23 CFR 470.105 - Urban area boundaries and highway functional classification.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 23 Highways 1 2011-04-01 2011-04-01 false Urban area boundaries and highway functional classification. 470.105 Section 470.105 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PLANNING AND RESEARCH HIGHWAY SYSTEMS Federal-aid Highway Systems § 470.105 Urban area boundaries and...

23 CFR 470.105 - Urban area boundaries and highway functional classification.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 23 Highways 1 2014-04-01 2014-04-01 false Urban area boundaries and highway functional classification. 470.105 Section 470.105 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PLANNING AND RESEARCH HIGHWAY SYSTEMS Federal-aid Highway Systems § 470.105 Urban area boundaries and...

23 CFR 470.105 - Urban area boundaries and highway functional classification.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 23 Highways 1 2012-04-01 2012-04-01 false Urban area boundaries and highway functional classification. 470.105 Section 470.105 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PLANNING AND RESEARCH HIGHWAY SYSTEMS Federal-aid Highway Systems § 470.105 Urban area boundaries and...

A Functional Classification of Occupations.

ERIC Educational Resources Information Center

McKinlay, Donald Bruce

The need for more and better manpower information is hampered by the lack of adequate occupational data classification systems. The diversity of interests in occupations probably accounts for the absence of consensus regarding either the general outlines or the specific details of a standardized occupational classification system which would…

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.

PubMed

Pläschke, Rachel N; Cieslik, Edna C; Müller, Veronika I; Hoffstaedter, Felix; Plachti, Anna; Varikuti, Deepthi P; Goosses, Mareike; Latz, Anne; Caspers, Svenja; Jockwitz, Christiane; Moebus, Susanne; Gruber, Oliver; Eickhoff, Claudia R; Reetz, Kathrin; Heller, Julia; Südmeyer, Martin; Mathys, Christian; Caspers, Julian; Grefkes, Christian; Kalenscher, Tobias; Langner, Robert; Eickhoff, Simon B

2017-12-01

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

On the nature of global classification

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Developing and validating the Communication Function Classification System for individuals with cerebral palsy

PubMed Central

HIDECKER, MARY JO COOLEY; PANETH, NIGEL; ROSENBAUM, PETER L; KENT, RAYMOND D; LILLIE, JANET; EULENBERG, JOHN B; CHESTER, KEN; JOHNSON, BRENDA; MICHALSEN, LAUREN; EVATT, MORGAN; TAYLOR, KARA

2011-01-01

Aim The purpose of this study was to create and validate a Communication Function Classification System (CFCS) for children with cerebral palsy (CP) that can be used by a wide variety of individuals who are interested in CP. This paper reports the content validity, interrater reliability, and test–retest reliability of the CFCS for children with CP. Method An 11-member development team created comprehensive descriptions of the CFCS levels, and four nominal groups comprising 27 participants critiqued these levels. Within a Delphi survey, 112 participants commented on the clarity and usefulness of the CFCS. Interrater reliability was completed by 61 professionals and 68 parents/relatives who classified 69 children with CP aged 2 to 18 years. Test–retest reliability was completed by 48 professionals who allowed at least 2 weeks between classifications. The participants who assessed the CFCS were all relevant stakeholders: adults with CP, parents of children with CP, educators, occupational therapists, physical therapists, physicians, and speech–language pathologists. Results The interrater reliability of the CFCS was 0.66 between two professionals and 0.49 between a parent and a professional. Professional interrater reliability improved to 0.77 for classification of children older than 4 years. The test–retest reliability was 0.82. Interpretation The CFCS demonstrates content validity and shows very good test–retest reliability, good professional interrater reliability, and moderate parent–professional interrater reliability. Combining the CFCS with the Gross Motor Function Classification System and the Manual Ability Classification System contributes to a functional performance view of daily life for individuals with CP, in accordance with the World Health Organization’s International Classification of Functioning, Disability and Health. PMID:21707596

Characteristics of a global classification system for perinatal deaths: a Delphi consensus study.

