaluate the performance in classifying systemic lupus erythematosus by the 2012 Systemic Lupus International Collaborating Clinics criteria (SLICC'12), versus the revised American College of Rheumatology criteria from 1997 (ACR'97) in adult and juvenile SLE patients. A systematic literature search was conducted in PubMed and Embase for studies comparing SLICC'12 and ACR'97 with clinical diagnosis. A meta-analysis was performed to estimate the sensitivity and specificity of SLICC'12 and ACR'97. To assess classification earlier in the disease by either set, sensitivity and specificity were compared for patients with disease duration <5years. Sensitivity and specificity of individual criteria items were also assessed. In adult SLE (nine studies: 5236 patients, 1313 controls), SLICC'12 has higher sensitivity (94.6% vs. 89.6%) and similar specificity (95.5% vs. 98.1%) compared to ACR'97. For juvenile SLE (four studies: 568 patients, 339 controls), SLICC'12 demonstrates higher sensitivity (99.9% vs. 84.3%) than ACR'97, but much lower specificity (82.0% vs. 94.1%). SLICC'12 classifies juvenile SLE patients earlier in disease course. Individual items contributing to diagnostic accuracy are low complement, anti-ds DNA and acute cutaneous lupus in SLICC'12, and the immunologic and hematologic disorder in ACR'97. Based on sensitivity and specificity SLICC'12 is best for adult SLE. Following the view that higher specificity, i.e. avoidance of false positives, is preferable, ACR'97 is best for juvenile SLE even if associated with lower sensitivity. Our results on the contribution of the individual items of SLICC'12 and ACR´97 may be of value in future efforts to update classification criteria. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Harmful algal bloom smart device application: using image analysis and machine learning techniques for early classification of harmful algal blooms

EPA Science Inventory

The Ecological Stewardship Institute at Northern Kentucky University and the U.S. Environmental Protection Agency are collaborating to optimize a harmful algal bloom detection algorithm that estimates the presence and count of cyanobacteria in freshwater systems by image analysis...

A Comparison of Revised Bloom and Marzano's New Taxonomy of Learning

ERIC Educational Resources Information Center

Irvine, Jeff

2017-01-01

The seminal "Taxonomy of Educational Objectives: The Classification of Educational Goals--Handbook I, Cognitive Domain" (Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956) represented years of collaboration by the Committee of College and University Examiners, and was the first of three volumes that together would become known as…

A Classification Scheme for Therapeutic Recreation Research Grounded in the Rehabilitative Sciences.

ERIC Educational Resources Information Center

Shank, J. W.; And Others

1996-01-01

Presents therapeutic recreation (TR) research according to a model from the National Center for Medical Rehabilitation Research to guide research on disability, rehabilitation, and quality of life for persons with disabilities. Suggests that disseminating TR research can stimulate interdisciplinary collaboration and support inclusion of TR…

The International Neuroblastoma Risk Group (INRG) Classification System: An INRG Task Force Report

PubMed Central

Cohn, Susan L.; Pearson, Andrew D.J.; London, Wendy B.; Monclair, Tom; Ambros, Peter F.; Brodeur, Garrett M.; Faldum, Andreas; Hero, Barbara; Iehara, Tomoko; Machin, David; Mosseri, Veronique; Simon, Thorsten; Garaventa, Alberto; Castel, Victoria; Matthay, Katherine K.

2009-01-01

Purpose Because current approaches to risk classification and treatment stratification for children with neuroblastoma (NB) vary greatly throughout the world, it is difficult to directly compare risk-based clinical trials. The International Neuroblastoma Risk Group (INRG) classification system was developed to establish a consensus approach for pretreatment risk stratification. Patients and Methods The statistical and clinical significance of 13 potential prognostic factors were analyzed in a cohort of 8,800 children diagnosed with NB between 1990 and 2002 from North America and Australia (Children's Oncology Group), Europe (International Society of Pediatric Oncology Europe Neuroblastoma Group and German Pediatric Oncology and Hematology Group), and Japan. Survival tree regression analyses using event-free survival (EFS) as the primary end point were performed to test the prognostic significance of the 13 factors. Results Stage, age, histologic category, grade of tumor differentiation, the status of the MYCN oncogene, chromosome 11q status, and DNA ploidy were the most highly statistically significant and clinically relevant factors. A new staging system (INRG Staging System) based on clinical criteria and tumor imaging was developed for the INRG Classification System. The optimal age cutoff was determined to be between 15 and 19 months, and 18 months was selected for the classification system. Sixteen pretreatment groups were defined on the basis of clinical criteria and statistically significantly different EFS of the cohort stratified by the INRG criteria. Patients with 5-year EFS more than 85%, more than 75% to ≤ 85%, ≥ 50% to ≤ 75%, or less than 50% were classified as very low risk, low risk, intermediate risk, or high risk, respectively. Conclusion By defining homogenous pretreatment patient cohorts, the INRG classification system will greatly facilitate the comparison of risk-based clinical trials conducted in different regions of the world and the development of international collaborative studies. PMID:19047291

Implementation of standardized nomenclature in the electronic medical record.

PubMed

Klehr, Joan; Hafner, Jennifer; Spelz, Leah Mylrea; Steen, Sara; Weaver, Kathy

2009-01-01

To describe a customized electronic medical record documentation system which provides an electronic health record, Epic, which was implemented in December 2006 using standardized taxonomies for nursing documentation. Descriptive data is provided regarding the development, implementation, and evaluation processes for the electronic medical record system. Nurses used standardized nursing nomenclature including NANDA-I diagnoses, Nursing Interventions Classification, and Nursing Outcomes Classification in a measurable and user-friendly format using the care plan activity. Key factors in the success of the project included close collaboration among staff nurses and information technology staff, ongoing support and encouragement from the vice president/chief nursing officer, the ready availability of expert resources, and nursing ownership of the project. Use of this evidence-based documentation enhanced institutional leadership in clinical documentation.

Molecular classification of gastric adenocarcinoma: translating new insights from the cancer genome atlas research network.

PubMed

Sunakawa, Yu; Lenz, Heinz-Josef

2015-04-01

Gastric cancer is a heterogenous cancer, which may be classified into several distinct subtypes based on pathology and epidemiology, each with different initiating pathological processes and each possibly having different tumor biology. A classification of gastric cancer should be important to select patients who can benefit from the targeted therapies or to precisely predict prognosis. The Cancer Genome Atlas (TCGA) study collaborated with previous reports regarding subtyping gastric cancer but also proposed a refined classification based on molecular characteristics. The addition of the new molecular classification strategy to a current classical subtyping may be a promising option, particularly stratification by Epstein-Barr virus (EBV) and microsatellite instability (MSI) statuses. According to TCGA study, EBV gastric cancer patients may benefit the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) antibodies or phosphoinositide 3-kinase (PI3K) inhibitors which are now being developed. The discoveries of predictive biomarkers should improve patient care and individualized medicine in the management since the targeted therapies may have the potential to change the landscape of gastric cancer treatment, moreover leading to both better understanding of the heterogeneity and better outcomes. Patient enrichment by predictive biomarkers for new treatment strategies will be critical to improve clinical outcomes. Additionally, liquid biopsies will be able to enable us to monitor in real-time molecular escape mechanism, resulting in better treatment strategies.

Issues of diagnostic review in brain tumor studies: from the Brain Tumor Epidemiology Consortium.

PubMed

Davis, Faith G; Malmer, Beatrice S; Aldape, Ken; Barnholtz-Sloan, Jill S; Bondy, Melissa L; Brännström, Thomas; Bruner, Janet M; Burger, Peter C; Collins, V Peter; Inskip, Peter D; Kruchko, Carol; McCarthy, Bridget J; McLendon, Roger E; Sadetzki, Siegal; Tihan, Tarik; Wrensch, Margaret R; Buffler, Patricia A

2008-03-01

Epidemiologists routinely conduct centralized single pathology reviews to minimize interobserver diagnostic variability, but this practice does not facilitate the combination of studies across geographic regions and institutions where diagnostic practices differ. A meeting of neuropathologists and epidemiologists focused on brain tumor classification issues in the context of protocol needs for consortial studies (http://epi.grants.cancer.gov/btec/). It resulted in recommendations relevant to brain tumors and possibly other rare disease studies. Two categories of brain tumors have enough general agreement over time, across regions, and between individual pathologists that one can consider using existing diagnostic data without further review: glioblastomas and meningiomas (as long as uniform guidelines such as those provided by the WHO are used). Prospective studies of these tumors benefit from collection of pathology reports, at a minimum recording the pathology department and classification system used in the diagnosis. Other brain tumors, such as oligodendroglioma, are less distinct and require careful histopathologic review for consistent classification across study centers. Epidemiologic study protocols must consider the study specific aims, diagnostic changes that have taken place over time, and other issues unique to the type(s) of tumor being studied. As diagnostic changes are being made rapidly, there are no readily available answers on disease classification issues. It is essential that epidemiologists and neuropathologists collaborate to develop appropriate study designs and protocols for specific hypothesis and populations.

European consensus meeting of ARM-Net members concerning diagnosis and early management of newborns with anorectal malformations.

PubMed

van der Steeg, H J J; Schmiedeke, E; Bagolan, P; Broens, P; Demirogullari, B; Garcia-Vazquez, A; Grasshoff-Derr, S; Lacher, M; Leva, E; Makedonsky, I; Sloots, C E J; Schwarzer, N; Aminoff, D; Schipper, M; Jenetzky, E; van Rooij, I A L M; Giuliani, S; Crétolle, C; Holland Cunz, S; Midrio, P; de Blaauw, I

2015-03-01

The ARM-Net (anorectal malformation network) consortium held a consensus meeting in which the classification of ARM and preoperative workup were evaluated with the aim of improving monitoring of treatment and outcome. The Krickenbeck classification of ARM and preoperative workup suggested by Levitt and Peña, used as a template, were discussed, and a collaborative consensus was achieved. The Krickenbeck classification is appropriate in describing ARM for clinical use. The preoperative workup was slightly modified. In males with a visible fistula, no cross-table lateral X-ray is needed and an anoplasty or (mini-) posterior sagittal anorectoplasty can directly be performed. In females with a small vestibular fistula (Hegar size <5 mm), a primary repair or colostomy is recommended; the repair may be delayed if the fistula admits a Hegar size >5 mm, and in the meantime, gentle painless dilatations can be performed. In both male and female perineal fistula and either a low birth weight (<2,000 g) or severe associated congenital anomalies, prolonged preoperative painless dilatations might be indicated to decrease perioperative morbidity caused by general anesthesia. The Krickenbeck classification is appropriate in describing ARM for clinical use. Some minor modifications to the preoperative workup by Levitt and Peña have been introduced in order to refine terminology and establish a comprehensive preoperative workup.

The DSM-5: Classification and criteria changes.

PubMed

Regier, Darrel A; Kuhl, Emily A; Kupfer, David J

2013-06-01

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) marks the first significant revision of the publication since the DSM-IV in 1994. Changes to the DSM were largely informed by advancements in neuroscience, clinical and public health need, and identified problems with the classification system and criteria put forth in the DSM-IV. Much of the decision-making was also driven by a desire to ensure better alignment with the International Classification of Diseases and its upcoming 11th edition (ICD-11). In this paper, we describe select revisions in the DSM-5, with an emphasis on changes projected to have the greatest clinical impact and those that demonstrate efforts to enhance international compatibility, including integration of cultural context with diagnostic criteria and changes that facilitate DSM-ICD harmonization. It is anticipated that this collaborative spirit between the American Psychiatric Association (APA) and the World Health Organization (WHO) will continue as the DSM-5 is updated further, bringing the field of psychiatry even closer to a singular, cohesive nosology. Copyright © 2013 World Psychiatric Association.

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.

Broad and Inconsistent Muscle Food Classification Is Problematic for Dietary Guidance in the U.S.

PubMed Central

O’Connor, Lauren E.; Campbell, Wayne W.; Woerner, Dale R.; Belk, Keith E.

2017-01-01

Dietary recommendations regarding consumption of muscle foods, such as red meat, processed meat, poultry or fish, largely rely on current dietary intake assessment methods. This narrative review summarizes how U.S. intake values for various types of muscle foods are grouped and estimated via methods that include: (1) food frequency questionnaires; (2) food disappearance data from the U.S. Department of Agriculture Economic Research Service; and (3) dietary recall information from the National Health and Nutrition Examination Survey data. These reported methods inconsistently classify muscle foods into groups, such as those previously listed, which creates discrepancies in estimated intakes. Researchers who classify muscle foods into these groups do not consistently considered nutrient content, in turn leading to implications of scientific conclusions and dietary recommendations. Consequentially, these factors demonstrate a need for a more universal muscle food classification system. Further specification to this system would improve accuracy and precision in which researchers can classify muscle foods in nutrition research. Future multidisciplinary collaboration is needed to develop a new classification system via systematic review protocol of current literature. PMID:28926963

Structure and needs of global loss databases about natural disaster

NASA Astrophysics Data System (ADS)

Steuer, Markus

2010-05-01

Global loss databases are used for trend analyses and statistics in scientific projects, studies for governmental and nongovernmental organizations and for the insurance and finance industry as well. At the moment three global data sets are established: EM-DAT (CRED), Sigma (Swiss Re) and NatCatSERVICE (Munich Re). Together with the Asian Disaster Reduction Center (ADRC) and United Nations Development Program (UNDP) started a collaborative initiative in 2007 with the aim to agreed on and implemented a common "Disaster Category Classification and Peril Terminology for Operational Databases". This common classification has been established through several technical meetings and working groups and represents a first and important step in the development of a standardized international classification of disasters and terminology of perils. This means concrete to set up a common hierarchy and terminology for all global and regional databases on natural disasters and establish a common and agreed definition of disaster groups, main types and sub-types of events. Also the theme of georeferencing, temporal aspects, methodology and sourcing were other issues that have been identified and will be discussed. The implementation of the new and defined structure for global loss databases is already set up for Munich Re NatCatSERVICE. In the following oral session we will show the structure of the global databases as defined and in addition to give more transparency of the data sets behind published statistics and analyses. The special focus will be on the catastrophe classification from a moderate loss event up to a great natural catastrophe, also to show the quality of sources and give inside information about the assessment of overall and insured losses. Keywords: disaster category classification, peril terminology, overall and insured losses, definition

Harmful algal bloom smart device application: using image analysis and machine learning techniques for classification of harmful algal blooms

EPA Science Inventory

Northern Kentucky University and the U.S. EPA Office of Research Development in Cincinnati Agency are collaborating to develop a harmful algal bloom detection algorithm that estimates the presence of cyanobacteria in freshwater systems by image analysis. Green and blue-green alg...

Required Collaborative Work in Online Courses: A Predictive Modeling Approach

ERIC Educational Resources Information Center

Smith, Marlene A.; Kellogg, Deborah L.

2015-01-01

This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

The Quest for High-Level Knowledge in Schools: Revisiting the Concepts of Classification and Framing

ERIC Educational Resources Information Center

Morais, Ana M.; Neves, Isabel P.

2018-01-01

This article centres on the problem of raising the level of school knowledge, particularly science knowledge, for all. The article describes studies in science education developed in Portugal by Morais and Neves and collaborators. These studies are mainly based on Bernstein's model of pedagogic discourse (PD), and on his theorisation on knowledge…

Efficient sensor network vehicle classification using peak harmonics of acoustic emissions

NASA Astrophysics Data System (ADS)

William, Peter E.; Hoffman, Michael W.

2008-04-01

An application is proposed for detection and classification of battlefield ground vehicles using the emitted acoustic signal captured at individual sensor nodes of an ad hoc Wireless Sensor Network (WSN). We make use of the harmonic characteristics of the acoustic emissions of battlefield vehicles, in reducing both the computations carried on the sensor node and the transmitted data to the fusion center for reliable and effcient classification of targets. Previous approaches focus on the lower frequency band of the acoustic emissions up to 500Hz; however, we show in the proposed application how effcient discrimination between battlefield vehicles is performed using features extracted from higher frequency bands (50 - 1500Hz). The application shows that selective time domain acoustic features surpass equivalent spectral features. Collaborative signal processing is utilized, such that estimation of certain signal model parameters is carried by the sensor node, in order to reduce the communication between the sensor node and the fusion center, while the remaining model parameters are estimated at the fusion center. The transmitted data from the sensor node to the fusion center ranges from 1 ~ 5% of the sampled acoustic signal at the node. A variety of classification schemes were examined, such as maximum likelihood, vector quantization and artificial neural networks. Evaluation of the proposed application, through processing of an acoustic data set with comparison to previous results, shows that the improvement is not only in the number of computations but also in the detection and false alarm rate as well.

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

In this dissertation, feature extraction algorithms have been developed for extraction of characteristic features from harmonic signals. The common theme for all developed algorithms is the simplicity in generating a significant set of features directly from the time domain harmonic signal. The features are a time domain representation of the composite, yet sparse, harmonic signature in the spectral domain. The algorithms are adequate for low-power unattended sensors which perform sensing, feature extraction, and classification in a standalone scenario. The first algorithm generates the characteristic features using only the duration between successive zero-crossing intervals. The second algorithm estimates the harmonics' amplitudes of the harmonic structure employing a simplified least squares method without the need to estimate the true harmonic parameters of the source signal. The third algorithm, resulting from a collaborative effort with Daniel White at the DSP Lab, University of Nebraska-Lincoln, presents an analog front end approach that utilizes a multichannel analog projection and integration to extract the sparse spectral features from the analog time domain signal. Classification is performed using a multilayer feedforward neural network. Evaluation of the proposed feature extraction algorithms for classification through the processing of several acoustic and vibration data sets (including military vehicles and rotating electric machines) with comparison to spectral features shows that, for harmonic signals, time domain features are simpler to extract and provide equivalent or improved reliability over the spectral features in both the detection probabilities and false alarm rate.

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Classification guides. 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

14 CFR 1203.412 - Classification guides.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Classification guides. 1203.412 Section 1203... Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification authorities...

14 CFR § 1203.412 - Classification guides.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Classification guides. § 1203.412 Section... PROGRAM Guides for Original Classification § 1203.412 Classification guides. (a) General. A classification guide, based upon classification determinations made by appropriate program and classification...

Recognition of skin melanoma through dermoscopic image analysis

NASA Astrophysics Data System (ADS)

Gómez, Catalina; Herrera, Diana Sofia

2017-11-01

Melanoma skin cancer diagnosis can be challenging due to the similarities of the early stage symptoms with regular moles. Standardized visual parameters can be determined and characterized to suspect a melanoma cancer type. The automation of this diagnosis could have an impact in the medical field by providing a tool to support the specialists with high accuracy. The objective of this study is to develop an algorithm trained to distinguish a highly probable melanoma from a non-dangerous mole by the segmentation and classification of dermoscopic mole images. We evaluate our approach on the dataset provided by the International Skin Imaging Collaboration used in the International Challenge Skin Lesion Analysis Towards Melanoma Detection. For the segmentation task, we apply a preprocessing algorithm and use Otsu's thresholding in the best performing color space; the average Jaccard Index in the test dataset is 70.05%. For the subsequent classification stage, we use joint histograms in the YCbCr color space, a RBF Gaussian SVM trained with five features concerning circularity and irregularity of the segmented lesion, and the Gray Level Co-occurrence matrix features for texture analysis. These features are combined to obtain an Average Classification Accuracy of 63.3% in the test dataset.