PubMed

Wojcieszek, Aleena M; Reinebrant, Hanna E; Leisher, Susannah Hopkins; Allanson, Emma; Coory, Michael; Erwich, Jan Jaap; Frøen, J Frederik; Gardosi, Jason; Gordijn, Sanne; Gulmezoglu, Metin; Heazell, Alexander E P; Korteweg, Fleurisca J; McClure, Elizabeth; Pattinson, Robert; Silver, Robert M; Smith, Gordon; Teoh, Zheyi; Tunçalp, Özge; Flenady, Vicki

2016-08-15

Despite the global burden of perinatal deaths, there is currently no single, globally-acceptable classification system for perinatal deaths. Instead, multiple, disparate systems are in use world-wide. This inconsistency hinders accurate estimates of causes of death and impedes effective prevention strategies. The World Health Organisation (WHO) is developing a globally-acceptable classification approach for perinatal deaths. To inform this work, we sought to establish a consensus on the important characteristics of such a system. A group of international experts in the classification of perinatal deaths were identified and invited to join an expert panel to develop a list of important characteristics of a quality global classification system for perinatal death. A Delphi consensus methodology was used to reach agreement. Three rounds of consultation were undertaken using a purpose built on-line survey. Round one sought suggested characteristics for subsequent scoring and selection in rounds two and three. The panel of experts agreed on a total of 17 important characteristics for a globally-acceptable perinatal death classification system. Of these, 10 relate to the structural design of the system and 7 relate to the functional aspects and use of the system. This study serves as formative work towards the development of a globally-acceptable approach for the classification of the causes of perinatal deaths. The list of functional and structural characteristics identified should be taken into consideration when designing and developing such a system.

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

PubMed

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

2007-03-01

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

Prognostic value of computed tomography classification systems for intra-articular calcaneus fractures.

PubMed

Swords, Michael P; Alton, Timothy B; Holt, Sarah; Sangeorzan, Bruce J; Shank, John R; Benirschke, Stephen K

2014-10-01

There are several published computed tomography (CT) classification systems for calcaneus fractures, each validated by a different standard. The goal of this study was to measure which system would best predict clinical outcomes as measured by a widely used and validated musculoskeletal health status questionnaire. Forty-nine patients with isolated intra-articular joint depression calcaneus fractures more than 2 years after treatment were identified. All had preoperative CT studies and were treated with open reduction and plate fixation using a lateral extensile approach. Four different blinded reviewers classified injuries according to the CT classification systems of Crosby and Fitzgibbons, Eastwood, and Sanders. Functional outcomes evaluated with a Musculoskeletal Functional Assessment (MFA). The mean follow-up was 4.3 years. The mean MFA score was 15.7 (SD = 11.6), which is not significantly different from published values for midfoot injuries, hindfoot injuries, or both, 1 year after injury (mean = 22.1, SD = 18.4). The classification systems of Crosby and Fitzgibbons, Eastwood, and Sanders, the number of fragments of the posterior facet, and payer status were not significantly associated with outcome as determined by the MFA. The Sanders classification trended toward significance. Anterior process comminution and surgeon's overall impression of severity were significantly associated with functional outcome. The amount of anterior process comminution was an important determinant of functional outcome with increasing anterior process comminution significantly associated with worsened functional outcome (P = .04). In addition, the surgeon's overall impression of severity of injury was predictive of functional outcome (P = .02), as determined by MFA. Level III, comparative series. © The Author(s) 2014.

Global Similarity Predicts Dissociation of Classification and Recognition: Evidence Questioning the Implicit-Explicit Learning Distinction in Amnesia

ERIC Educational Resources Information Center

Jamieson, Randall K.; Holmes, Signy; Mewhort, D. J. K.

2010-01-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort…

Subacute and non-acute casemix in Australia.

PubMed

Lee, L A; Eagar, K M; Smith, M C

1998-10-19

The costs of subacute care (palliative care, rehabilitation medicine, psychogeriatrics, and geriatric evaluation and management) and non-acute care (nursing home, convalescent and planned respite care) are not adequately described by existing casemix classifications. The predominant treatment goals in subacute care are enhancement of quality of life and/or improvement in functional status and, in non-acute care, maintenance of current health and functional status. A national classification system for this area has now been developed--the Australian National Sub-Acute and Non-Acute Patient Classification System (AN-SNAP). The AN-SNAP system, based on analysis of over 30,000 episodes of care, defines four case types of subacute care (palliative care, rehabilitation, psychogeriatric care, and geriatric evaluation and management and one case type of non-acute care (maintenance care), and classifies both overnight and ambulatory care. The AN-SNAP system reflects the goal of management--a change in functional status or improvement in quality of life--rather than the patient's diagnosis. It will complement the existing AN-DRG classification.

Global similarity predicts dissociation of classification and recognition: evidence questioning the implicit-explicit learning distinction in amnesia.