The Prokaryote-Eukaryote Dichotomy: Meanings and Mythology

PubMed Central

Sapp, Jan

2005-01-01

Drawing on documents both published and archival, this paper explains how the prokaryote-eukaryote dichotomy of the 1960s was constructed, the purposes it served, and what it implied in terms of classification and phylogeny. In doing so, I first show how the concept was attributed to Edouard Chatton and the context in which he introduced the terms. Following, I examine the context in which the terms were reintroduced into biology in 1962 by Roger Stanier and C. B. van Niel. I study the discourse over the subsequent decade to understand how the organizational dichotomy took on the form of a natural classification as the kingdom Monera or superkingdom Procaryotae. Stanier and van Niel admitted that, in regard to constructing a natural classification of bacteria, structural characteristics were no more useful than physiological properties. They repeatedly denied that bacterial phylogenetics was possible. I thus examine the great historical irony that the “prokaryote,” in both its organizational and phylogenetic senses, was defined (negatively) on the basis of structure. Finally, we see how phylogenetic research based on 16S rRNA led by Carl Woese and his collaborators confronted the prokaryote concept while moving microbiology to the center of evolutionary biology. PMID:15944457

A Classification Methodology and Retrieval Model to Support Software Reuse

DTIC Science & Technology

1988-01-01

Dewey Decimal Classification ( DDC 18), an enumerative scheme, occupies 40 pages [Buchanan 19791. Langridge [19731 states that the facets listed in the...sense of historical importance or wide spread use. The schemes are: Dewey Decimal Classification ( DDC ), Universal Decimal Classification (UDC...Classification Systems ..... ..... 2.3.3 Library Classification__- .52 23.3.1 Dewey Decimal Classification -53 2.33.2 Universal Decimal Classification 55 2333

A Collaborative Brain-Computer Interface for Improving Human Performance

PubMed Central

Wang, Yijun; Jung, Tzyy-Ping

2011-01-01

Electroencephalogram (EEG) based brain-computer interfaces (BCI) have been studied since the 1970s. Currently, the main focus of BCI research lies on the clinical use, which aims to provide a new communication channel to patients with motor disabilities to improve their quality of life. However, the BCI technology can also be used to improve human performance for normal healthy users. Although this application has been proposed for a long time, little progress has been made in real-world practices due to technical limits of EEG. To overcome the bottleneck of low single-user BCI performance, this study proposes a collaborative paradigm to improve overall BCI performance by integrating information from multiple users. To test the feasibility of a collaborative BCI, this study quantitatively compares the classification accuracies of collaborative and single-user BCI applied to the EEG data collected from 20 subjects in a movement-planning experiment. This study also explores three different methods for fusing and analyzing EEG data from multiple subjects: (1) Event-related potentials (ERP) averaging, (2) Feature concatenating, and (3) Voting. In a demonstration system using the Voting method, the classification accuracy of predicting movement directions (reaching left vs. reaching right) was enhanced substantially from 66% to 80%, 88%, 93%, and 95% as the numbers of subjects increased from 1 to 5, 10, 15, and 20, respectively. Furthermore, the decision of reaching direction could be made around 100–250 ms earlier than the subject's actual motor response by decoding the ERP activities arising mainly from the posterior parietal cortex (PPC), which are related to the processing of visuomotor transmission. Taken together, these results suggest that a collaborative BCI can effectively fuse brain activities of a group of people to improve the overall performance of natural human behavior. PMID:21655253

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at participating nodes. Therefore, the feature-extraction method based on the Haar DWT is presented that employs a maximum-entropy measure to determine significant wavelet coefficients. Features are formed by calculating the energy of coefficients grouped around the competing clusters. A DWT-based feature extraction algorithm used for vehicle classification in WSNs can be enhanced by an added rule for selecting the optimal number of resolution levels to improve the correct classification rate and reduce energy consumption expended in local algorithm computations. Published field trial data for vehicular ground targets, measured with multiple sensor types, are used to evaluate the wavelet-assisted algorithms. Extracted features are used in established target recognition routines, e.g., the Bayesian minimum-error-rate classifier, to compare the effects on the classification performance of the wavelet compression. Simulations of feature sets and recognition routines at different resolution levels in target scenarios indicate the impact on classification rates, while formulas are provided to estimate reduction in resource use due to distributed compression.

Exploiting the Use of Social Networking to Facilitate Collaboration in the Scientific Community

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

Coppock, Edrick G.

The goal of this project was to exploit social networking to facilitate scientific collaboration. The project objective was to research and identify scientific collaboration styles that are best served by social networking applications and to model the most effective social networking applications to substantiate how social networking can support scientific collaboration. To achieve this goal and objective, the project was to develop an understanding of the types of collaborations conducted by scientific researchers, through classification, data analysis and identification of unique collaboration requirements. Another technical objective in support of this goal was to understand the current state of technology inmore » collaboration tools. In order to test hypotheses about which social networking applications effectively support scientific collaboration the project was to create a prototype scientific collaboration system. The ultimate goal for testing the hypotheses and research of the project was to refine the prototype into a functional application that could effectively facilitate and grow collaboration within the U.S. Department of Energy (DOE) research community.« less

47 CFR 64.2305 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... businesses. (c) Primary advertising classification. A primary advertising classification is the principal... advertising classification is the classification of a subscriber to telephone exchange service as a business...' telephone numbers, addresses, or primary advertising classifications (as such classifications are assigned...

47 CFR 64.2305 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... businesses. (c) Primary advertising classification. A primary advertising classification is the principal... advertising classification is the classification of a subscriber to telephone exchange service as a business...' telephone numbers, addresses, or primary advertising classifications (as such classifications are assigned...

Development of seed zones for the Eastern United States: Request for input and collaboration!

Treesearch

Carrie C. Pike; George Hernandez; Barbara Crane; Paul Berrang

2017-01-01

Artificial regeneration is necessary for meeting a variety of management objectives following timber harvests and other disturbances. While foresters use ecological classification to identify the most appropriate species to plant on a particular site, they generally use seed zones to identify the most suitable seed source of that species to plant. Seed zones have been...

Force Protection via UGV-UAV Collaboration: Development of Control Law for Vision Based Target Tracking on SUAV

DTIC Science & Technology

2007-12-01

Hardware - In - Loop , Piccolo, UAV, Unmanned Aerial Vehicle 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...Maneuvering Target.......................... 35 C. HARDWARE - IN - LOOP SIMULATION............................................... 37 1. Hardware - In - Loop Setup...law as proposed in equation (23) is capable of tracking a maneuvering target. C. HARDWARE - IN - LOOP SIMULATION The intention of HIL simulation

Collaboration between specialties for respiratory allergies in the International Classification of Diseases (ICD)-11.

PubMed

Tanno, Luciana Kase; Calderon, Moises; Linzer, Jeffrey F; Chalmers, Robert J G; Demoly, Pascal

2017-02-10

The International Classification of Diseases (ICD) has been grouping the allergic and hypersensitivity disorders involving the respiratory tract under topographic distribution, regardless of the underlying mechanisms, triggers or concepts currently in use for allergic and hypersensitivity conditions. In order to strengthen awareness and deliberate the creation of the new "Allergic or hypersensitivity disorders involving the respiratory tract" section of the ICD-11, we here propose make the building process public. The new frame has been constructed to cover the gaps previously identified and was based on consensus academic reports and ICD-11 principles. Constant and bilateral discussion was kept with relevant groups representing specialties and resulted in proposals submission into the ICD-11 online platform. The "Allergic or hypersensitivity disorders involving the respiratory tract" section covers 64 entities distributed across five main categories. All the 79 proposals submitted resulted from an intensive collaboration of the Allergy working group, relevant Expert working groups and the WHO ICD governance. The establishment of the ICD-11 "Allergic or hypersensitivity disorders involving the respiratory tract" section will allow the dissemination of the updated concepts to be used in clinical practice by many different specialties and health professionals.

LSST Astroinformatics And Astrostatistics: Data-oriented Astronomical Research

NASA Astrophysics Data System (ADS)

Borne, Kirk D.; Stassun, K.; Brunner, R. J.; Djorgovski, S. G.; Graham, M.; Hakkila, J.; Mahabal, A.; Paegert, M.; Pesenson, M.; Ptak, A.; Scargle, J.; Informatics, LSST; Statistics Team

2011-01-01

The LSST Informatics and Statistics Science Collaboration (ISSC) focuses on research and scientific discovery challenges posed by the very large and complex data collection that LSST will generate. Application areas include astroinformatics, machine learning, data mining, astrostatistics, visualization, scientific data semantics, time series analysis, and advanced signal processing. Research problems to be addressed with these methodologies include transient event characterization and classification, rare class discovery, correlation mining, outlier/anomaly/surprise detection, improved estimators (e.g., for photometric redshift or early onset supernova classification), exploration of highly dimensional (multivariate) data catalogs, and more. We present sample science results from these data-oriented approaches to large-data astronomical research. We present results from LSST ISSC team members, including the EB (Eclipsing Binary) Factory, the environmental variations in the fundamental plane of elliptical galaxies, and outlier detection in multivariate catalogs.

Clinical staging: its importance in therapeutic decisions and clinical trials.

PubMed

Denis, L J

1992-02-01

International collaboration has resulted in a revised and unified 1987 formulation for the TNM classification in solid tumors. The simplification and eliminations of most variables caused difficulties for the clinical use of the system in some tumors such as bladder cancer. The approval of the proposed adaptation covering the tumor mass, subdividing the T4 category and adapting the stage grouping, resolves these difficulties. Published reports demonstrate support for the TNM system as a clinical base for treatment decisions and prognosis. The TNMG stage and grade are important basic prognostic factors, but other prognostic factors, especially biologic tumor activity, are under clinical investigation. The TNM classification is the initial evaluation after histologic confirmation of cancer to guide treatment and prognosis. The quality of the evaluation is enhanced by precise communication on the employed methodology.

Transfer Learning beyond Text Classification

NASA Astrophysics Data System (ADS)

Yang, Qiang

Transfer learning is a new machine learning and data mining framework that allows the training and test data to come from different distributions or feature spaces. We can find many novel applications of machine learning and data mining where transfer learning is necessary. While much has been done in transfer learning in text classification and reinforcement learning, there has been a lack of documented success stories of novel applications of transfer learning in other areas. In this invited article, I will argue that transfer learning is in fact quite ubiquitous in many real world applications. In this article, I will illustrate this point through an overview of a broad spectrum of applications of transfer learning that range from collaborative filtering to sensor based location estimation and logical action model learning for AI planning. I will also discuss some potential future directions of transfer learning.

32 CFR 2001.15 - Classification guides.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

32 CFR 2001.15 - Classification guides.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

32 CFR 2001.15 - Classification guides.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

32 CFR 2001.15 - Classification guides.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

32 CFR 2001.15 - Classification guides.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

An International Survey of Brain Banking Operation and Characterization Practices

PubMed Central

Palmer-Aronsten, Beatrix; McCrossin, Toni; Kril, Jillian

2016-01-01

Brain banks continue to make a major contribution to the study of neurological and psychiatric disorders. The current complexity and scope of research heighten the need for well-characterized cases and the demand for larger cohorts and necessitate strategies, such as the establishment of bank networks based in regional areas. While individual brain banks have developed protocols that meet researchers' needs within the confines of resources and funding, to further promote collaboration, standardization and scientific validity and understanding of the current protocols of participating banks are required. A survey was sent to brain banks, identified by an Internet search, to investigate operational protocols, case characterization, cohort management, data collection, standardization, and degree of collaboration between banks. The majority of the 24 banks that returned the survey have been established for more than 20 years, and most are affiliated with a regional network. While prospective donor programs were the primary source of donation, the data collected on donors varied. Longitudinal information assists case characterization and enhances the analysis capabilities of research. However, acquiring this information depended on the availability of qualified staff. Respondents indicated a high level of importance for standardization, but only 8 of 24 considered this occurred between banks. Standard diagnostic criteria were not achieved in the classification of controls, and some banks relied on the researcher to indicate the criteria for classification of controls. Although the capacity to collaborate with other banks was indicated by 16 of 24 banks, this occurred infrequently. Engagement of all brain banks to participate toward a consensus of diagnostic tools, especially for controls, will strengthen collaboration. PMID:27399803

An International Survey of Brain Banking Operation and Characterization Practices.

PubMed

Palmer-Aronsten, Beatrix; Sheedy, Donna; McCrossin, Toni; Kril, Jillian

2016-12-01

Brain banks continue to make a major contribution to the study of neurological and psychiatric disorders. The current complexity and scope of research heighten the need for well-characterized cases and the demand for larger cohorts and necessitate strategies, such as the establishment of bank networks based in regional areas. While individual brain banks have developed protocols that meet researchers' needs within the confines of resources and funding, to further promote collaboration, standardization and scientific validity and understanding of the current protocols of participating banks are required. A survey was sent to brain banks, identified by an Internet search, to investigate operational protocols, case characterization, cohort management, data collection, standardization, and degree of collaboration between banks. The majority of the 24 banks that returned the survey have been established for more than 20 years, and most are affiliated with a regional network. While prospective donor programs were the primary source of donation, the data collected on donors varied. Longitudinal information assists case characterization and enhances the analysis capabilities of research. However, acquiring this information depended on the availability of qualified staff. Respondents indicated a high level of importance for standardization, but only 8 of 24 considered this occurred between banks. Standard diagnostic criteria were not achieved in the classification of controls, and some banks relied on the researcher to indicate the criteria for classification of controls. Although the capacity to collaborate with other banks was indicated by 16 of 24 banks, this occurred infrequently. Engagement of all brain banks to participate toward a consensus of diagnostic tools, especially for controls, will strengthen collaboration.

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

32 CFR 2001.16 - Fundamental classification guidance review.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Fundamental classification guidance review. 2001... INFORMATION Classification § 2001.16 Fundamental classification guidance review. (a) Performance of fundamental classification guidance reviews. An initial fundamental classification guidance review shall be...

40 CFR 152.164 - Classification procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 25 2013-07-01 2013-07-01 false Classification procedures. 152.164... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.164 Classification procedures. (a) Grouping of products for classification purposes. In its discretion, the Agency may identify...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

40 CFR 152.164 - Classification procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 24 2014-07-01 2014-07-01 false Classification procedures. 152.164... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.164 Classification procedures. (a) Grouping of products for classification purposes. In its discretion, the Agency may identify...

7 CFR 27.34 - Classification procedure.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Classification procedure. 27.34 Section 27.34... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.34 Classification procedure. Classification shall proceed as rapidly as possible, but not...

32 CFR 2001.14 - Classification challenges.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Classification challenges. 2001.14 Section 2001... Classification § 2001.14 Classification challenges. (a) Challenging classification. Authorized holders, including authorized holders outside the classifying agency, who want to challenge the classification status of...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

32 CFR 2001.14 - Classification challenges.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Classification challenges. 2001.14 Section 2001... Classification § 2001.14 Classification challenges. (a) Challenging classification. Authorized holders, including authorized holders outside the classifying agency, who want to challenge the classification status of...

40 CFR 152.164 - Classification procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 25 2012-07-01 2012-07-01 false Classification procedures. 152.164... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.164 Classification procedures. (a) Grouping of products for classification purposes. In its discretion, the Agency may identify...

7 CFR 27.34 - Classification procedure.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Classification procedure. 27.34 Section 27.34... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.34 Classification procedure. Classification shall proceed as rapidly as possible, but not...

32 CFR 2001.14 - Classification challenges.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Classification challenges. 2001.14 Section 2001... Classification § 2001.14 Classification challenges. (a) Challenging classification. Authorized holders, including authorized holders outside the classifying agency, who want to challenge the classification status of...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Proposed classifications. 2461.1 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.1 Proposed classifications. (a) Proposed classifications will...

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Changing classifications. 2461.4 Section... MANAGEMENT, DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.4 Changing classifications. Classifications may be changed...

7 CFR 27.34 - Classification procedure.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Classification procedure. 27.34 Section 27.34... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.34 Classification procedure. Classification shall proceed as rapidly as possible, but not...

32 CFR 2001.14 - Classification challenges.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Classification challenges. 2001.14 Section 2001... Classification § 2001.14 Classification challenges. (a) Challenging classification. Authorized holders, including authorized holders outside the classifying agency, who want to challenge the classification status of...

40 CFR 152.164 - Classification procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 24 2011-07-01 2011-07-01 false Classification procedures. 152.164... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.164 Classification procedures. (a) Grouping of products for classification purposes. In its discretion, the Agency may identify...

40 CFR 152.164 - Classification procedures.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 23 2010-07-01 2010-07-01 false Classification procedures. 152.164... PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.164 Classification procedures. (a) Grouping of products for classification purposes. In its discretion, the Agency may identify...

7 CFR 27.34 - Classification procedure.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification procedure. 27.34 Section 27.34... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.34 Classification procedure. Classification shall proceed as rapidly as possible, but not...

Detection of collaborative activity with Kinect depth cameras.

PubMed

Sevrin, Loic; Noury, Norbert; Abouchi, Nacer; Jumel, Fabrice; Massot, Bertrand; Saraydaryan, Jacques

2016-08-01

The health status of elderly subjects is highly correlated to their activities together with their social interactions. Thus, the long term monitoring in home of their health status, shall also address the analysis of collaborative activities. This paper proposes a preliminary approach of such a system which can detect the simultaneous presence of several subjects in a common area using Kinect depth cameras. Most areas in home being dedicated to specific tasks, the localization enables the classification of tasks, whether collaborative or not. A scenario of a 24 hours day shrunk into 24 minutes was used to validate our approach. It pointed out the need of artifacts removal to reach high specificity and good sensitivity.

22 CFR 9.4 - Original classification.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the unauthorized...

22 CFR 9.4 - Original classification.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the unauthorized...

22 CFR 9.4 - Original classification.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the unauthorized...

22 CFR 9.4 - Original classification.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Original classification. 9.4 Section 9.4... classification. (a) Definition. Original classification is the initial determination that certain information... classification. (b) Classification levels. (1) Top Secret shall be applied to information the unauthorized...

12 CFR 403.4 - Derivative classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative classification. (1) Unlike original classification which is an initial determination, derivative classification... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4...

Classification in Australia.

ERIC Educational Resources Information Center

McKinlay, John

Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

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.

32 CFR 1633.12 - Reconsideration of classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., upon which the classification is based, change or when he finds that the registrant made a... 32 National Defense 6 2010-07-01 2010-07-01 false Reconsideration of classification. 1633.12... ADMINISTRATION OF CLASSIFICATION § 1633.12 Reconsideration of classification. No classification is permanent. The...

19 CFR 152.16 - Judicial changes in classification.

Code of Federal Regulations, 2010 CFR

2010-04-01

... OF THE TREASURY (CONTINUED) CLASSIFICATION AND APPRAISEMENT OF MERCHANDISE Classification § 152.16 Judicial changes in classification. The following procedures apply to changes in classification made by... 19 Customs Duties 2 2010-04-01 2010-04-01 false Judicial changes in classification. 152.16 Section...

32 CFR 1633.12 - Reconsideration of classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., upon which the classification is based, change or when he finds that the registrant made a... 32 National Defense 6 2011-07-01 2011-07-01 false Reconsideration of classification. 1633.12... ADMINISTRATION OF CLASSIFICATION § 1633.12 Reconsideration of classification. No classification is permanent. The...

32 CFR 2103.13 - Duration of original classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Duration of original classification. 2103.13... DECLASSIFIED Original Classification § 2103.13 Duration of original classification. Original classification may be extended beyond six years only by officials with Top Secret classification authority. This...

32 CFR 2001.12 - Duration of classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Duration of classification. 2001.12 Section 2001... Classification § 2001.12 Duration of classification. (a) Determining duration of classification for information originally classified under the Order—(1) Establishing duration of classification. Except for information...