PubMed

Jamieson, Randall K; Holmes, Signy; Mewhort, D J K

2010-11-01

Dissociation of classification and recognition in amnesia is widely taken to imply 2 functional systems: an implicit procedural-learning system that is spared in amnesia and an explicit episodic-learning system that is compromised. We argue that both tasks reflect the global similarity of probes to memory. In classification, subjects sort unstudied grammatical exemplars from lures, whereas in recognition, they sort studied grammatical exemplars from lures. Hence, global similarity is necessarily greater in recognition than in classification. Moreover, a grammatical exemplar's similarity to studied exemplars is a nonlinear function of the integrity of the data in memory. Assuming that data integrity is better for control subjects than for subjects with amnesia, the nonlinear relation combined with the advantage for recognition over classification predicts the dissociation of recognition and classification. To illustrate the dissociation of recognition and classification in healthy undergraduates, we manipulated study time to vary the integrity of the data in memory and brought the dissociation under experimental control. We argue that the dissociation reflects a general cost in memory rather than a selective impairment of separate procedural and episodic systems. (c) 2010 APA, all rights reserved

The Relationship between Manual Ability and Ambulation in Adolescents with Cerebral Palsy

ERIC Educational Resources Information Center

Majnemer, Annette; Shikako-Thomas, Keiko; Shevell, Michael; Poulin, Chantal; Lach, Lucyna; Law, Mary; Schmitz, Norbert

2013-01-01

This study examined the relationship between gross motor function and manual ability in 120 adolescents with cerebral palsy (CP) (15.2, SD 2.1 years, 59.8% male). Adolescents were evaluated using the Gross Motor Function Classification System (GMFCS) and the Manual Ability Classification System (MACS). A neurologist classified CP subtype. Most…

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

PubMed

Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

2016-02-01

Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, p<0.001), with worse dystonia severity implying worse function. Secondary dystonias had worse dystonia and less function than primary dystonias (p<0.001). A longer proportion of life lived with dystonia is associated with more severe dystonia (rs =0.42, p<0.001). The BFM-M is strongly linked with the GMFCS, MACS, and CFCS, irrespective of aetiology. Each scale offers interrelated but complementary information and is applicable to all aetiologies. Movement disorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

Attachment-based classifications of children's family drawings: psychometric properties and relations with children's adjustment in kindergarten.

PubMed

Pianta, R C; Longmaid, K; Ferguson, J E

1999-06-01

Investigated an attachment-based theoretical framework and classification system, introduced by Kaplan and Main (1986), for interpreting children's family drawings. This study concentrated on the psychometric properties of the system and the relation between drawings classified using this system and teacher ratings of classroom social-emotional and behavioral functioning, controlling for child age, ethnic status, intelligence, and fine motor skills. This nonclinical sample consisted of 200 kindergarten children of diverse racial and socioeconomic status (SES). Limited support for reliability of this classification system was obtained. Kappas for overall classifications of drawings (e.g., secure) exceeded .80 and mean kappa for discrete drawing features (e.g., figures with smiles) was .82. Coders' endorsement of the presence of certain discrete drawing features predicted their overall classification at 82.5% accuracy. Drawing classification was related to teacher ratings of classroom functioning independent of child age, sex, race, SES, intelligence, and fine motor skills (with p values for the multivariate effects ranging from .043-.001). Results are discussed in terms of the psychometric properties of this system for classifying children's representations of family and the limitations of family drawing techniques for young children.

Access management classification and spacing standards

DOT National Transportation Integrated Search

1996-08-23

The specific objectives of this background paper are:(1)Provide an overview of : the relationship between the functional integrity of the highway system and the : access management classification system, (2)Review and evaluate the current : Oregon De...

[Automation in surgery: a systematical approach].

PubMed

Strauss, G; Meixensberger, J; Dietz, A; Manzey, D

2007-04-01

Surgical assistance systems permit a misalignment from the purely manual to an assisted activity of the surgeon (automation). Automation defines a system, that partly or totally fulfils function, those was carried out before totally or partly by the user. The organization of surgical assistance systems following application (planning, simulation, intraoperative navigation and visualization) or technical configuration of the system (manipulator, robot) is not suitable for a description of the interaction between user (surgeon) and the system. The available work has the goal of providing a classification for the degree of the automation of surgical interventions and describing by examples. The presented classification orients itself at pre-working from the Human-Factors-Sciences. As a condition for an automation of a surgical intervention applies that an assumption of a task, which was alone assigned so far to the surgeon takes place via the system. For both reference objects (humans and machine) the condition passively or actively comes into consideration. Besides can be classified according to which functions are taken over during a selected function division by humans and/or the surgical assistance system. Three functional areas were differentiated: "information acquisition and -analysis", "decision making and action planning" as well as "execution of the surgical action". From this results a classification of pre- and intraoperative surgical assist systems in six categories, which represent different automation degrees. The classification pattern is described and illustrated on the basis of surgical of examples.