32 CFR 2001.12 - Duration of classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Duration of classification. 2001.12 Section 2001... Classification § 2001.12 Duration of classification. (a) Determining duration of classification for information originally classified under the Order—(1) Establishing duration of classification. Except for information...

32 CFR 2001.12 - Duration of classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Duration of classification. 2001.12 Section 2001... Classification § 2001.12 Duration of classification. (a) Determining duration of classification for information originally classified under the Order—(1) Establishing duration of classification. Except for information...

Effects of two classification strategies on a Benthic Community Index for streams in the Northern Lakes and Forests Ecoregion

USGS Publications Warehouse

Butcher, Jason T.; Stewart, Paul M.; Simon, Thomas P.

2003-01-01

Ninety-four sites were used to analyze the effects of two different classification strategies on the Benthic Community Index (BCI). The first, a priori classification, reflected the wetland status of the streams; the second, a posteriori classification, used a bio-environmental analysis to select classification variables. Both classifications were examined by measuring classification strength and testing differences in metric values with respect to group membership. The a priori (wetland) classification strength (83.3%) was greater than the a posteriori (bio-environmental) classification strength (76.8%). Both classifications found one metric that had significant differences between groups. The original index was modified to reflect the wetland classification by re-calibrating the scoring criteria for percent Crustacea and Mollusca. A proposed refinement to the original Benthic Community Index is suggested. This study shows the importance of using hypothesis-driven classifications, as well as exploratory statistical analysis, to evaluate alternative ways to reveal environmental variability in biological assessment tools.

14 CFR 1203.501 - Applying derivative classification markings.

Code of Federal Regulations, 2011 CFR

2011-01-01

... INFORMATION SECURITY PROGRAM Derivative Classification § 1203.501 Applying derivative classification markings... classification decisions: (b) Verify the information's current level of classification so far as practicable...

14 CFR 1203.501 - Applying derivative classification markings.

Code of Federal Regulations, 2010 CFR

2010-01-01

... INFORMATION SECURITY PROGRAM Derivative Classification § 1203.501 Applying derivative classification markings... classification decisions: (b) Verify the information's current level of classification so far as practicable...

Classifying clinical decision making: a unifying approach.

PubMed

Buckingham, C D; Adams, A

2000-10-01

This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.

Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification.

PubMed

Borozan, Ivan; Watt, Stuart; Ferretti, Vincent

2015-05-01

Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized. Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the discriminatory ability of individual similarity measures in the training set. Because the similarity between some sequences is determined more accurately with one type of measure rather than another, our classifier allows different sets of weights to be associated with different sequences. Using five different similarity measures, we show that our model significantly improves the classification accuracy over the current composition- and alignment-based models, when predicting the taxonomic lineage for both short viral sequence fragments and complete viral sequences. We also show that our model can be used effectively for the classification of reads from a real metagenome dataset as well as protein sequences. All the datasets and the code used in this study are freely available at https://collaborators.oicr.on.ca/vferretti/borozan_csss/csss.html. ivan.borozan@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification

PubMed Central

Borozan, Ivan; Watt, Stuart; Ferretti, Vincent

2015-01-01

Motivation: Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized. Results: Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the discriminatory ability of individual similarity measures in the training set. Because the similarity between some sequences is determined more accurately with one type of measure rather than another, our classifier allows different sets of weights to be associated with different sequences. Using five different similarity measures, we show that our model significantly improves the classification accuracy over the current composition- and alignment-based models, when predicting the taxonomic lineage for both short viral sequence fragments and complete viral sequences. We also show that our model can be used effectively for the classification of reads from a real metagenome dataset as well as protein sequences. Availability and implementation: All the datasets and the code used in this study are freely available at https://collaborators.oicr.on.ca/vferretti/borozan_csss/csss.html. Contact: ivan.borozan@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573913

Diagnosis and classification of Idiopathic Inflammatory Myopathies

PubMed Central

Lundberg, Ingrid E.; Miller, Frederick W.; Tjärnlund, Anna; Bottai, Matteo

2016-01-01

The idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of diseases, collectively named myositis, sharing symptoms of muscle weakness and muscle fatigue and inflammation in muscle tissue. Other organs are frequently involved supporting that these are systemic inflammatory diseases. The IIMs can be sub-grouped into dermatomyositis, polymyositis and inclusion body myositis. The myositis-specific autoantibodies (MSAs) identify other and often more distinct clinical phenotypes, such as the anti-synthetase syndrome with antisynthetase autoantibodies and frequent interstitial lung disease (ILD) and anti-SRP and anti-HMGCR autoantibodies that identify necrotizing myopathy. The MSAs are important both to support myositis diagnosis and to identify subgroups with different patterns of extramuscular organ involvement such as ILD. Another cornerstone in the diagnostic procedure is muscle biopsy to identify inflammation and to exclude non-inflammatory myopathies. Treatment effect and prognosis varies by subgroup. To develop new and better therapies, validated classification criteria that identify distinct subgroups of myositis are critical.. The lack of such criteria was the main rationale for the development of new classification criteria for inflammatory myopathies, which are summarized in this review, along with an historical background on previous diagnostic and classification criteria. As these are rare diseases with a prevalence of 10 in 100 000 individuals an international collaboration was essential, as was the interdisciplinary effort including adult and paediatric experts in rheumatology, neurology, dermatology and epidemiology. The new criteria have been developed based on data from more than 1 500 patients from 47 centers world-wide and are based on clinically easily available variables. PMID:27320359

Is overall similarity classification less effortful than single-dimension classification?

PubMed

Wills, Andy J; Milton, Fraser; Longmore, Christopher A; Hester, Sarah; Robinson, Jo

2013-01-01

It is sometimes argued that the implementation of an overall similarity classification is less effortful than the implementation of a single-dimension classification. In the current article, we argue that the evidence securely in support of this view is limited, and report additional evidence in support of the opposite proposition--overall similarity classification is more effortful than single-dimension classification. Using a match-to-standards procedure, Experiments 1A, 1B and 2 demonstrate that concurrent load reduces the prevalence of overall similarity classification, and that this effect is robust to changes in the concurrent load task employed, the level of time pressure experienced, and the short-term memory requirements of the classification task. Experiment 3 demonstrates that participants who produced overall similarity classifications from the outset have larger working memory capacities than those who produced single-dimension classifications initially, and Experiment 4 demonstrates that instructions to respond meticulously increase the prevalence of overall similarity classification.

7 CFR 27.31 - Classification of cotton.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Classification of cotton. 27.31 Section 27.31... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.31 Classification of cotton. For purposes of subsection 15b (f) of The Act, classification of...

7 CFR 27.31 - Classification of cotton.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Classification of cotton. 27.31 Section 27.31... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.31 Classification of cotton. For purposes of subsection 15b (f) of The Act, classification of...

32 CFR 2103.12 - Level of original classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Level of original classification. 2103.12... DECLASSIFIED Original Classification § 2103.12 Level of original classification. Unnecessary classification, and classification at a level higher than is necessary, shall be avoided. If there is reasonable doubt...

Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

PubMed Central

Austin, Peter C; Lee, Douglas S

2011-01-01

Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

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

7 CFR 28.911 - Review classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Review classification. 28.911 Section 28.911... Producers Classification § 28.911 Review classification. (a) A producer may request one review classification for each bale of eligible cotton. The fee for review classification is $2.20 per bale. (b) Samples...

14 CFR § 1203.407 - Duration of classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Duration of classification. § 1203.407... SECURITY PROGRAM Guides for Original Classification § 1203.407 Duration of classification. (a) At the time of original classification, the original classification authority shall establish a specific date or...

Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery.

PubMed

Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

2011-01-01

This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.

Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery

PubMed Central

LI, GUIYING; LU, DENGSHENG; MORAN, EMILIO; HETRICK, SCOTT

2011-01-01

This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms – maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes. PMID:22368311

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/

The ICNP-BaT--a multilingual web-based tool to support the collaborative translation of the International Classification for Nursing Practice (ICNP).

PubMed

Schrader, Ulrich; Tackenberg, Peter; Widmer, Rudolf; Portenier, Lucien; König, Peter

2007-01-01

To ease and speed up the translation of the ICNP version 1 into the German language a web service was developed to support the collaborative work of all Austrian, Swiss, and German translators and subsequently of the evaluators of the resultant translation. The web service does help to support a modified Delphi technique. Since the web service is multilingual by design it can facilitate the translation of the ICNP into other languages as well. The process chosen can be adopted by other projects involved in translating terminologies.

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2013-01-01 2013-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2014-01-01 2014-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

Knowledge Representation and Care Planning for Population Health Management.

PubMed

Merahn, Steven

2015-01-01

The traditional organizing principles of medical knowledge may be insufficient to allow for problem representations that are relevant to solution development in emerging models of care such as population health management. Operational classification and central management of clinical and quality objectives and associated strategies will allow for productive innovation in care design and better support goal-directed collaboration among patients and their health resource communities.

The Johns Hopkins RTR Consortium: A Collaborative Approach to Advance Translational Science and Standardize Clinical Monitoring of Restorative Transplantation

DTIC Science & Technology

2016-10-01

based Therapy, Large animal models, Allograft, Hand Transplantation ,Face Transplantation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT...Changes in Approach b. Problems/Delays and Plans for Resolution c. Changes that Impacted Expenditures d. Changes in use or care of vertebrate animals ...Vascularized Composite Allotransplantation Immunoregulation Tolerance Rejection Ischemia Reperfusion Cell based Therapy Large animal models

The Value of Doctrine for a Developing Organization

DTIC Science & Technology

2009-12-01

increasingly public topic since the events of September 11, 2001. Customs and Border Protection (CBP) is one of the Department of Homeland Security’s...CBP was created, the majority of the existing organization came from two legacy agencies, U.S. Customs and the Immigration and Naturalization Service...Collaboration, Merger, Trust, Customs And Border Protection, CBP 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY

Friction Drag Reduction Using Superhydrophobic Surface in High Reynolds Number Turbulent Flow

DTIC Science & Technology

2017-12-25

high Reynolds numbers by using the large towing tank available Naval Academy in Annapolis, in collaboration with Professor Michael...NAME(S) AND ADDRESS(ES) 12. DISTRIBUTION/ AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION... High Reynolds Number Turbulent Flow Smits, Alexander J Princeton University, Princeton, NJ 08544 N/A Office of Naval Research 875 N. Randolph Street

Tribometer for Ultra Harsh Environments

DTIC Science & Technology

2006-05-01

aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of infonmation...harsh environments 1S. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF : 17. LIMITATION OF 18. NUMBER 19a. NAME OF RESPONSIBLE PERSON a . REPORT b...can provide a pathway for the collaboration of several universities, government laboratories and industry to evaluate next generation of aerospace

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

Meeting the criteria of a nursing diagnosis classification: Evaluation of ICNP, ICF, NANDA and ZEFP.

PubMed

Müller-Staub, Maria; Lavin, Mary Ann; Needham, Ian; van Achterberg, Theo

2007-07-01

Few studies described nursing diagnosis classification criteria and how classifications meet these criteria. The purpose was to identify criteria for nursing diagnosis classifications and to assess how these criteria are met by different classifications. First, a literature review was conducted (N=50) to identify criteria for nursing diagnoses classifications and to evaluate how these criteria are met by the International Classification of Nursing Practice (ICNP), the International Classification of Functioning, Disability and Health (ICF), the International Nursing Diagnoses Classification (NANDA), and the Nursing Diagnostic System of the Centre for Nursing Development and Research (ZEFP). Using literature review based general and specific criteria, the principal investigator evaluated each classification, applying a matrix. Second, a convenience sample of 20 nursing experts from different Swiss care institutions answered standardized interview forms, querying current national and international classification state and use. The first general criterion is that a diagnosis classification should describe the knowledge base and subject matter for which the nursing profession is responsible. ICNP) and NANDA meet this goal. The second general criterion is that each class fits within a central concept. The ICF and NANDA are the only two classifications built on conceptually driven classes. The third general classification criterion is that each diagnosis possesses a description, diagnostic criteria, and related etiologies. Although ICF and ICNP describe diagnostic terms, only NANDA fulfils this criterion. The analysis indicated that NANDA fulfilled most of the specific classification criteria in the matrix. The nursing experts considered NANDA to be the best-researched and most widely implemented classification in Switzerland and internationally. The international literature and the opinion of Swiss expert nurses indicate that-from the perspective of classifying comprehensive nursing diagnoses-NANDA should be recommended for nursing practice and electronic nursing documentation. Study limitations and future research needs are discussed.

Three-column classification and Schatzker classification: a three- and two-dimensional computed tomography characterisation and analysis of tibial plateau fractures.

PubMed

Patange Subba Rao, Sheethal Prasad; Lewis, James; Haddad, Ziad; Paringe, Vishal; Mohanty, Khitish

2014-10-01

The aim of the study was to evaluate inter-observer reliability and intra-observer reproducibility between the three-column classification and Schatzker classification systems using 2D and 3D CT models. Fifty-two consecutive patients with tibial plateau fractures were evaluated by five orthopaedic surgeons. All patients were classified into Schatzker and three-column classification systems using x-rays and 2D and 3D CT images. The inter-observer reliability was evaluated in the first round and the intra-observer reliability was determined during the second round 2 weeks later. The average intra-observer reproducibility for the three-column classification was from substantial to excellent in all sub classifications, as compared with Schatzker classification. The inter-observer kappa values increased from substantial to excellent in three-column classification and to moderate in Schatzker classification The average values for three-column classification for all the categories are as follows: (I-III) k2D = 0.718, 95% CI 0.554-0.864, p < 0.0001 and average 3D = 0.874, 95% CI 0.754-0.890, p < 0.0001. For Schatzker classification system, the average values for all six categories are as follows: (I-VI) k2D = 0.536, 95% CI 0.365-0.685, p < 0.0001 and average k3D = 0.552 95% CI 0.405-0.700, p < 0.0001. The values are statistically significant. Statistically significant inter-observer values in both rounds were noted with the three-column classification, making it statistically an excellent agreement. The intra-observer reproducibility for the three-column classification improved as compared with the Schatzker classification. The three-column classification seems to be an effective way to characterise and classify fractures of tibial plateau.

Object-Based Random Forest Classification of Land Cover from Remotely Sensed Imagery for Industrial and Mining Reclamation

NASA Astrophysics Data System (ADS)

Chen, Y.; Luo, M.; Xu, L.; Zhou, X.; Ren, J.; Zhou, J.

2018-04-01

The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification accuracy was higher than that of SVM and ANN under the same feature variables. In terms of efficiency, the RF classification method performs better than SVM and ANN, it is more capable of handling multidimensional feature variables. The RF method combined with object-based analysis approach could highlight the classification accuracy further. The multiresolution segmentation approach on the basis of ESP scale parameter optimization was used for obtaining six scales to execute image segmentation, when the segmentation scale was 49, the classification accuracy reached the highest value of 89.58 %. The classification accuracy of object-based RF classification was 1.42 % higher than that of pixel-based classification (88.16 %), and the classification accuracy was further improved. Therefore, the RF classification method combined with object-based analysis approach could achieve relatively high accuracy in the classification and extraction of land use information for industrial and mining reclamation areas. Moreover, the interpretation of remotely sensed imagery using the proposed method could provide technical support and theoretical reference for remotely sensed monitoring land reclamation.

46 CFR 30.10-9 - Classification requirements-TB/ALL.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Classification requirements-TB/ALL. 30.10-9 Section 30... Definitions § 30.10-9 Classification requirements—TB/ALL. The term classification requirements means... classification society. ...

46 CFR 30.10-9 - Classification requirements-TB/ALL.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Classification requirements-TB/ALL. 30.10-9 Section 30... Definitions § 30.10-9 Classification requirements—TB/ALL. The term classification requirements means... classification society. ...

46 CFR 30.10-9 - Classification requirements-TB/ALL.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Classification requirements-TB/ALL. 30.10-9 Section 30... Definitions § 30.10-9 Classification requirements—TB/ALL. The term classification requirements means... classification society. ...

5 CFR 1312.7 - Derivative classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., DOWNGRADING, DECLASSIFICATION AND SAFEGUARDING OF NATIONAL SECURITY INFORMATION Classification and Declassification of National Security Information § 1312.7 Derivative classification. A derivative classification... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Derivative classification. 1312.7 Section...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Classification requirements. 9701.221 Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT... HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

PubMed Central

Moran, Emilio Federico.

2010-01-01

High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervised classification, incorporation of textural images and multispectral images, spectral-spatial classifier, and segmentation-based classification are examined in a relatively new developing urban landscape, Lucas do Rio Verde in Mato Grosso State, Brazil. This research shows that use of spatial information during the image classification procedure, either through the integrated use of textural and spectral images or through the use of segmentation-based classification method, can significantly improve land cover classification performance. PMID:21643433

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

A new classification of spin in systematic reviews and meta-analyses was developed and ranked according to the severity.

PubMed

Yavchitz, Amélie; Ravaud, Philippe; Altman, Douglas G; Moher, David; Hrobjartsson, Asbjørn; Lasserson, Toby; Boutron, Isabelle

2016-07-01

We aimed to (1) identify and classify spin (i.e., a description that overstates efficacy and/or understates harm) in systematic reviews and (2) rank spin in abstracts of systematic reviews according to their severity (i.e., the likelihood of distorting readers' interpretation of the results). First, we used a four-phase consensus process to develop a classification of different types of spin. Second, we ranked the types of spin in abstracts according to their severity using a Q-sort survey with members of the Cochrane Collaboration. We identified 39 types of spin, 28 from the main text and 21 from the abstract; 13 were specific to the systematic review design. Spin was classified into three categories: (1) misleading reporting, (2) misleading interpretation, and (3) inappropriate extrapolation. Spin ranked as the most severe by the 122 people who participated in the survey were (1) recommendations for clinical practice not supported by findings in the conclusion, (2) misleading title, and (3) selective reporting. This study allowed for identifying spin that is likely to distort interpretation. Our classification could help authors, editors, and reviewers avoid spin in reports of systematic reviews. Copyright © 2016 Elsevier Inc. All rights reserved.

Towards the system-wide implementation of the International Classification of Functioning, Disability and Health in routine practice: Lessons from a pilot study in China.

PubMed

Li, Jianan; Prodinger, Birgit; Reinhardt, Jan D; Stucki, Gerold

2016-06-13

In 2011 the Chinese leadership in rehabilitation, in collaboration with the International Classification of Functioning, Disability and Health (ICF) Research Branch, embarked on an effort towards the system-wide implementation of the ICF in the healthcare system in China. We report here on the lessons learned from the pilot phase of testing the ICF Generic Set, a parsimonious set of 7 ICF categories, which have been shown to best describe functioning across the general population and people with various health conditions, for use in routine clinical practice in China. The paper discusses whether classification and measurement are compatible, what number of ICF categories should be included in data collection in routine practice, and the usefulness of a functioning profile and functioning score in clinical practice and health research planning. In addition, the paper reflects on the use of ICF qualifiers in a rating scale and the particularities of certain ICF categories contained in the ICF Generic Set when used as items in the context of Chinese rehabilitation and healthcare. Finally, the steps required to enhance the utility of system-wide implementation of the ICF in rehabilitation and healthcare services are set out.

Does the Chemical Diversity of the Order Haplosclerida (Phylum Porifera: Class Demospongia) Fit with Current Taxonomic Classification?

PubMed

Tribalat, Marie-Aude; Marra, Maria V; McCormack, Grace P; Thomas, Olivier P

2016-06-01

Sponges and their associated microbiota are well known to produce a large diversity of natural products, also called specialized metabolites. In addition to their potential use in the pharmaceutical industry, these rather species-specific compounds may help in the classification of some particular sponge groups. We review herein compounds isolated from haplosclerid sponges (Class Demospongia, Order Haplosclerida) in order to help in the revision of this large group of marine invertebrates. We focus only on 3-alkylpyridine derivatives and polyacetylenic compounds, as these two groups of natural products are characteristic of haplosclerid species and are highly diverse. A close collaboration between chemists and biologists is required in order to fully apply chemotaxonomical approaches, and whenever possible biological data should include morphological and molecular data and some insight into their microbial abundance. Georg Thieme Verlag KG Stuttgart · New York.

Genomic landscape of gastric cancer: molecular classification and potential targets.

PubMed

Guo, Jiawei; Yu, Weiwei; Su, Hui; Pang, Xiufeng

2017-02-01

Gastric cancer imposes a considerable health burden worldwide, and its mortality ranks as the second highest for all types of cancers. The limited knowledge of the molecular mechanisms underlying gastric cancer tumorigenesis hinders the development of therapeutic strategies. However, ongoing collaborative sequencing efforts facilitate molecular classification and unveil the genomic landscape of gastric cancer. Several new drivers and tumorigenic pathways in gastric cancer, including chromatin remodeling genes, RhoA-related pathways, TP53 dysregulation, activation of receptor tyrosine kinases, stem cell pathways and abnormal DNA methylation, have been revealed. These newly identified genomic alterations await translation into clinical diagnosis and targeted therapies. Considering that loss-of-function mutations are intractable, synthetic lethality could be employed when discussing feasible therapeutic strategies. Although many challenges remain to be tackled, we are optimistic regarding improvements in the prognosis and treatment of gastric cancer in the near future.

Representation of Nursing Terminologies in UMLS

PubMed Central

Kim, Tae Youn; Coenen, Amy; Hardiker, Nicholas; Bartz, Claudia C.

2011-01-01

There are seven nursing terminologies or classifications that are considered a standard to support nursing practice in the U.S. Harmonizing these terminologies will enhance the interoperability of clinical data documented across nursing practice. As a first step to harmonize the nursing terminologies, the purpose of this study was to examine how nursing problems or diagnostic concepts from select terminologies were cross-mapped in Unified Medical Language System (UMLS). A comparison analysis was conducted by examining whether cross-mappings available in UMLS through concept unique identifiers were consistent with cross-mappings conducted by human experts. Of 423 concepts from three terminologies, 411 (97%) were manually cross-mapped by experts to the International Classification for Nursing Practice. The UMLS semantic mapping among the 411 nursing concepts presented 33.6% accuracy (i.e., 138 of 411 concepts) when compared to expert cross-mappings. Further research and collaboration among experts in this field are needed for future enhancement of UMLS. PMID:22195127

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.

49 CFR 8.17 - Classification challenges.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 1 2011-10-01 2011-10-01 false Classification challenges. 8.17 Section 8.17 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.17 Classification challenges. (a) Authorized...

46 CFR 90.10-35 - Recognized classification society.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Recognized classification society. 90.10-35 Section 90... classification society. The term recognized classification society means the American Bureau of Shipping or other classification society recognized by the Commandant. ...

49 CFR 8.17 - Classification challenges.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 1 2013-10-01 2013-10-01 false Classification challenges. 8.17 Section 8.17 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.17 Classification challenges. (a) Authorized...

49 CFR 8.17 - Classification challenges.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 1 2014-10-01 2014-10-01 false Classification challenges. 8.17 Section 8.17 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.17 Classification challenges. (a) Authorized...

49 CFR 8.17 - Classification challenges.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 1 2012-10-01 2012-10-01 false Classification challenges. 8.17 Section 8.17 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.17 Classification challenges. (a) Authorized...

49 CFR 8.17 - Classification challenges.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 1 2010-10-01 2010-10-01 false Classification challenges. 8.17 Section 8.17 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.17 Classification challenges. (a) Authorized...

Unveiling a spinor field classification with non-Abelian gauge symmetries

NASA Astrophysics Data System (ADS)

Fabbri, Luca; da Rocha, Roldão

2018-05-01

A spinor fields classification with non-Abelian gauge symmetries is introduced, generalizing the U(1) gauge symmetries-based Lounesto's classification. Here, a more general classification, contrary to the Lounesto's one, encompasses spinor multiplets, corresponding to non-Abelian gauge fields. The particular case of SU(2) gauge symmetry, encompassing electroweak and electromagnetic conserved charges, is then implemented by a non-Abelian spinor classification, now involving 14 mixed classes of spinor doublets. A richer flagpole, dipole, and flag-dipole structure naturally descends from this general classification. The Lounesto's classification of spinors is shown to arise as a Pauli's singlet, into this more general classification.

Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

NASA Technical Reports Server (NTRS)

Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

1990-01-01

Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

OMOGENIA: A Semantically Driven Collaborative Environment

NASA Astrophysics Data System (ADS)

Liapis, Aggelos

Ontology creation can be thought of as a social procedure. Indeed the concepts involved in general need to be elicited from communities of domain experts and end-users by teams of knowledge engineers. Many problems in ontology creation appear to resemble certain problems in software design, particularly with respect to the setup of collaborative systems. For instance, the resolution of conceptual conflicts between formalized ontologies is a major engineering problem as ontologies move into widespread use on the semantic web. Such conflict resolution often requires human collaboration and cannot be achieved by automated methods with the exception of simple cases. In this chapter we discuss research in the field of computer-supported cooperative work (CSCW) that focuses on classification and which throws light on ontology building. Furthermore, we present a semantically driven collaborative environment called OMOGENIA as a natural way to display and examine the structure of an evolving ontology in a collaborative setting.

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...

Classification of wheat: Badhwar profile similarity technique

NASA Technical Reports Server (NTRS)

Austin, W. W.

1980-01-01

The Badwar profile similarity classification technique used successfully for classification of corn was applied to spring wheat classifications. The software programs and the procedures used to generate full-scene classifications are presented, and numerical results of the acreage estimations are given.

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...

14 CFR 1203.406 - Additional classification factors.

Code of Federal Regulations, 2011 CFR

2011-01-01

... PROGRAM Guides for Original Classification § 1203.406 Additional classification factors. In determining the appropriate classification category, the following additional factors should be considered: (a... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Additional classification factors. 1203.406...

32 CFR 2001.13 - Classification prohibitions and limitations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Classification prohibitions and limitations... INFORMATION Classification § 2001.13 Classification prohibitions and limitations. (a) Declassification without... determined by an original classification authority with jurisdiction over the information, remains classified...

15 CFR 30.61 - Statistical classification schedules.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 15 Commerce and Foreign Trade 1 2011-01-01 2011-01-01 false Statistical classification schedules... § 30.61 Statistical classification schedules. The following statistical classification schedules are....census.gov/trade. (a) Schedule B—Statistical Classification for Domestic and Foreign Commodities Exported...

15 CFR 30.61 - Statistical classification schedules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Statistical classification schedules... § 30.61 Statistical classification schedules. The following statistical classification schedules are....census.gov/trade. (a) Schedule B—Statistical Classification for Domestic and Foreign Commodities Exported...

7 CFR 28.9 - Inspection; sampling; classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Inspection; sampling; classification. 28.9 Section 28... Administrative and General § 28.9 Inspection; sampling; classification. The inspection, sampling, and... instructions for the sampling, classification, and issuance of classification memoranda for cotton classed for...

7 CFR 28.9 - Inspection; sampling; classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Inspection; sampling; classification. 28.9 Section 28... Administrative and General § 28.9 Inspection; sampling; classification. The inspection, sampling, and... instructions for the sampling, classification, and issuance of classification memoranda for cotton classed for...

49 CFR 8.15 - Mandatory review for classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 1 2011-10-01 2011-10-01 false Mandatory review for classification. 8.15 Section 8.15 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.15 Mandatory review for classification...

Project implementation : classification of organic soils and classification of marls - training of INDOT personnel.

DOT National Transportation Integrated Search

2012-09-01

This is an implementation project for the research completed as part of the following projects: SPR3005 Classification of Organic Soils : and SPR3227 Classification of Marl Soils. The methods developed for the classification of both soi...

7 CFR 28.911 - Review classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one review...

6 CFR 7.26 - Derivative classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 6 Domestic Security 1 2012-01-01 2012-01-01 false Derivative classification. 7.26 Section 7.26... INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is defined... already classified, and marking the newly developed material consistent with the classification markings...

7 CFR 28.911 - Review classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one review...

6 CFR 7.26 - Derivative classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 6 Domestic Security 1 2013-01-01 2013-01-01 false Derivative classification. 7.26 Section 7.26... INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is defined... already classified, and marking the newly developed material consistent with the classification markings...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

6 CFR 7.26 - Derivative classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 6 Domestic Security 1 2014-01-01 2014-01-01 false Derivative classification. 7.26 Section 7.26... INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is defined... already classified, and marking the newly developed material consistent with the classification markings...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

7 CFR 28.911 - Review classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one review...

78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-18

...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and known as ``registration'' by the U.S. cotton industry and the Intercontinental Exchange (ICE). In...

76 FR 60388 - Revision of Cotton Futures Classification Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-29

...-005] RIN 0581-AD16 Revision of Cotton Futures Classification Procedures AGENCY: Agricultural Marketing... update the procedures for cotton futures quality classification services by using Smith-Doxey classification data in the cotton futures classification process. In addition, references to a separate and...

77 FR 5379 - Revision of Cotton Futures Classification Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-03

... 0581-AD16 Revision of Cotton Futures Classification Procedures AGENCY: Agricultural Marketing Service... for cotton futures quality classification services by using Smith-Doxey classification data in the cotton futures classification process. In addition, references to a separate and optional review of...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

37 CFR 2.85 - Classification schedules.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Classification schedules. 2..., DEPARTMENT OF COMMERCE RULES OF PRACTICE IN TRADEMARK CASES Classification § 2.85 Classification schedules. (a) International classification system. Section 6.1 of this chapter sets forth the international...

7 CFR 28.911 - Review classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one review...

7 CFR 27.14 - Filing of classification and Micronaire determination requests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Filing of classification and Micronaire determination... STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.14 Filing of classification and Micronaire determination requests...

7 CFR 27.14 - Filing of classification and Micronaire determination requests.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Filing of classification and Micronaire determination... STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.14 Filing of classification and Micronaire determination requests...

18 CFR 3a.31 - Classification markings and special notations.

Code of Federal Regulations, 2011 CFR

2011-04-01

... unit taking the action. When classification changes are made, the classification markings themselves... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Classification markings... REGULATORY COMMISSION, DEPARTMENT OF ENERGY GENERAL RULES NATIONAL SECURITY INFORMATION Classification...

7 CFR 27.36 - Classification and Micronaire determinations based on official standards.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification and Micronaire determinations based on... COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.36 Classification and Micronaire...

7 CFR 27.87 - Fees; classification and Micronaire determination information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Fees; classification and Micronaire determination... STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Costs of Classification and Micronaire § 27.87 Fees; classification and Micronaire determination...

7 CFR 27.87 - Fees; classification and Micronaire determination information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Fees; classification and Micronaire determination... STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Costs of Classification and Micronaire § 27.87 Fees; classification and Micronaire determination...

7 CFR 27.36 - Classification and Micronaire determinations based on official standards.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification and Micronaire determinations based on... COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.36 Classification and Micronaire...

49 CFR 8.19 - Procedures for submitting and processing requests for classification reviews.

Code of Federal Regulations, 2010 CFR

2010-10-01

... classification determination made by another department or agency, the Committee will immediately consult with... for classification reviews. 8.19 Section 8.19 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information...

14 CFR 1203.203 - Degree of protection.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Authorized categories of classification. The three categories of classification, as authorized and defined in... be safeguarded as if it were classified pending a determination by an original classification... appropriate level of classification, it shall be safeguarded at the higher level of classification pending a...

Radiographic classifications in Perthes disease

PubMed Central

Huhnstock, Stefan; Svenningsen, Svein; Merckoll, Else; Catterall, Anthony; Terjesen, Terje; Wiig, Ola

2017-01-01

Background and purpose Different radiographic classifications have been proposed for prediction of outcome in Perthes disease. We assessed whether the modified lateral pillar classification would provide more reliable interobserver agreement and prognostic value compared with the original lateral pillar classification and the Catterall classification. Patients and methods 42 patients (38 boys) with Perthes disease were included in the interobserver study. Their mean age at diagnosis was 6.5 (3–11) years. 5 observers classified the radiographs in 2 separate sessions according to the Catterall classification, the original and the modified lateral pillar classifications. Interobserver agreement was analysed using weighted kappa statistics. We assessed the associations between the classifications and femoral head sphericity at 5-year follow-up in 37 non-operatively treated patients in a crosstable analysis (Gamma statistics for ordinal variables, γ). Results The original lateral pillar and Catterall classifications showed moderate interobserver agreement (kappa 0.49 and 0.43, respectively) while the modified lateral pillar classification had fair agreement (kappa 0.40). The original lateral pillar classification was strongly associated with the 5-year radiographic outcome, with a mean γ correlation coefficient of 0.75 (95% CI: 0.61–0.95) among the 5 observers. The modified lateral pillar and Catterall classifications showed moderate associations (mean γ correlation coefficient 0.55 [95% CI: 0.38–0.66] and 0.64 [95% CI: 0.57–0.72], respectively). Interpretation The Catterall classification and the original lateral pillar classification had sufficient interobserver agreement and association to late radiographic outcome to be suitable for clinical use. Adding the borderline B/C group did not increase the interobserver agreement or prognostic value of the original lateral pillar classification. PMID:28613966

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification... authority. The name and position, or personal identifier, of the original classification authority shall...

46 CFR 8.260 - Revocation of classification society recognition.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the minimum...

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...

49 CFR 8.19 - Procedures for submitting and processing requests for classification reviews.

Code of Federal Regulations, 2011 CFR

2011-10-01

... for classification reviews. 8.19 Section 8.19 Transportation Office of the Secretary of Transportation CLASSIFIED INFORMATION: CLASSIFICATION/DECLASSIFICATION/ACCESS Classification/Declassification of Information § 8.19 Procedures for submitting and processing requests for classification reviews. (a) The Director...

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...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

39 CFR 3020.11 - Initial Mail Classification Schedule.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 39 Postal Service 1 2014-07-01 2014-07-01 false Initial Mail Classification Schedule. 3020.11 Section 3020.11 Postal Service POSTAL REGULATORY COMMISSION PERSONNEL PRODUCT LISTS Mail Classification Schedule § 3020.11 Initial Mail Classification Schedule. The initial Mail Classification Schedule shall...

28 CFR 345.20 - Position classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 28 Judicial Administration 2 2012-07-01 2012-07-01 false Position classification. 345.20 Section... INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate... the objectives and principles of pay classification as a part of the routine orientation of new FPI...

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Size classifications. 51.2836 Section 51.2836...) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum diameter Inches Millimeters Maximum...

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Size classifications. 51.2836 Section 51.2836...-Granex-Grano and Creole Types) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

28 CFR 345.20 - Position classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 28 Judicial Administration 2 2014-07-01 2014-07-01 false Position classification. 345.20 Section... INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate... the objectives and principles of pay classification as a part of the routine orientation of new FPI...

12 CFR 1777.20 - Capital classifications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 12 Banks and Banking 9 2013-01-01 2013-01-01 false Capital classifications. 1777.20 Section 1777... DEVELOPMENT SAFETY AND SOUNDNESS PROMPT CORRECTIVE ACTION Capital Classifications and Orders Under Section 1366 of the 1992 Act § 1777.20 Capital classifications. (a) Capital classifications after the effective...

12 CFR 1777.20 - Capital classifications.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 10 2014-01-01 2014-01-01 false Capital classifications. 1777.20 Section 1777... DEVELOPMENT SAFETY AND SOUNDNESS PROMPT CORRECTIVE ACTION Capital Classifications and Orders Under Section 1366 of the 1992 Act § 1777.20 Capital classifications. (a) Capital classifications after the effective...

22 CFR 9.8 - Classification challenges.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

7 CFR 51.2284 - Size classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Size classification. 51.2284 Section 51.2284... Size classification. The following classifications are provided to describe the size of any lot... shall conform to the requirements of the specified classification as defined below: (a) Halves. Lot...

7 CFR 51.2284 - Size classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Size classification. 51.2284 Section 51.2284...) Size Requirements § 51.2284 Size classification. The following classifications are provided to describe... of kernels in the lot shall conform to the requirements of the specified classification as defined...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 28 Judicial Administration 2 2014-07-01 2014-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

28 CFR 345.20 - Position classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 2 2013-07-01 2013-07-01 false Position classification. 345.20 Section... INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate... the objectives and principles of pay classification as a part of the routine orientation of new FPI...

7 CFR 51.2284 - Size classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Size classification. 51.2284 Section 51.2284...) Size Requirements § 51.2284 Size classification. The following classifications are provided to describe... of kernels in the lot shall conform to the requirements of the specified classification as defined...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

43 CFR 2461.2 - Classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false Classifications. 2461.2 Section 2461.2..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Multiple-Use Classification Procedures § 2461.2 Classifications. Not less than 60 days after publication of the...

12 CFR 1777.20 - Capital classifications.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 9 2012-01-01 2012-01-01 false Capital classifications. 1777.20 Section 1777... DEVELOPMENT SAFETY AND SOUNDNESS PROMPT CORRECTIVE ACTION Capital Classifications and Orders Under Section 1366 of the 1992 Act § 1777.20 Capital classifications. (a) Capital classifications after the effective...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 28 Judicial Administration 2 2012-07-01 2012-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 2 2013-07-01 2013-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

7 CFR 51.2281 - Color classifications.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Color classifications. 51.2281 Section 51.2281...) Color Requirements § 51.2281 Color classifications. The following classifications are provided to... the lot shall not be darker than the darkest color permitted in the specified classification as shown...

22 CFR 9.8 - Classification challenges.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification, the following shall be indicated in a manner that is immediately apparent: (1) Classification...

7 CFR 51.2281 - Color classifications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Color classifications. 51.2281 Section 51.2281...) Color Requirements § 51.2281 Color classifications. The following classifications are provided to... the lot shall not be darker than the darkest color permitted in the specified classification as shown...

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Size classifications. 51.2836 Section 51.2836...-Granex-Grano and Creole Types) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum...

22 CFR 9.8 - Classification challenges.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification, the following shall be indicated in a manner that is immediately apparent: (1) Classification...

7 CFR 51.2281 - Color classifications.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Color classifications. 51.2281 Section 51.2281... Color classifications. The following classifications are provided to describe the color of any lot... than the darkest color permitted in the specified classification as shown on the color chart. ...

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification, the following shall be indicated in a manner that is immediately apparent: (1) Classification...

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.

7 CFR 27.80 - Fees; classification, Micronaire, and supervision.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Fees; classification, Micronaire, and supervision. 27... Classification and Micronaire § 27.80 Fees; classification, Micronaire, and supervision. For services rendered by... classification and Micronaire determination results certified on cotton class certificates.) (e) Supervision, by...

7 CFR 27.80 - Fees; classification, Micronaire, and supervision.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Fees; classification, Micronaire, and supervision. 27... Classification and Micronaire § 27.80 Fees; classification, Micronaire, and supervision. For services rendered by... classification and Micronaire determination results certified on cotton class certificates.) (e) Supervision, by...

12 CFR 1777.20 - Capital classifications.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 7 2011-01-01 2011-01-01 false Capital classifications. 1777.20 Section 1777... DEVELOPMENT SAFETY AND SOUNDNESS PROMPT CORRECTIVE ACTION Capital Classifications and Orders Under Section 1366 of the 1992 Act § 1777.20 Capital classifications. (a) Capital classifications after the effective...

22 CFR 9.8 - Classification challenges.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification, the following shall be indicated in a manner that is immediately apparent: (1) Classification...

28 CFR 345.20 - Position classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 28 Judicial Administration 2 2011-07-01 2011-07-01 false Position classification. 345.20 Section... INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate... the objectives and principles of pay classification as a part of the routine orientation of new FPI...

22 CFR 9.8 - Classification challenges.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Classification challenges. 9.8 Section 9.8 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.8 Classification... classification status is improper are expected and encouraged to challenge the classification status of the...

28 CFR 345.20 - Position classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Position classification. 345.20 Section... INDUSTRIES (FPI) INMATE WORK PROGRAMS Position Classification § 345.20 Position classification. (a) Inmate... the objectives and principles of pay classification as a part of the routine orientation of new FPI...

7 CFR 51.2284 - Size classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Size classification. 51.2284 Section 51.2284... Size classification. The following classifications are provided to describe the size of any lot... shall conform to the requirements of the specified classification as defined below: (a) Halves. Lot...

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Size classifications. 51.2836 Section 51.2836...) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum diameter Inches Millimeters Maximum...

7 CFR 51.2836 - Size classifications.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Size classifications. 51.2836 Section 51.2836...) Size Classifications § 51.2836 Size classifications. The size of onions may be specified in accordance with one of the following classifications. Size designation Minimum diameter Inches Millimeters Maximum...

7 CFR 51.2281 - Color classifications.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Color classifications. 51.2281 Section 51.2281... Color classifications. The following classifications are provided to describe the color of any lot... than the darkest color permitted in the specified classification as shown on the color chart. ...

28 CFR 524.73 - Classification procedures.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 28 Judicial Administration 2 2011-07-01 2011-07-01 false Classification procedures. 524.73 Section..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73 Classification procedures. (a) Initial assignment. Except as provided for in paragraphs (a) (1) through (4) of...

5 CFR 511.701 - Effective dates generally.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Except as provided in § 511.703, classification actions may not be made retroactive. (b) Office of Personnel Management's classification decision. (1) The effective date of a classification decision made by... CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511...

7 CFR 27.69 - Classification review; notations on certificate.

Code of Federal Regulations, 2011 CFR

2011-01-01

... review of classification is made after the issuance of a cotton class certificate, the results of the... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification review; notations on certificate. 27.69... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification...

12 CFR 403.3 - Classification principles and authority.

Code of Federal Regulations, 2011 CFR

2011-01-01

... classification determination is made, each item of information that may require protection shall be identified... its classification. The final determination must be made within thirty (30) days. (b) Classification.... Security Officer. (2) A determination to classify information shall be made by an original classification...

5 CFR 511.701 - Effective dates generally.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) Except as provided in § 511.703, classification actions may not be made retroactive. (b) Office of Personnel Management's classification decision. (1) The effective date of a classification decision made by... CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511...

22 CFR 9.5 - Original classification authority.

Code of Federal Regulations, 2010 CFR

2010-04-01

... classification authority. (a) Authority for original classification of information as Top Secret may be exercised... Notice dated May 26, 2000. (b) Authority for original classification of information as Secret or..., 2000. In the absence of the Secret or Confidential classification authority, the person designated to...

46 CFR 8.260 - Revocation of classification society recognition.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the minimum...

A Computerized English-Spanish Correlation Index to Five Biomedical Library Classification Schemes Based on MeSH*

PubMed Central

Muench, Eugene V.

1971-01-01

A computerized English/Spanish correlation index to five biomedical library classification schemes and a computerized English/Spanish, Spanish/English listings of MeSH are described. The index was accomplished by supplying appropriate classification numbers of five classification schemes (National Library of Medicine; Library of Congress; Dewey Decimal; Cunningham; Boston Medical) to MeSH and a Spanish translation of MeSH The data were keypunched, merged on magnetic tape, and sorted in a computer alphabetically by English and Spanish subject headings and sequentially by classification number. Some benefits and uses of the index are: a complete index to classification schemes based on MeSH terms; a tool for conversion of classification numbers when reclassifying collections; a Spanish index and a crude Spanish translation of five classification schemes; a data base for future applications, e.g., automatic classification. Other classification schemes, such as the UDC, and translations of MeSH into other languages can be added. PMID:5172471

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.

Integration of Chinese medicine with Western medicine could lead to future medicine: molecular module medicine.

PubMed

Zhang, Chi; Zhang, Ge; Chen, Ke-ji; Lu, Ai-ping

2016-04-01

The development of an effective classification method for human health conditions is essential for precise diagnosis and delivery of tailored therapy to individuals. Contemporary classification of disease systems has properties that limit its information content and usability. Chinese medicine pattern classification has been incorporated with disease classification, and this integrated classification method became more precise because of the increased understanding of the molecular mechanisms. However, we are still facing the complexity of diseases and patterns in the classification of health conditions. With continuing advances in omics methodologies and instrumentation, we are proposing a new classification approach: molecular module classification, which is applying molecular modules to classifying human health status. The initiative would be precisely defining the health status, providing accurate diagnoses, optimizing the therapeutics and improving new drug discovery strategy. Therefore, there would be no current disease diagnosis, no disease pattern classification, and in the future, a new medicine based on this classification, molecular module medicine, could redefine health statuses and reshape the clinical practice.

Practice nurse involvement in primary care depression management: an observational cost-effectiveness analysis

PubMed Central

2014-01-01

Background Most evidence on the effect of collaborative care for depression is derived in the selective environment of randomised controlled trials. In collaborative care, practice nurses may act as case managers. The Primary Care Services Improvement Project (PCSIP) aimed to assess the cost-effectiveness of alternative models of practice nurse involvement in a real world Australian setting. Previous analyses have demonstrated the value of high level practice nurse involvement in the management of diabetes and obesity. This paper reports on their value in the management of depression. Methods General practices were assigned to a low or high model of care based on observed levels of practice nurse involvement in clinical-based activities for the management of depression (i.e. percentage of depression patients seen, percentage of consultation time spent on clinical-based activities). Linked, routinely collected data was used to determine patient level depression outcomes (proportion of depression-free days) and health service usage costs. Standardised depression assessment tools were not routinely used, therefore a classification framework to determine the patient’s depressive state was developed using proxy measures (e.g. symptoms, medications, referrals, hospitalisations and suicide attempts). Regression analyses of costs and depression outcomes were conducted, using propensity weighting to control for potential confounders. Results Capacity to determine depressive state using the classification framework was dependent upon the level of detail provided in medical records. While antidepressant medication prescriptions were a strong indicator of depressive state, they could not be relied upon as the sole measure. Propensity score weighted analyses of total depression-related costs and depression outcomes, found that the high level model of care cost more (95% CI: -$314.76 to $584) and resulted in 5% less depression-free days (95% CI: -0.15 to 0.05), compared to the low level model. However, this result was highly uncertain, as shown by the confidence intervals. Conclusions Classification of patients’ depressive state was feasible, but time consuming, using the classification framework proposed. Further validation of the framework is required. Unlike the analyses of diabetes and obesity management, no significant differences in the proportion of depression-free days or health service costs were found between the alternative levels of practice nurse involvement. PMID:24422622

The contribution of the vaccine adverse event text mining system to the classification of possible Guillain-Barré syndrome reports.

PubMed

Botsis, T; Woo, E J; Ball, R

2013-01-01

We previously demonstrated that a general purpose text mining system, the Vaccine adverse event Text Mining (VaeTM) system, could be used to automatically classify reports of an-aphylaxis for post-marketing safety surveillance of vaccines. To evaluate the ability of VaeTM to classify reports to the Vaccine Adverse Event Reporting System (VAERS) of possible Guillain-Barré Syndrome (GBS). We used VaeTM to extract the key diagnostic features from the text of reports in VAERS. Then, we applied the Brighton Collaboration (BC) case definition for GBS, and an information retrieval strategy (i.e. the vector space model) to quantify the specific information that is included in the key features extracted by VaeTM and compared it with the encoded information that is already stored in VAERS as Medical Dictionary for Regulatory Activities (MedDRA) Preferred Terms (PTs). We also evaluated the contribution of the primary (diagnosis and cause of death) and secondary (second level diagnosis and symptoms) diagnostic VaeTM-based features to the total VaeTM-based information. MedDRA captured more information and better supported the classification of reports for GBS than VaeTM (AUC: 0.904 vs. 0.777); the lower performance of VaeTM is likely due to the lack of extraction by VaeTM of specific laboratory results that are included in the BC criteria for GBS. On the other hand, the VaeTM-based classification exhibited greater specificity than the MedDRA-based approach (94.96% vs. 87.65%). Most of the VaeTM-based information was contained in the secondary diagnostic features. For GBS, clinical signs and symptoms alone are not sufficient to match MedDRA coding for purposes of case classification, but are preferred if specificity is the priority.

Incidence of Radiologically Isolated Syndrome: A Population-Based Study.

PubMed

Forslin, Y; Granberg, T; Jumah, A Antwan; Shams, S; Aspelin, P; Kristoffersen-Wiberg, M; Martola, J; Fredrikson, S

2016-06-01

Incidental MR imaging findings resembling MS in asymptomatic individuals, fulfilling the Okuda criteria, are termed "radiologically isolated syndrome." Those with radiologically isolated syndrome are at high risk of their condition converting to MS. The epidemiology of radiologically isolated syndrome remains largely unknown, and there are no population-based studies, to our knowledge. Our aim was to study the population-based incidence of radiologically isolated syndrome in a high-incidence region for MS and to evaluate the effect on radiologically isolated syndrome incidence when revising the original radiologically isolated syndrome criteria by using the latest radiologic classification for dissemination in space. All 2272 brain MR imaging scans in 1907 persons obtained during 2013 in the Swedish county of Västmanland, with a population of 259,000 inhabitants, were blindly evaluated by a senior radiologist and a senior neuroradiologist. The Okuda criteria for radiologically isolated syndrome were applied by using both the Barkhof and Swanton classifications for dissemination in space. Assessments of clinical data were performed by a radiology resident and a senior neurologist. The cumulative incidence of radiologically isolated syndrome was 2 patients (0.1%), equaling an incidence rate of 0.8 cases per 100,000 person-years, in a region with an incidence rate of MS of 10.2 cases per 100,000 person-years. There was no difference in the radiologically isolated syndrome incidence rate when applying a modified version of the Okuda criteria by using the newer Swanton classification for dissemination in space. Radiologically isolated syndrome is uncommon in a high-incidence region for MS. Adapting the Okuda criteria to use the dissemination in space-Swanton classification may be feasible. Future studies on radiologically isolated syndrome may benefit from a collaborative approach to ensure adequate numbers of participants. © 2016 by American Journal of Neuroradiology.

Recommendations for the classification of group A rotaviruses using all 11 genomic RNA segments.

PubMed

Matthijnssens, Jelle; Ciarlet, Max; Rahman, Mustafizur; Attoui, Houssam; Bányai, Krisztián; Estes, Mary K; Gentsch, Jon R; Iturriza-Gómara, Miren; Kirkwood, Carl D; Martella, Vito; Mertens, Peter P C; Nakagomi, Osamu; Patton, John T; Ruggeri, Franco M; Saif, Linda J; Santos, Norma; Steyer, Andrej; Taniguchi, Koki; Desselberger, Ulrich; Van Ranst, Marc

2008-01-01

Recently, a classification system was proposed for rotaviruses in which all the 11 genomic RNA segments are used (Matthijnssens et al. in J Virol 82:3204-3219, 2008). Based on nucleotide identity cut-off percentages, different genotypes were defined for each genome segment. A nomenclature for the comparison of complete rotavirus genomes was considered in which the notations Gx-P[x]-Ix-Rx-Cx-Mx-Ax-Nx-Tx-Ex-Hx are used for the VP7-VP4-VP6-VP1-VP2-VP3-NSP1-NSP2-NSP3-NSP4-NSP5/6 encoding genes, respectively. This classification system is an extension of the previously applied genotype-based system which made use of the rotavirus gene segments encoding VP4, VP7, VP6, and NSP4. In order to assign rotavirus strains to one of the established genotypes or a new genotype, a standard procedure is proposed in this report. As more human and animal rotavirus genomes will be completely sequenced, new genotypes for each of the 11 gene segments may be identified. A Rotavirus Classification Working Group (RCWG) including specialists in molecular virology, infectious diseases, epidemiology, and public health was formed, which can assist in the appropriate delineation of new genotypes, thus avoiding duplications and helping minimize errors. Scientists discovering a potentially new rotavirus genotype for any of the 11 gene segments are invited to send the novel sequence to the RCWG, where the sequence will be analyzed, and a new nomenclature will be advised as appropriate. The RCWG will update the list of classified strains regularly and make this accessible on a website. Close collaboration with the Study Group Reoviridae of the International Committee on the Taxonomy of Viruses will be maintained.

Supervised machine learning and active learning in classification of radiology reports.

PubMed

Nguyen, Dung H M; Patrick, Jon D

2014-01-01

This paper presents an automated system for classifying the results of imaging examinations (CT, MRI, positron emission tomography) into reportable and non-reportable cancer cases. This system is part of an industrial-strength processing pipeline built to extract content from radiology reports for use in the Victorian Cancer Registry. In addition to traditional supervised learning methods such as conditional random fields and support vector machines, active learning (AL) approaches were investigated to optimize training production and further improve classification performance. The project involved two pilot sites in Victoria, Australia (Lake Imaging (Ballarat) and Peter MacCallum Cancer Centre (Melbourne)) and, in collaboration with the NSW Central Registry, one pilot site at Westmead Hospital (Sydney). The reportability classifier performance achieved 98.25% sensitivity and 96.14% specificity on the cancer registry's held-out test set. Up to 92% of training data needed for supervised machine learning can be saved by AL. AL is a promising method for optimizing the supervised training production used in classification of radiology reports. When an AL strategy is applied during the data selection process, the cost of manual classification can be reduced significantly. The most important practical application of the reportability classifier is that it can dramatically reduce human effort in identifying relevant reports from the large imaging pool for further investigation of cancer. The classifier is built on a large real-world dataset and can achieve high performance in filtering relevant reports to support cancer registries. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Application of the Coastal and Marine Ecological Classification Standard to ROV Video Data for Enhanced Analysis of Deep-Sea Habitats in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Ruby, C.; Skarke, A. D.; Mesick, S.

2016-02-01

The Coastal and Marine Ecological Classification Standard (CMECS) is a network of common nomenclature that provides a comprehensive framework for organizing physical, biological, and chemical information about marine ecosystems. It was developed by the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center, in collaboration with other feral agencies and academic institutions, as a means for scientists to more easily access, compare, and integrate marine environmental data from a wide range of sources and time frames. CMECS has been endorsed by the Federal Geographic Data Committee (FGDC) as a national metadata standard. The research presented here is focused on the application of CMECS to deep-sea video and environmental data collected by the NOAA ROV Deep Discoverer and the NOAA Ship Okeanos Explorer in the Gulf of Mexico in 2011-2014. Specifically, a spatiotemporal index of the physical, chemical, biological, and geological features observed in ROV video records was developed in order to allow scientist, otherwise unfamiliar with the specific content of existing video data, to rapidly determine the abundance and distribution of features of interest, and thus evaluate the applicability of those video data to their research. CMECS units (setting, component, or modifier) for seafloor images extracted from high-definition ROV video data were established based upon visual assessment as well as analysis of coincident environmental sensor (temperature, conductivity), navigation (ROV position, depth, attitude), and log (narrative dive summary) data. The resulting classification units were integrated into easily searchable textual and geo-databases as well as an interactive web map. The spatial distribution and associations of deep-sea habitats as indicated by CMECS classifications are described and optimized methodological approaches for application of CMECS to deep-sea video and environmental data are presented.

Polyphasic taxonomy, a consensus approach to bacterial systematics.

PubMed Central

Vandamme, P; Pot, B; Gillis, M; de Vos, P; Kersters, K; Swings, J

1996-01-01

Over the last 25 years, a much broader range of taxonomic studies of bacteria has gradually replaced the former reliance upon morphological, physiological, and biochemical characterization. This polyphasic taxonomy takes into account all available phenotypic and genotypic data and integrates them in a consensus type of classification, framed in a general phylogeny derived from 16S rRNA sequence analysis. In some cases, the consensus classification is a compromise containing a minimum of contradictions. It is thought that the more parameters that will become available in the future, the more polyphasic classification will gain stability. In this review, the practice of polyphasic taxonomy is discussed for four groups of bacteria chosen for their relevance, complexity, or both: the genera Xanthomonas and Campylobacter, the lactic acid bacteria, and the family Comamonadaceae. An evaluation of our present insights, the conclusions derived from it, and the perspectives of polyphasic taxonomy are discussed, emphasizing the keystone role of the species. Taxonomists did not succeed in standardizing species delimitation by using percent DNA hybridization values. Together with the absence of another "gold standard" for species definition, this has an enormous repercussion on bacterial taxonomy. This problem is faced in polyphasic taxonomy, which does not depend on a theory, a hypothesis, or a set of rules, presenting a pragmatic approach to a consensus type of taxonomy, integrating all available data maximally. In the future, polyphasic taxonomy will have to cope with (i) enormous amounts of data, (ii) large numbers of strains, and (iii) data fusion (data aggregation), which will demand efficient and centralized data storage. In the future, taxonomic studies will require collaborative efforts by specialized laboratories even more than now is the case. Whether these future developments will guarantee a more stable consensus classification remains an open question. PMID:8801440

Unmanned Tactical Autonomous Control and Collaboration Threat and Vulnerability Assessment

DTIC Science & Technology

2015-06-01

they are evaluated separately 15 from each other [19]. One major difference between this classification method and the FIPS 199 is that no...both technical and nontechnical methods ” [31]. These different methods will enable the UTACC system to effectively mitigate vulnerabilities that...team. Marines on the battlefield communicate with each other in many different and unique methods . UTACC must be adaptable to these different methods

Applied Neuroscience at the AFRL 711th Human Performance Wing

DTIC Science & Technology

2010-09-01

Support teaming and collaboration research performed by RHCPT 25 History of Applied Neuroscience Research First EEG studies of workload at AFRL...First to classify mental workload based on integrated EEG /ECG 26 First successful real- time workload classification Measured EEG workload in...complex tasks Closed-loop adaptive aiding based on EEG /ECG History of Applied Neuroscience Research 27 Current Applied Neuroscience Research • Mix of in

Wireless Emergency Alerts (WEA) Cybersecurity Risk Management Strategy for Alert Originators

DTIC Science & Technology

2014-03-01

formerly known as the Commercial Mobile Alert Service ( CMAS ) RDT&E program, is a collaborative partnership that includes the cellular industry, the...Examples illustrate a STRIDE analysis of the generic mission 1 The CMAS Alerting Pipeline Taxonomy describes in detail a hierarchical classification...SEI-2013-SR-018 | 1 1 Introduction The Wireless Emergency Alerts (WEA) service, formerly known as the Commercial Mobile Alert Service ( CMAS ), is a

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 5 2014-04-01 2014-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 5 2012-04-01 2012-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 5 2013-04-01 2013-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

24 CFR 3285.202 - Soil classifications and bearing capacity.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 5 2011-04-01 2011-04-01 false Soil classifications and bearing... Soil classifications and bearing capacity. The soil classification and bearing capacity of the soil must be determined before the foundation is constructed and anchored. The soil classification and...

43 CFR 2450.4 - Protests: Initial classification decision.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Protests: Initial classification decision... CLASSIFICATION SYSTEM Petition-Application Procedures § 2450.4 Protests: Initial classification decision. (a) For a period of 30 days after the proposed classification decision has been served upon the parties...

46 CFR 8.330 - Termination of classification society authority.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Termination of classification society authority. 8.330... classification society authority. (a) The Coast Guard may terminate an authorization agreement with a classification society if: (1) The Commandant revokes the classification society's recognition, as specified in...

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...

49 CFR 173.53 - Provisions for using old classifications of explosives.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Provisions for using old classifications of... SHIPPERS-GENERAL REQUIREMENTS FOR SHIPMENTS AND PACKAGINGS Definitions, Classification and Packaging for Class 1 § 173.53 Provisions for using old classifications of explosives. Where the classification system...

7 CFR 51.3198 - Size classifications.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Size classifications. 51.3198 Section 51.3198... Onions Size Classifications § 51.3198 Size classifications. Size shall be specified in connection with... certain size or larger, or in accordance with one of the size classifications listed below: Provided, that...

32 CFR 2700.22 - Classification guides.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Classification guides. 2700.22 Section 2700.22... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall issue classification guides pursuant to section 2-2 of E.O. 12065. These guides, which shall be used to...

32 CFR 2001.10 - Classification standards.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Classification standards. 2001.10 Section 2001... Classification § 2001.10 Classification standards. Identifying or describing damage to the national security. Section 1.1(a) of the Order specifies the conditions that must be met when making classification decisions...

32 CFR 2001.10 - Classification standards.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Classification standards. 2001.10 Section 2001... Classification § 2001.10 Classification standards. Identifying or describing damage to the national security. Section 1.1(a) of the Order specifies the conditions that must be met when making classification decisions...

7 CFR 51.1860 - Color classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Color classification. 51.1860 Section 51.1860... STANDARDS) United States Standards for Fresh Tomatoes 1 Color Classification § 51.1860 Color classification... illustrating the color classification requirements, as set forth in this section. This visual aid may be...

32 CFR 2700.22 - Classification guides.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Classification guides. 2700.22 Section 2700.22... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall issue classification guides pursuant to section 2-2 of E.O. 12065. These guides, which shall be used to...

32 CFR 2700.22 - Classification guides.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Classification guides. 2700.22 Section 2700.22... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall issue classification guides pursuant to section 2-2 of E.O. 12065. These guides, which shall be used to...

32 CFR 2001.10 - Classification standards.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Classification standards. 2001.10 Section 2001... Classification § 2001.10 Classification standards. Identifying or describing damage to the national security. Section 1.1(a) of the Order specifies the conditions that must be met when making classification decisions...

7 CFR 51.3198 - Size classifications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Size classifications. 51.3198 Section 51.3198... Onions Size Classifications § 51.3198 Size classifications. Size shall be specified in connection with... certain size or larger, or in accordance with one of the size classifications listed below: Provided, that...

7 CFR 51.1436 - Color classifications.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Color classifications. 51.1436 Section 51.1436... STANDARDS) United States Standards for Grades of Shelled Pecans Color Classifications § 51.1436 Color classifications. (a) The skin color of pecan kernels may be described in terms of the color classifications...

7 CFR 28.179 - Methods of cotton classification and comparison.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Methods of cotton classification and comparison. 28... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.179 Methods of cotton classification and comparison. The classification of samples from...

7 CFR 27.31 - Classification of Cotton.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Classification of Cotton. 27.31 Section 27.31... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.31 Classification of Cotton. For the purposes of subsection 15b (f) of the Act...

7 CFR 28.179 - Methods of cotton classification and comparison.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Methods of cotton classification and comparison. 28... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.179 Methods of cotton classification and comparison. The classification of samples from...

7 CFR 28.180 - Issuance of cotton classification memoranda.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Issuance of cotton classification memoranda. 28.180... CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.180 Issuance of cotton classification memoranda. As soon as practicable after the classification or...

7 CFR 27.31 - Classification of Cotton.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification of Cotton. 27.31 Section 27.31... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.31 Classification of Cotton. For the purposes of subsection 15b (f) of the Act...

7 CFR 28.179 - Methods of cotton classification and comparison.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Methods of cotton classification and comparison. 28... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.179 Methods of cotton classification and comparison. The classification of samples from...

7 CFR 28.179 - Methods of cotton classification and comparison.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Methods of cotton classification and comparison. 28... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.179 Methods of cotton classification and comparison. The classification of samples from...

7 CFR 28.179 - Methods of cotton classification and comparison.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Methods of cotton classification and comparison. 28... STANDARD CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.179 Methods of cotton classification and comparison. The classification of samples from...

7 CFR 28.180 - Issuance of cotton classification memoranda.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Issuance of cotton classification memoranda. 28.180... CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.180 Issuance of cotton classification memoranda. As soon as practicable after the classification or...

7 CFR 28.180 - Issuance of cotton classification memoranda.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Issuance of cotton classification memoranda. 28.180... CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.180 Issuance of cotton classification memoranda. As soon as practicable after the classification or...

7 CFR 28.180 - Issuance of cotton classification memoranda.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Issuance of cotton classification memoranda. 28.180... CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.180 Issuance of cotton classification memoranda. As soon as practicable after the classification or...

7 CFR 27.31 - Classification of Cotton.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification of Cotton. 27.31 Section 27.31... REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.31 Classification of Cotton. For the purposes of subsection 15b (f) of the Act...

7 CFR 28.180 - Issuance of cotton classification memoranda.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Issuance of cotton classification memoranda. 28.180... CONTAINER REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.180 Issuance of cotton classification memoranda. As soon as practicable after the classification or...

32 CFR 2001.10 - Classification standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Classification standards. 2001.10 Section 2001... Classification § 2001.10 Classification standards. Identifying or describing damage to the national security. Section 1.1(a) of the Order specifies the conditions that must be met when making classification decisions...

7 CFR 51.1436 - Color classifications.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Color classifications. 51.1436 Section 51.1436... STANDARDS) United States Standards for Grades of Shelled Pecans Color Classifications § 51.1436 Color classifications. (a) The skin color of pecan kernels may be described in terms of the color classifications...

32 CFR 2700.22 - Classification guides.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Classification guides. 2700.22 Section 2700.22... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall issue classification guides pursuant to section 2-2 of E.O. 12065. These guides, which shall be used to...

A Systematic Approach to Subgroup Classification in Intellectual Disability

ERIC Educational Resources Information Center

Schalock, Robert L.; Luckasson, Ruth

2015-01-01

This article describes a systematic approach to subgroup classification based on a classification framework and sequential steps involved in the subgrouping process. The sequential steps are stating the purpose of the classification, identifying the classification elements, using relevant information, and using clearly stated and purposeful…

32 CFR 2001.10 - Classification standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Classification standards. 2001.10 Section 2001... Classification § 2001.10 Classification standards. Identifying or describing damage to the national security. Section 1.1(a) of the Order specifies the conditions that must be met when making classification decisions...

5 CFR 511.602 - Notification of classification decision.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Notification of classification decision... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.602 Notification of classification decision. An employee whose position is reclassified to a lower grade which is based in whole or...

5 CFR 511.602 - Notification of classification decision.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Notification of classification decision... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Classification Appeals § 511.602 Notification of classification decision. An employee whose position is reclassified to a lower grade which is based in whole or...

9 CFR 146.7 - Terminology and classification; general.

Code of Federal Regulations, 2011 CFR

2011-01-01

... General Provisions § 146.7 Terminology and classification; general. The official classification terms defined in §§ 146.8 and 146.9 and the various designs illustrative of the official classifications... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Terminology and classification...

7 CFR 27.38 - Terms defined for purposes of classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Terms defined for purposes of classification. 27.38... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.38 Terms defined for purposes of classification. For the purposes of...

7 CFR 27.38 - Terms defined for purposes of classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Terms defined for purposes of classification. 27.38... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification and Micronaire Determinations § 27.38 Terms defined for purposes of classification. For the purposes of...

46 CFR 8.330 - Termination of classification society authority.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Termination of classification society authority. 8.330... classification society authority. (a) The Coast Guard may terminate an authorization agreement with a classification society if: (1) The Commandant revokes the classification society's recognition, as specified in...

7 CFR 51.1436 - Color classifications.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Color classifications. 51.1436 Section 51.1436... STANDARDS) United States Standards for Grades of Shelled Pecans Color Classifications § 51.1436 Color classifications. (a) The skin color of pecan kernels may be described in terms of the color classifications...

22 CFR 9.5 - Original classification authority.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., 2000. In the absence of the Secret or Confidential classification authority, the person designated to... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Original classification authority. 9.5 Section... classification authority. (a) Authority for original classification of information as Top Secret may be exercised...

22 CFR 9.5 - Original classification authority.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., 2000. In the absence of the Secret or Confidential classification authority, the person designated to... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Original classification authority. 9.5 Section... classification authority. (a) Authority for original classification of information as Top Secret may be exercised...

22 CFR 9.5 - Original classification authority.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., 2000. In the absence of the Secret or Confidential classification authority, the person designated to... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Original classification authority. 9.5 Section... classification authority. (a) Authority for original classification of information as Top Secret may be exercised...

Generating highly accurate prediction hypotheses through collaborative ensemble learning

NASA Astrophysics Data System (ADS)

Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco

2017-03-01

Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.

International Classification of Functioning, Disability and Health: Catalyst for interprofessional education and collaborative practice.

PubMed

Snyman, Stefanus; Von Pressentin, Klaus B; Clarke, Marina

2015-01-01

Patient-centred and community-based care is required for promotion of health equity. To enhance patient-centred interprofessional care, the World Health Organization recommends using the framework of the International Classification of Functioning, Disability and Health (ICF). Stellenbosch University's Interprofessional Education and Collaborative Practice (IPECP) strategy has promoted using ICF since 2010. Undergraduate medical students on rural clinical placements are expected to use ICF in approaching and managing patients. Students' ability to develop interprofessional care plans using ICF is assessed by a team of preceptors representing various health professions. This study explored the experiences of medical students and their preceptors using ICF in IPECP, and how patients perceived care received. Associative Group Analysis methodology was used to collect data for this study. In total, 68 study participants were enrolled of which 37 were medical students, 16 preceptors and 15 patients. Students found ICF enabled a patient-centred approach and reinforce the importance of context. Patients felt listened to and cared for. Preceptors, obliged to use ICF, came to appreciate the advantages of interprofessional care, promoting mutually beneficial teamwork and job satisfaction. The value of integrating IPECP as an authentic learning experience was demonstrated as was ICF as a catalyst in pushing boundaries for change.

32 CFR 2700.22 - Classification guides.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall... direct derivative classification, shall identify the information to be protected in specific and uniform...

46 CFR 30.10-57 - Recognized classification society-TB/ALL.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Recognized classification society-TB/ALL. 30.10-57... Definitions § 30.10-57 Recognized classification society—TB/ALL. The term recognized classification society means the American Bureau of Shipping or other classification society recognized by the Commandant. ...

43 CFR 2430.5 - Additional criteria for classification of lands valuable for residential, commercial...

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Additional criteria for classification of..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) DISPOSAL CLASSIFICATIONS Criteria for Disposal Classifications § 2430.5 Additional criteria for classification of lands valuable for residential, commercial...

43 CFR 2462.1 - Publication of notice of, and public hearings on, proposed classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... hearings on, proposed classification. 2462.1 Section 2462.1 Public Lands: Interior Regulations Relating to... (2000) BUREAU INITIATED CLASSIFICATION SYSTEM Disposal Classification Procedure: Over 2,560 Acres § 2462.1 Publication of notice of, and public hearings on, proposed classification. The authorized officer...

46 CFR 8.220 - Recognition of a classification society.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive statutory...

43 CFR 2410.1 - All classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false All classifications. 2410.1 Section 2410.1..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) CRITERIA FOR ALL LAND CLASSIFICATIONS General Criteria § 2410.1 All classifications. All classifications under the regulations of this part will give due...

43 CFR 2462.2 - Publication of notice of classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Publication of notice of classification... CLASSIFICATION SYSTEM Disposal Classification Procedure: Over 2,560 Acres § 2462.2 Publication of notice of classification. After having considered the comments received as the result of publication, the authorized...

43 CFR 2410.1 - All classifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 43 Public Lands: Interior 2 2012-10-01 2012-10-01 false All classifications. 2410.1 Section 2410.1..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) CRITERIA FOR ALL LAND CLASSIFICATIONS General Criteria § 2410.1 All classifications. All classifications under the regulations of this part will give due...

43 CFR 2410.1 - All classifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 43 Public Lands: Interior 2 2013-10-01 2013-10-01 false All classifications. 2410.1 Section 2410.1..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) CRITERIA FOR ALL LAND CLASSIFICATIONS General Criteria § 2410.1 All classifications. All classifications under the regulations of this part will give due...

7 CFR 51.1402 - Size classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Size classification. 51.1402 Section 51.1402... Classification § 51.1402 Size classification. Size of pecans may be specified in connection with the grade in accordance with one of the following classifications. To meet the requirements for any one of these...

7 CFR 51.1402 - Size classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Size classification. 51.1402 Section 51.1402... Classification § 51.1402 Size classification. Size of pecans may be specified in connection with the grade in accordance with one of the following classifications. To meet the requirements for any one of these...

7 CFR 51.1436 - Color classifications.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Color classifications. 51.1436 Section 51.1436... Classifications § 51.1436 Color classifications. (a) The skin color of pecan kernels may be described in terms of the color classifications provided in this section. When the color of kernels in a lot generally...

7 CFR 51.1436 - Color classifications.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Color classifications. 51.1436 Section 51.1436... Classifications § 51.1436 Color classifications. (a) The skin color of pecan kernels may be described in terms of the color classifications provided in this section. When the color of kernels in a lot generally...

43 CFR 2410.1 - All classifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 43 Public Lands: Interior 2 2014-10-01 2014-10-01 false All classifications. 2410.1 Section 2410.1..., DEPARTMENT OF THE INTERIOR LAND RESOURCE MANAGEMENT (2000) CRITERIA FOR ALL LAND CLASSIFICATIONS General Criteria § 2410.1 All classifications. All classifications under the regulations of this part will give due...

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,…

7 CFR 28.40 - Terms defined; cotton classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Terms defined; cotton classification. 28.40 Section 28... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Regulations Under the United States Cotton Standards Act Classification § 28.40 Terms defined; cotton classification. For the purposes of classification of any cotton or...

7 CFR 28.40 - Terms defined; cotton classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Terms defined; cotton classification. 28.40 Section 28... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Regulations Under the United States Cotton Standards Act Classification § 28.40 Terms defined; cotton classification. For the purposes of classification of any cotton or...

7 CFR 28.181 - Review of cotton classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Review of cotton classification. 28.181 Section 28.181... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.181 Review of cotton classification. A review of any classification or comparison made pursuant to this subpart...

7 CFR 28.40 - Terms defined; cotton classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Terms defined; cotton classification. 28.40 Section 28... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Regulations Under the United States Cotton Standards Act Classification § 28.40 Terms defined; cotton classification. For the purposes of classification of any cotton or...

7 CFR 28.181 - Review of cotton classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Review of cotton classification. 28.181 Section 28.181... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.181 Review of cotton classification. A review of any classification or comparison made pursuant to this subpart...

7 CFR 28.40 - Terms defined; cotton classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Terms defined; cotton classification. 28.40 Section 28... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Regulations Under the United States Cotton Standards Act Classification § 28.40 Terms defined; cotton classification. For the purposes of classification of any cotton or...

7 CFR 28.181 - Review of cotton classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Review of cotton classification. 28.181 Section 28.181... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.181 Review of cotton classification. A review of any classification or comparison made pursuant to this subpart...

7 CFR 28.181 - Review of cotton classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Review of cotton classification. 28.181 Section 28.181... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.181 Review of cotton classification. A review of any classification or comparison made pursuant to this subpart...

7 CFR 28.40 - Terms defined; cotton classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Terms defined; cotton classification. 28.40 Section 28... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Regulations Under the United States Cotton Standards Act Classification § 28.40 Terms defined; cotton classification. For the purposes of classification of any cotton or...

7 CFR 28.181 - Review of cotton classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Review of cotton classification. 28.181 Section 28.181... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Classification for Foreign Growth Cotton § 28.181 Review of cotton classification. A review of any classification or comparison made pursuant to this subpart...

28 CFR 524.76 - Appeals of CIM classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Appeals of CIM classification. 524.76..., CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.76 Appeals of CIM classification. An inmate may at any time appeal (through the Administrative Remedy Program) the...

77 FR 37879 - Cooperative Patent Classification External User Day

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-25

... Classification External User Day AGENCY: United States Patent and Trademark Office, Commerce. ACTION: Notice... Classification (CPC) External User Day event at its Alexandria Campus. CPC is a partnership between the USPTO and... classification system that will incorporate the best classification practices of the two Offices. This CPC event...

5 CFR 511.702 - Agency or Office classification appeal decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Agency or Office classification appeal... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511.702 Agency or Office classification appeal decisions. (a) Subject to § 511.703, the...

5 CFR 511.702 - Agency or Office classification appeal decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 1 2011-01-01 2011-01-01 false Agency or Office classification appeal... REGULATIONS CLASSIFICATION UNDER THE GENERAL SCHEDULE Effective Dates of Position Classification Actions or Decisions § 511.702 Agency or Office classification appeal decisions. (a) Subject to § 511.703, the...

20 CFR 410.418 - Irrebuttable presumption of total disability due to pneumoconiosis.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Classification of Radiographs of Pneumoconioses, 1971, or (2) The International Classification of the Radiographs of the Pneumoconioses of the International Labour Office, Extended Classification (1968) (which may be referred to as the “ILO Classification (1968)”), or (3) The Classification of the Pneumoconiosis...

46 CFR 8.220 - Recognition of a classification society.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive statutory...

46 CFR 30.10-57 - Recognized classification society-TB/ALL.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Recognized classification society-TB/ALL. 30.10-57... Definitions § 30.10-57 Recognized classification society—TB/ALL. The term recognized classification society means the American Bureau of Shipping or other classification society recognized by the Commandant. ...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

7 CFR 30.31 - Classification of leaf tobacco.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Classification of leaf tobacco. 30.31 Section 30.31... REGULATIONS TOBACCO STOCKS AND STANDARDS Classification of Leaf Tobacco Covering Classes, Types and Groups of Grades § 30.31 Classification of leaf tobacco. For the purpose of this classification leaf tobacco shall...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 1648.6 - Registrants transferred for classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Registrants transferred for classification. 1648... SYSTEM CLASSIFICATION BY LOCAL BOARD § 1648.6 Registrants transferred for classification. (a) Before a..., be transferred for classification to a local board nearer to his current address than is the local...

32 CFR 2700.12 - Criteria for and level of original classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... classification are authorized—“Top Secret,” “Secret,” “Confidential.” No other classification designation is... classification. 2700.12 Section 2700.12 National Defense Other Regulations Relating to National Defense OFFICE FOR MICRONESIAN STATUS NEGOTIATIONS SECURITY INFORMATION REGULATIONS Original Classification § 2700.12...

6 CFR 7.24 - Duration of classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 6 Domestic Security 1 2013-01-01 2013-01-01 false Duration of classification. 7.24 Section 7.24... INFORMATION Classified Information § 7.24 Duration of classification. (a) At the time of original classification, original classification authorities shall apply a date or event in which the information will be...

6 CFR 7.24 - Duration of classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 6 Domestic Security 1 2014-01-01 2014-01-01 false Duration of classification. 7.24 Section 7.24... INFORMATION Classified Information § 7.24 Duration of classification. (a) At the time of original classification, original classification authorities shall apply a date or event in which the information will be...

10 CFR 1016.32 - Classification and preparation of documents.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 10 Energy 4 2013-01-01 2013-01-01 false Classification and preparation of documents. 1016.32... of Information § 1016.32 Classification and preparation of documents. (a) Classification. Restricted... he is not positive is not within that definition and CG-UF-3 does not provide positive classification...

10 CFR 1016.32 - Classification and preparation of documents.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 10 Energy 4 2014-01-01 2014-01-01 false Classification and preparation of documents. 1016.32... of Information § 1016.32 Classification and preparation of documents. (a) Classification. Restricted... he is not positive is not within that definition and CG-UF-3 does not provide positive classification...

32 CFR 2700.12 - Criteria for and level of original classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... classification are authorized—“Top Secret,” “Secret,” “Confidential.” No other classification designation is... classification. 2700.12 Section 2700.12 National Defense Other Regulations Relating to National Defense OFFICE FOR MICRONESIAN STATUS NEGOTIATIONS SECURITY INFORMATION REGULATIONS Original Classification § 2700.12...

10 CFR 1016.32 - Classification and preparation of documents.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 10 Energy 4 2012-01-01 2012-01-01 false Classification and preparation of documents. 1016.32... of Information § 1016.32 Classification and preparation of documents. (a) Classification. Restricted... he is not positive is not within that definition and CG-UF-3 does not provide positive classification...

6 CFR 7.24 - Duration of classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 6 Domestic Security 1 2012-01-01 2012-01-01 false Duration of classification. 7.24 Section 7.24... INFORMATION Classified Information § 7.24 Duration of classification. (a) At the time of original classification, original classification authorities shall apply a date or event in which the information will be...

6 CFR 7.24 - Duration of classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 6 Domestic Security 1 2011-01-01 2011-01-01 false Duration of classification. 7.24 Section 7.24... INFORMATION Classified Information § 7.24 Duration of classification. (a) At the time of original classification, original classification authorities shall apply a date or event in which the information will be...

32 CFR 2700.12 - Criteria for and level of original classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... classification are authorized—“Top Secret,” “Secret,” “Confidential.” No other classification designation is... classification. 2700.12 Section 2700.12 National Defense Other Regulations Relating to National Defense OFFICE FOR MICRONESIAN STATUS NEGOTIATIONS SECURITY INFORMATION REGULATIONS Original Classification § 2700.12...

The search for structure - Object classification in large data sets. [for astronomers

NASA Technical Reports Server (NTRS)

Kurtz, Michael J.

1988-01-01

Research concerning object classifications schemes are reviewed, focusing on large data sets. Classification techniques are discussed, including syntactic, decision theoretic methods, fuzzy techniques, and stochastic and fuzzy grammars. Consideration is given to the automation of MK classification (Morgan and Keenan, 1973) and other problems associated with the classification of spectra. In addition, the classification of galaxies is examined, including the problems of systematic errors, blended objects, galaxy types, and galaxy clusters.

Classification, disease, and diagnosis.

PubMed

Jutel, Annemarie

2011-01-01

Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

NASA Astrophysics Data System (ADS)

Jürgens, Björn; Herrero-Solana, Victor

2017-04-01

Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory.

PubMed

Gradishar, William; Johnson, KariAnne; Brown, Krystal; Mundt, Erin; Manley, Susan

2017-07-01

There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, the well-documented limitations of these databases call into question how often clinicians will encounter discordant variant classifications that may introduce uncertainty into patient management. Here, we evaluate discordance in BRCA1 and BRCA2 variant classifications between a single commercial testing laboratory and a public database commonly consulted in clinical practice. BRCA1 and BRCA2 variant classifications were obtained from ClinVar and compared with the classifications from a reference laboratory. Full concordance and discordance were determined for variants whose ClinVar entries were of the same pathogenicity (pathogenic, benign, or uncertain). Variants with conflicting ClinVar classifications were considered partially concordant if ≥1 of the listed classifications agreed with the reference laboratory classification. Four thousand two hundred and fifty unique BRCA1 and BRCA2 variants were available for analysis. Overall, 73.2% of classifications were fully concordant and 12.3% were partially concordant. The remaining 14.5% of variants had discordant classifications, most of which had a definitive classification (pathogenic or benign) from the reference laboratory compared with an uncertain classification in ClinVar (14.0%). Here, we show that discrepant classifications between a public database and single reference laboratory potentially account for 26.7% of variants in BRCA1 and BRCA2 . The time and expertise required of clinicians to research these discordant classifications call into question the practicality of checking all test results against a database and suggest that discordant classifications should be interpreted with these limitations in mind. With the increasing use of clinical genetic testing for hereditary cancer risk, accurate variant classification is vital to ensuring appropriate medical management. There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, we show that up to 26.7% of variants in BRCA1 and BRCA2 have discordant classifications between ClinVar and a reference laboratory. The findings presented in this paper serve as a note of caution regarding the utility of database consultation. © AlphaMed Press 2017.

Some new classification methods for hyperspectral remote sensing

NASA Astrophysics Data System (ADS)

Du, Pei-jun; Chen, Yun-hao; Jones, Simon; Ferwerda, Jelle G.; Chen, Zhi-jun; Zhang, Hua-peng; Tan, Kun; Yin, Zuo-xia

2006-10-01

Hyperspectral Remote Sensing (HRS) is one of the most significant recent achievements of Earth Observation Technology. Classification is the most commonly employed processing methodology. In this paper three new hyperspectral RS image classification methods are analyzed. These methods are: Object-oriented FIRS image classification, HRS image classification based on information fusion and HSRS image classification by Back Propagation Neural Network (BPNN). OMIS FIRS image is used as the example data. Object-oriented techniques have gained popularity for RS image classification in recent years. In such method, image segmentation is used to extract the regions from the pixel information based on homogeneity criteria at first, and spectral parameters like mean vector, texture, NDVI and spatial/shape parameters like aspect ratio, convexity, solidity, roundness and orientation for each region are calculated, finally classification of the image using the region feature vectors and also using suitable classifiers such as artificial neural network (ANN). It proves that object-oriented methods can improve classification accuracy since they utilize information and features both from the point and the neighborhood, and the processing unit is a polygon (in which all pixels are homogeneous and belong to the class). HRS image classification based on information fusion, divides all bands of the image into different groups initially, and extracts features from every group according to the properties of each group. Three levels of information fusion: data level fusion, feature level fusion and decision level fusion are used to HRS image classification. Artificial Neural Network (ANN) can perform well in RS image classification. In order to promote the advances of ANN used for HIRS image classification, Back Propagation Neural Network (BPNN), the most commonly used neural network, is used to HRS image classification.

Comparison of staging diagnosis by two magnifying endoscopy classification for superficial oesophageal cancer.

PubMed

Ebi, Masahide; Shimura, Takaya; Murakami, Kenji; Yamada, Tomonori; Hirata, Yoshikazu; Tsukamoto, Hironobu; Mizoshita, Tsutomu; Tanida, Satoshi; Kataoka, Hiromi; Kamiya, Takeshi; Joh, Takashi

2012-11-01

Due to the possibility of lymph node metastasis, surgical resection is indicated for superficial oesophageal cancer with invasion to a depth greater than the muscularis mucosa. Although two magnifying endoscopy classifications are currently used to diagnose the depth of invasion, which classification is more suitable remains controversial. To compare and evaluate the clinical outcomes of two classifications for superficial oesophageal squamous cell carcinoma. This cross-sectional study consists of 44 superficial oesophageal squamous cell carcinoma lesions with magnification image-enhanced endoscopy images. Only magnifying endoscopic images were displayed to two experienced endoscopists who independently diagnosed the depth of invasion according to both classifications. The sensitivity of invasion greater than the muscularis mucosa tended to be higher in Inoue's classification than Arima's classification (78.3±6.2% vs. 50.0±3.0%; P=0.144), whereas the specificity was significantly lower in Inoue's classification than in Arima's classification (61.9±0.0% vs. 97.6±3.4%; P=0.043). For both classifications, rates of concordance were 90.9% and 84.4%, and κ statistics were 0.81 and 0.66, respectively. Our results suggest that Arima's classification is suitable for general screening before treatment to avoid unnecessary surgery. Inoue's classification is appropriate for assessing wide lesion. Copyright © 2012 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Clinical, aetiological, anatomical and pathological classification (CEAP): gold standard and limits.

PubMed

Rabe, E; Pannier, F

2012-03-01

The first CEAP (clinical, aetiological, anatomical and pathological elements) consensus document was published after a consensus conference of the American Venous Forum, held at the sixth annual meeting of the AVF in February 1994 in Maui, Hawaii. In the following years the CEAP classification was published in many international journals and books which has led to widespread international use of the CEAP classification since 1995. The aim of this paper is to review the benefits and limits of CEAP from the available literature. In an actual Medline analysis with the keywords 'CEAP' and 'venous insufficiency', 266 publications using the CEAP classification in venous diseases are available. The CEAP classification was accepted in the venous community and used in scientific publications, but in most of the cases only the clinical classification was used. Limitations of the first version including a lack of clear definition of clinical signs led to a revised version. The CEAP classification is the gold standard of classification of chronic venous disorders today. Nevertheless for proper use some facts have to be taken into account: the CEAP classification is not a severity classification, C2 summarizes all kinds of varicose veins, in C3 it may be difficult to separate venous and other reasons for oedema, and corona phlebectatica is not included in the classification. Further revisions of the CEAP classification may help to overcome the still-existing deficits.

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.

42 CFR 412.517 - Revision of LTC-DRG group classifications and weighting factors.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Revision of LTC-DRG group classifications and... classifications and weighting factors. (a) CMS adjusts the classifications and weighting factors annually to... the LTC-DRG classifications and recalibration of the weighting factors described in paragraph (a) of...

43 CFR 2430.3 - Additional criteria for classification of lands needed for urban or suburban purposes.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Additional criteria for classification of... MANAGEMENT (2000) DISPOSAL CLASSIFICATIONS Criteria for Disposal Classifications § 2430.3 Additional criteria for classification of lands needed for urban or suburban purposes. (a) To be needed for urban or...

43 CFR 2430.4 - Additional criteria for classification of lands valuable for public purposes.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 2 2011-10-01 2011-10-01 false Additional criteria for classification of... (2000) DISPOSAL CLASSIFICATIONS Criteria for Disposal Classifications § 2430.4 Additional criteria for classification of lands valuable for public purposes. (a) To be valuable for public purposes, lands must be...

42 CFR 412.517 - Revision of LTC-DRG group classifications and weighting factors.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Revision of LTC-DRG group classifications and... classifications and weighting factors. (a) CMS adjusts the classifications and weighting factors annually to... the LTC-DRG classifications and recalibration of the weighting factors described in paragraph (a) of...

29 CFR 14.3 - DOL Classification Review Committee.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 1 2014-07-01 2013-07-01 true DOL Classification Review Committee. 14.3 Section 14.3 Labor... Classification Review Committee. A DOL Classification Review Committee is hereby established. (a) Composition of... under the Freedom of Information Act, 5 U.S.C. 552, when a proposed denial is based on classification...

ASIST SIG/CR Classification Workshop 2000: Classification for User Support and Learning.

ERIC Educational Resources Information Center

Soergel, Dagobert

2001-01-01

Reports on papers presented at the 62nd Annual Meeting of ASIST (American Society for Information Science and Technology) for the Special Interest Group in Classification Research (SIG/CR). Topics include types of knowledge; developing user-oriented classifications, including domain analysis; classification in the user interface; and automatic…

7 CFR 27.12 - Classification request for each lot of cotton.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Classification request for each lot of cotton. 27.12... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.12 Classification request for each lot of cotton. For each lot or mark of cotton of which the...

7 CFR 27.12 - Classification request for each lot of cotton.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Classification request for each lot of cotton. 27.12... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.12 Classification request for each lot of cotton. For each lot or mark of cotton of which the...

7 CFR 27.12 - Classification request for each lot of cotton.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Classification request for each lot of cotton. 27.12... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.12 Classification request for each lot of cotton. For each lot or mark of cotton of which the...

7 CFR 27.12 - Classification request for each lot of cotton.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Classification request for each lot of cotton. 27.12... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.12 Classification request for each lot of cotton. For each lot or mark of cotton of which the...

7 CFR 27.12 - Classification request for each lot of cotton.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Classification request for each lot of cotton. 27.12... CONTAINER REGULATIONS COTTON CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Requests § 27.12 Classification request for each lot of cotton. For each lot or mark of cotton of which the...

Basis of Criminalistic Classification of a Person in Republic Kazakhstan and Republic Mongolia

ERIC Educational Resources Information Center

Abdilov, Kanat S.; Zusbaev, Baurzan T.; Naurysbaev, Erlan A.; Nukiev, Berik A.; Nurkina, Zanar B.; Myrzahanov, Erlan N.; Urazalin, Galym T.

2016-01-01

In this article reviewed problems of the criminalistic classification building of a person. In the work were used legal formal, logical, comparative legal methods. The author describes classification kinds. Reveal the meaning of classification in criminalistic systematics. Shows types of grounds of criminalistic classification of a person.…

An Evaluation of Item Response Theory Classification Accuracy and Consistency Indices

ERIC Educational Resources Information Center

Wyse, Adam E.; Hao, Shiqi

2012-01-01

This article introduces two new classification consistency indices that can be used when item response theory (IRT) models have been applied. The new indices are shown to be related to Rudner's classification accuracy index and Guo's classification accuracy index. The Rudner- and Guo-based classification accuracy and consistency indices are…

33 CFR 154.1016 - Facility classification by COTP.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false Facility classification by COTP... Facilities § 154.1016 Facility classification by COTP. (a) The COTP may upgrade the classification of: (1) An...) The COTP may downgrade, the classification of: (1) An MTR facility specified in § 154.1015(c) to a...

32 CFR 1642.3 - Basis for classification in Class 3-A.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Basis for classification in Class 3-A. 1642.3... CLASSIFICATION OF REGISTRANTS DEFERRED BECAUSE OF HARDSHIP TO DEPENDENTS § 1642.3 Basis for classification in... registrant for classification in Class 3-A, the board will first determine whether the registrant's wife...

7 CFR 27.62 - Conditions for review of classification and for incidental Micronaire determination for original...

Code of Federal Regulations, 2011 CFR

2011-01-01

... may be made at the same time as the request for initial classification. The written application may... 7 Agriculture 2 2011-01-01 2011-01-01 false Conditions for review of classification and for... CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Reviews and Micronaire Determinations...

7 CFR 27.62 - Conditions for review of classification and for incidental Micronaire determination for original...

Code of Federal Regulations, 2010 CFR

2010-01-01

... may be made at the same time as the request for initial classification. The written application may... 7 Agriculture 2 2010-01-01 2010-01-01 false Conditions for review of classification and for... CLASSIFICATION UNDER COTTON FUTURES LEGISLATION Regulations Classification Reviews and Micronaire Determinations...

Impact of Growth in the Universe of Subjects on Classification.

ERIC Educational Resources Information Center

Ranganathan, Shiyali Ramamritam

The development of the removal of rigidity in library classification is traced from the Enumerative Classification of DC (1876) through the Nearly-Faceted Classification of UDC (1896), the rigidly, though fully faceted version of CC (1933), the generalized faceted structure of version 2 of CC (1949), down to the Freely Faceted Classification of…

7 CFR 28.903 - Classification of samples.

Code of Federal Regulations, 2010 CFR

2010-01-01

... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.903 Classification of samples. The Director, or an...

7 CFR 28.903 - Classification of samples.

Code of Federal Regulations, 2012 CFR

2012-01-01

... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.903 Classification of samples. The Director, or an...

7 CFR 28.903 - Classification of samples.

Code of Federal Regulations, 2011 CFR

2011-01-01

... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.903 Classification of samples. The Director, or an...

7 CFR 28.903 - Classification of samples.

Code of Federal Regulations, 2013 CFR

2013-01-01

... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.903 Classification of samples. The Director, or an...

7 CFR 28.903 - Classification of samples.

Code of Federal Regulations, 2014 CFR

2014-01-01

... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.903 Classification of samples. The Director, or an...

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

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

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.

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

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.

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.

Ecosystem classifications based on summer and winter conditions.

PubMed

Andrew, Margaret E; Nelson, Trisalyn A; Wulder, Michael A; Hobart, George W; Coops, Nicholas C; Farmer, Carson J Q

2013-04-01

Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.

Polyp morphology: an interobserver evaluation for the Paris classification among international experts.

PubMed

van Doorn, Sascha C; Hazewinkel, Y; East, James E; van Leerdam, Monique E; Rastogi, Amit; Pellisé, Maria; Sanduleanu-Dascalescu, Silvia; Bastiaansen, Barbara A J; Fockens, Paul; Dekker, Evelien

2015-01-01

The Paris classification is an international classification system for describing polyp morphology. Thus far, the validity and reproducibility of this classification have not been assessed. We aimed to determine the interobserver agreement for the Paris classification among seven Western expert endoscopists. A total of 85 short endoscopic video clips depicting polyps were created and assessed by seven expert endoscopists according to the Paris classification. After a digital training module, the same 85 polyps were assessed again. We calculated the interobserver agreement with a Fleiss kappa and as the proportion of pairwise agreement. The interobserver agreement of the Paris classification among seven experts was moderate with a Fleiss kappa of 0.42 and a mean pairwise agreement of 67%. The proportion of lesions assessed as "flat" by the experts ranged between 13 and 40% (P<0.001). After the digital training, the interobserver agreement did not change (kappa 0.38, pairwise agreement 60%). Our study is the first to validate the Paris classification for polyp morphology. We demonstrated only a moderate interobserver agreement among international Western experts for this classification system. Our data suggest that, in its current version, the use of this classification system in daily practice is questionable and it is unsuitable for comparative endoscopic research. We therefore suggest introduction of a simplification of the classification system.

Limitations and implications of stream classification

USGS Publications Warehouse

Juracek, K.E.; Fitzpatrick, F.A.

2003-01-01

Stream classifications that are based on channel form, such as the Rosgen Level II classification, are useful tools for the physical description and grouping of streams and for providing a means of communication for stream studies involving scientists and (or) managers with different backgrounds. The Level II classification also is used as a tool to assess stream stability, infer geomorphic processes, predict future geomorphic response, and guide stream restoration or rehabilitation activities. The use of the Level II classification for these additional purposes is evaluated in this paper. Several examples are described to illustrate the limitations and management implications of the Level II classification. Limitations include: (1) time dependence, (2) uncertain applicability across physical environments, (3) difficulty in identification of a true equilibrium condition, (4) potential for incorrect determination of bankfull elevation, and (5) uncertain process significance of classification criteria. Implications of using stream classifications based on channel form, such as Rosgen's, include: (1) acceptance of the limitations, (2) acceptance of the risk of classifying streams incorrectly, and (3) classification results may be used inappropriately. It is concluded that use of the Level II classification for purposes beyond description and communication is not appropriate. Research needs are identified that, if addressed, may help improve the usefulness of the Level II classification.

Addition of Histology to the Paris Classification of Pediatric Crohn Disease Alters Classification of Disease Location.

PubMed

Fernandes, Melissa A; Verstraete, Sofia G; Garnett, Elizabeth A; Heyman, Melvin B

2016-02-01

The aim of the study was to investigate the value of microscopic findings in the classification of pediatric Crohn disease (CD) by determining whether classification of disease changes significantly with inclusion of histologic findings. Sixty patients were randomly selected from a cohort of patients studied at the Pediatric Inflammatory Bowel Disease Clinic at the University of California, San Francisco Benioff Children's Hospital. Two physicians independently reviewed the electronic health records of the included patients to determine the Paris classification for each patient by adhering to present guidelines and then by including microscopic findings. Macroscopic and combined disease location classifications were discordant in 34 (56.6%), with no statistically significant differences between groups. Interobserver agreement was higher in the combined classification (κ = 0.73, 95% confidence interval 0.65-0.82) as opposed to when classification was limited to macroscopic findings (κ = 0.53, 95% confidence interval 0.40-0.58). When evaluating the proximal upper gastrointestinal tract (Paris L4a), the interobserver agreement was better in macroscopic compared with the combined classification. Disease extent classifications differed significantly when comparing isolated macroscopic findings (Paris classification) with the combined scheme that included microscopy. Further studies are needed to determine which scheme provides more accurate representation of disease extent.

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results.

PubMed

Hosseinpour-Feizi, Hojjat; Soleimanpour, Jafar; Sales, Jafar Ganjpour; Arzroumchilar, Ali

2011-01-01

The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems. The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance. A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems. Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification's priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method.

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.

Classification schemes for knowledge translation interventions: a practical resource for researchers.

PubMed

Slaughter, Susan E; Zimmermann, Gabrielle L; Nuspl, Megan; Hanson, Heather M; Albrecht, Lauren; Esmail, Rosmin; Sauro, Khara; Newton, Amanda S; Donald, Maoliosa; Dyson, Michele P; Thomson, Denise; Hartling, Lisa

2017-12-06

As implementation science advances, the number of interventions to promote the translation of evidence into healthcare, health systems, or health policy is growing. Accordingly, classification schemes for these knowledge translation (KT) interventions have emerged. A recent scoping review identified 51 classification schemes of KT interventions to integrate evidence into healthcare practice; however, the review did not evaluate the quality of the classification schemes or provide detailed information to assist researchers in selecting a scheme for their context and purpose. This study aimed to further examine and assess the quality of these classification schemes of KT interventions, and provide information to aid researchers when selecting a classification scheme. We abstracted the following information from each of the original 51 classification scheme articles: authors' objectives; purpose of the scheme and field of application; socioecologic level (individual, organizational, community, system); adaptability (broad versus specific); target group (patients, providers, policy-makers), intent (policy, education, practice), and purpose (dissemination versus implementation). Two reviewers independently evaluated the methodological quality of the development of each classification scheme using an adapted version of the AGREE II tool. Based on these assessments, two independent reviewers reached consensus about whether to recommend each scheme for researcher use, or not. Of the 51 original classification schemes, we excluded seven that were not specific classification schemes, not accessible or duplicates. Of the remaining 44 classification schemes, nine were not recommended. Of the 35 recommended classification schemes, ten focused on behaviour change and six focused on population health. Many schemes (n = 29) addressed practice considerations. Fewer schemes addressed educational or policy objectives. Twenty-five classification schemes had broad applicability, six were specific, and four had elements of both. Twenty-three schemes targeted health providers, nine targeted both patients and providers and one targeted policy-makers. Most classification schemes were intended for implementation rather than dissemination. Thirty-five classification schemes of KT interventions were developed and reported with sufficient rigour to be recommended for use by researchers interested in KT in healthcare. Our additional categorization and quality analysis will aid in selecting suitable classification schemes for research initiatives in the field of implementation science.

Remote sensing based detection of forested wetlands: An evaluation of LiDAR, aerial imagery, and their data fusion

NASA Astrophysics Data System (ADS)

Suiter, Ashley Elizabeth

Multi-spectral imagery provides a robust and low-cost dataset for assessing wetland extent and quality over broad regions and is frequently used for wetland inventories. However in forested wetlands, hydrology is obscured by tree canopy making it difficult to detect with multi-spectral imagery alone. Because of this, classification of forested wetlands often includes greater errors than that of other wetlands types. Elevation and terrain derivatives have been shown to be useful for modelling wetland hydrology. But, few studies have addressed the use of LiDAR intensity data detecting hydrology in forested wetlands. Due the tendency of LiDAR signal to be attenuated by water, this research proposed the fusion of LiDAR intensity data with LiDAR elevation, terrain data, and aerial imagery, for the detection of forested wetland hydrology. We examined the utility of LiDAR intensity data and determined whether the fusion of Lidar derived data with multispectral imagery increased the accuracy of forested wetland classification compared with a classification performed with only multi-spectral image. Four classifications were performed: Classification A -- All Imagery, Classification B -- All LiDAR, Classification C -- LiDAR without Intensity, and Classification D -- Fusion of All Data. These classifications were performed using random forest and each resulted in a 3-foot resolution thematic raster of forested upland and forested wetland locations in Vermilion County, Illinois. The accuracies of these classifications were compared using Kappa Coefficient of Agreement. Importance statistics produced within the random forest classifier were evaluated in order to understand the contribution of individual datasets. Classification D, which used the fusion of LiDAR and multi-spectral imagery as input variables, had moderate to strong agreement between reference data and classification results. It was found that Classification A performed using all the LiDAR data and its derivatives (intensity, elevation, slope, aspect, curvatures, and Topographic Wetness Index) was the most accurate classification with Kappa: 78.04%, indicating moderate to strong agreement. However, Classification C, performed with LiDAR derivative without intensity data had less agreement than would be expected by chance, indicating that LiDAR contributed significantly to the accuracy of Classification B.

46 CFR 56.04-2 - Piping classification according to service.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Piping classification according to service. 56.04-2... PIPING SYSTEMS AND APPURTENANCES Piping Classification § 56.04-2 Piping classification according to... Piping Classification Service Class 1 Pressure (p.s.i.g.) Temp. (°F) Class B and C poisons 2 I any and 0...

46 CFR 56.04-2 - Piping classification according to service.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 2 2011-10-01 2011-10-01 false Piping classification according to service. 56.04-2... PIPING SYSTEMS AND APPURTENANCES Piping Classification § 56.04-2 Piping classification according to... Piping Classification Service Class 1 Pressure (p.s.i.g.) Temp. (°F) Class B and C poisons 2 I any and 0...

32 CFR 1639.3 - Basis for classification in Class 2-D.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Basis for classification in Class 2-D. 1639.3... CLASSIFICATION OF REGISTRANTS PREPARING FOR THE MINISTRY § 1639.3 Basis for classification in Class 2-D. (a) In... maintained for qualification for the deferment. (b) The registrant's classification shall be determined on...

32 CFR 1639.3 - Basis for classification in Class 2-D.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Basis for classification in Class 2-D. 1639.3... CLASSIFICATION OF REGISTRANTS PREPARING FOR THE MINISTRY § 1639.3 Basis for classification in Class 2-D. (a) In... maintained for qualification for the deferment. (b) The registrant's classification shall be determined on...

48 CFR 245.201-73 - Security classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Security classification... Procedures 245.201-73 Security classification. Follow the procedures at PGI 245.201-73 for security classification. ...

48 CFR 245.201-73 - Security classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 3 2012-10-01 2012-10-01 false Security classification... Procedures 245.201-73 Security classification. Follow the procedures at PGI 245.201-73 for security classification. ...

Comparative study of classification algorithms for damage classification in smart composite laminates

NASA Astrophysics Data System (ADS)

Khan, Asif; Ryoo, Chang-Kyung; Kim, Heung Soo

2017-04-01

This paper presents a comparative study of different classification algorithms for the classification of various types of inter-ply delaminations in smart composite laminates. Improved layerwise theory is used to model delamination at different interfaces along the thickness and longitudinal directions of the smart composite laminate. The input-output data obtained through surface bonded piezoelectric sensor and actuator is analyzed by the system identification algorithm to get the system parameters. The identified parameters for the healthy and delaminated structure are supplied as input data to the classification algorithms. The classification algorithms considered in this study are ZeroR, Classification via regression, Naïve Bayes, Multilayer Perceptron, Sequential Minimal Optimization, Multiclass-Classifier, and Decision tree (J48). The open source software of Waikato Environment for Knowledge Analysis (WEKA) is used to evaluate the classification performance of the classifiers mentioned above via 75-25 holdout and leave-one-sample-out cross-validation regarding classification accuracy, precision, recall, kappa statistic and ROC Area.

PDF text classification to leverage information extraction from publication reports.

PubMed

Bui, Duy Duc An; Del Fiol, Guilherme; Jonnalagadda, Siddhartha

2016-06-01

Data extraction from original study reports is a time-consuming, error-prone process in systematic review development. Information extraction (IE) systems have the potential to assist humans in the extraction task, however majority of IE systems were not designed to work on Portable Document Format (PDF) document, an important and common extraction source for systematic review. In a PDF document, narrative content is often mixed with publication metadata or semi-structured text, which add challenges to the underlining natural language processing algorithm. Our goal is to categorize PDF texts for strategic use by IE systems. We used an open-source tool to extract raw texts from a PDF document and developed a text classification algorithm that follows a multi-pass sieve framework to automatically classify PDF text snippets (for brevity, texts) into TITLE, ABSTRACT, BODYTEXT, SEMISTRUCTURE, and METADATA categories. To validate the algorithm, we developed a gold standard of PDF reports that were included in the development of previous systematic reviews by the Cochrane Collaboration. In a two-step procedure, we evaluated (1) classification performance, and compared it with machine learning classifier, and (2) the effects of the algorithm on an IE system that extracts clinical outcome mentions. The multi-pass sieve algorithm achieved an accuracy of 92.6%, which was 9.7% (p<0.001) higher than the best performing machine learning classifier that used a logistic regression algorithm. F-measure improvements were observed in the classification of TITLE (+15.6%), ABSTRACT (+54.2%), BODYTEXT (+3.7%), SEMISTRUCTURE (+34%), and MEDADATA (+14.2%). In addition, use of the algorithm to filter semi-structured texts and publication metadata improved performance of the outcome extraction system (F-measure +4.1%, p=0.002). It also reduced of number of sentences to be processed by 44.9% (p<0.001), which corresponds to a processing time reduction of 50% (p=0.005). The rule-based multi-pass sieve framework can be used effectively in categorizing texts extracted from PDF documents. Text classification is an important prerequisite step to leverage information extraction from PDF documents. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Remote Sensing Information Classification

NASA Technical Reports Server (NTRS)

Rickman, Douglas L.

2008-01-01

This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

75 FR 70754 - Postal Classification Changes

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-18

... POSTAL REGULATORY COMMISSION [Docket No. MC2011-5; Order No. 583] Postal Classification Changes...-filed Postal Service request announcing a classification change affecting bundle and container charges... Commission announcing a classification change [[Page 70755

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.

Towards a robust framework for catchment classification

NASA Astrophysics Data System (ADS)

Deshmukh, A.; Samal, A.; Singh, R.

2017-12-01

Classification of catchments based on various measures of similarity has emerged as an important technique to understand regional scale hydrologic behavior. Classification of catchment characteristics and/or streamflow response has been used reveal which characteristics are more likely to explain the observed variability of hydrologic response. However, numerous algorithms for supervised or unsupervised classification are available, making it hard to identify the algorithm most suitable for the dataset at hand. Consequently, existing catchment classification studies vary significantly in the classification algorithms employed with no previous attempt at understanding the degree of uncertainty in classification due to this algorithmic choice. This hinders the generalizability of interpretations related to hydrologic behavior. Our goal is to develop a protocol that can be followed while classifying hydrologic datasets. We focus on a classification framework for unsupervised classification and provide a step-by-step classification procedure. The steps include testing the clusterabiltiy of original dataset prior to classification, feature selection, validation of clustered data, and quantification of similarity of two clusterings. We test several commonly available methods within this framework to understand the level of similarity of classification results across algorithms. We apply the proposed framework on recently developed datasets for India to analyze to what extent catchment properties can explain observed catchment response. Our testing dataset includes watershed characteristics for over 200 watersheds which comprise of both natural (physio-climatic) characteristics and socio-economic characteristics. This framework allows us to understand the controls on observed hydrologic variability across India.

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.

Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

NASA Astrophysics Data System (ADS)

Niazmardi, S.; Safari, A.; Homayouni, S.

2017-09-01

Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

National Seabed Mapping Programmes Collaborate to Advance Marine Geomorphological Mapping in Adjoining European Seas

NASA Astrophysics Data System (ADS)

Monteys, X.; Guinan, J.; Green, S.; Gafeira, J.; Dove, D.; Baeten, N. J.; Thorsnes, T.

2017-12-01

Marine geomorphological mapping is an effective means of characterising and understanding the seabed and its features with direct relevance to; offshore infrastructure placement, benthic habitat mapping, conservation & policy, marine spatial planning, fisheries management and pure research. Advancements in acoustic survey techniques and data processing methods resulting in the availability of high-resolution marine datasets e.g. multibeam echosounder bathymetry and shallow seismic mean that geological interpretations can be greatly improved by combining with geomorphological maps. Since December 2015, representatives from the national seabed mapping programmes of Norway (MAREANO), Ireland (INFOMAR) and the United Kingdom (MAREMAP) have collaborated and established the MIM geomorphology working group) with the common aim of advancing best practice for geological mapping in their adjoining sea areas in north-west Europe. A recently developed two-part classification system for Seabed Geomorphology (`Morphology' and Geomorphology') has been established as a result of an initiative led by the British Geological Survey (BGS) with contributions from the MIM group (Dove et al. 2016). To support the scheme, existing BGS GIS tools (SIGMA) have been adapted to apply this two-part classification system and here we present on the tools effectiveness in mapping geomorphological features, along with progress in harmonising the classification and feature nomenclature. Recognising that manual mapping of seabed features can be time-consuming and subjective, semi-automated approaches for mapping seabed features and improving mapping efficiency is being developed using Arc-GIS based tools. These methods recognise, spatially delineate and morphologically describe seabed features such as pockmarks (Gafeira et al., 2012) and cold-water coral mounds. Such tools utilise multibeam echosounder data or any other bathymetric dataset (e.g. 3D seismic, Geldof et al., 2014) that can produce a depth digital model. The tools have the capability to capture an extensive list of morphological attributes. The MIM geomorphology working group's strategy to develop methods for more efficient marine geomorphological mapping is presented with data examples and case studies showing the latest results.

GaN/AlGaN Strain-Balanced Heterostructures for Near-IR Quantum Well Photodetectors

DTIC Science & Technology

2003-12-03

of Leeds as follows: The contractor will design, fabricate, and analyze Quantum Well Infrared Photodetectors (QWIP) that detect in the 2-6 micron...SUBJECT TERMS EOARD, Sensor Technology, infrared technology, Gallium Nitride, Quantum Well Devices 16. SECURITY CLASSIFICATION OF: 19a. NAME OF...resulting from these collaborations are the first quantum well infrared photodetectors based in the GaN material system to be reported. 1 1. In accordance

Incorporating Ecosystem Goods and Services in Environmental Planning: A Literature Review of Definitions, Classification and Operational Approaches

DTIC Science & Technology

2013-08-01

hunting, cleaner water, better views, and reduced human health risks and ecological risks). These require some interaction with, or at least some... evolution in collaboration. The discipline of ecology has possessed an underlying socio- economic character in several phases of its development as...environment. Early connection to concepts in evolution . Introduced the Greek term oikos linked to both ecology (study of the household) and

Image Analysis and Classification Based on Soil Strength

DTIC Science & Technology

2016-08-01

Satellite imagery classification is useful for a variety of commonly used ap- plications, such as land use classification, agriculture , wetland...required use of a coinci- dent digital elevation model (DEM) and a high-resolution orthophoto- graph collected by the National Agriculture Imagery Program...14. ABSTRACT Satellite imagery classification is useful for a variety of commonly used applications, such as land use classification, agriculture

32 CFR 1642.2 - The claim for classification in Class 3-A.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SYSTEM CLASSIFICATION OF REGISTRANTS DEFERRED BECAUSE OF HARDSHIP TO DEPENDENTS § 1642.2 The claim for classification in Class 3-A. A claim for classification in Class 3-A must be made by the registrant in writing... 32 National Defense 6 2010-07-01 2010-07-01 false The claim for classification in Class 3-A. 1642...

32 CFR 1642.2 - The claim for classification in Class 3-A.

Code of Federal Regulations, 2011 CFR

2011-07-01

... SYSTEM CLASSIFICATION OF REGISTRANTS DEFERRED BECAUSE OF HARDSHIP TO DEPENDENTS § 1642.2 The claim for classification in Class 3-A. A claim for classification in Class 3-A must be made by the registrant in writing... 32 National Defense 6 2011-07-01 2011-07-01 false The claim for classification in Class 3-A. 1642...

Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?

NASA Astrophysics Data System (ADS)

Švab Lenarčič, Andreja; Đurić, Nataša; Čotar, Klemen; Ritlop, Klemen; Oštir, Krištof

2016-10-01

It is a broadly established belief that the segmentation result significantly affects subsequent image classification accuracy. However, the actual correlation between the two has never been evaluated. Such an evaluation would be of considerable importance for any attempts to automate the object-based classification process, as it would reduce the amount of user intervention required to fine-tune the segmentation parameters. We conducted an assessment of segmentation and classification by analyzing 100 different segmentation parameter combinations, 3 classifiers, 5 land cover classes, 20 segmentation evaluation metrics, and 7 classification accuracy measures. The reliability definition of segmentation evaluation metrics as indicators of land cover classification accuracy was based on the linear correlation between the two. All unsupervised metrics that are not based on number of segments have a very strong correlation with all classification measures and are therefore reliable as indicators of land cover classification accuracy. On the other hand, correlation at supervised metrics is dependent on so many factors that it cannot be trusted as a reliable classification quality indicator. Algorithms for land cover classification studied in this paper are widely used; therefore, presented results are applicable to a wider area.

[LiLa classification for paediatric long bone fractures. Intraobserver and interobserver reliability].

PubMed

Kamphaus, A; Rapp, M; Wessel, L M; Buchholz, M; Massalme, E; Schneidmüller, D; Roeder, C; Kaiser, M M

2015-04-01

There are two child-specific fracture classification systems for long bone fractures: the AO classification of pediatric long-bone fractures (PCCF) and the LiLa classification of pediatric fractures of long bones (LiLa classification). Both are still not widely established in comparison to the adult AO classification for long bone fractures. During a period of 12 months all long bone fractures in children were documented and classified according to the LiLa classification by experts and non-experts. Intraobserver and interobserver reliability were calculated according to Cohen (kappa). A total of 408 fractures were classified. The intraobserver reliability for location in the skeletal and bone segment showed an almost perfect agreement (K = 0.91-0.95) and also the morphology (joint/shaft fracture) (K = 0.87-0.93). Due to different judgment of the fracture displacement in the second classification round, the intraobserver reliability of the whole classification revealed moderate agreement (K = 0.53-0.58). Interobserver reliability showed moderate agreement (K = 0.55) often due to the low quality of the X-rays. Further differences occurred due to difficulties in assigning the precise transition from metaphysis to diaphysis. The LiLa classification is suitable and in most cases user-friendly for classifying long bone fractures in children. Reliability is higher than in established fracture specific classifications and comparable to the AO classification of pediatric long bone fractures. Some mistakes were due to a low quality of the X-rays and some due to difficulties to classify the fractures themselves. Improvements include a more precise definition of the metaphysis and the kind of displacement. Overall the LiLa classification should still be considered as an alternative for classifying pediatric long bone fractures.