Developing and Validating the Communication Function Classification System for Individuals with Cerebral Palsy

ERIC Educational Resources Information Center

Hidecker, Mary Jo Cooley; Paneth, Nigel; Rosenbaum, Peter L.; Kent, Raymond D.; Lillie, Janet; Eulenberg, John B.; Chester, Ken, Jr.; Johnson, Brenda; Michalsen, Lauren; Evatt, Morgan; Taylor, Kara

2011-01-01

Aim: The purpose of this study was to create and validate the Communication Function Classification System (CFCS) for children with cerebral palsy (CP), for use by a wide variety of individuals who are interested in CP. This paper reports the content validity, interrater reliability, and test-retest reliability of the CFCS for children with CP.…

Development and reliability of the Functional Communication Classification System for children with cerebral palsy.

PubMed

Barty, Elizabeth; Caynes, Katy; Johnston, Leanne M

2016-10-01

This paper describes the development, validation, and reliability of the Functional Communication Classification System (FCCS), designed to classify expressive communication skills of children with cerebral palsy (CP) aged 4 years and 5 years (between their fourth and sixth birthdays). The Functional Communication Classification System (FCCS) was developed in 2006 using a literature review, client file audit, and expert consultative committee process in order to devise scale content, structure, and check clinical validity and utility. Interrater reliability was examined between speech-language pathologists (SLPs), other allied health professionals (AHPs), and parents of 48 children with CP. The scale was revised and a clinical reasoning prompt sheet added, then trialled again for 42 children. The result was a five-level system with descriptors and decision-making guides for classification of functional expressive communication for children with CP. Overall interrater reliability was excellent for the final FCCS, intraclass correlation coefficient=0.97 (95% confidence interval 0.95 to 0.98). Kappa values were 0.94 between SLPs and AHPs, 0.59 between SLPs and parents, and 0.60 between AHPs and parents. The FCCS is a reliable tool for describing functional communication in young children with CP, appropriate for use by SLPs, other AHPs, and parents of children with CP. © 2016 Mac Keith Press.

Clinical characteristics and functional status of children with different subtypes of dyskinetic cerebral palsy.

PubMed

Sun, Dianrong; Wang, Qiang; Hou, Mei; Li, Yutang; Yu, Rong; Zhao, Jianhui; Wang, Ke

2018-05-01

Dyskinetic cerebral palsy (CP) is the second major subtype of CP. Dyskinetic CP can be classified into different subtypes, but the exact clinical characteristics of these subtypes have been poorly studied. To investigate the clinical characteristics and functional classification of dyskinetic CP from the perspective of neurologic subtypes in a hospital-based follow-up study.This was an observational study of consecutive children with dyskinetic CP treated at The Affiliated Women & Children Hospital of Qingdao University (China) from October 2005 to February 2015. The children were stratified according to their neurologic subtype and assessed with the Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS). MRI scanning was conducted at 1 year of age for most children.Twenty-six participants (28.0%) had dystonic CP, 26 (28.0%) had choreoathetotic CP, and 41 (44.1%) had mixed CP. Auditory impairment and basal ganglion lesions occurred more frequently in the dystonia group (n = 8, 31%; and n = 16, 67%), while seizures, microcephaly, white matter lesions, and mixed lesions were more frequent in the mixed type (n = 14, 34%; n = 10, 24%; n = 15, 41%; n = 12, 32%). Functional classification levels were distributed unequally among the 3 subgroups (P < .01). No significant difference between GMFCS and MACS was found among the 3 subgroups (P > .05).Different subtypes of dyskinetic CP have specific comorbidities, radiological characteristics, and functional attributes according to their etiological factors and brain lesions. Children with dystonic CP have more limited functional status than children with choreoathetotic CP.

Classification in childhood disability: focusing on function in the 21st century.

PubMed

Rosenbaum, Peter; Eliasson, Ann-Christin; Hidecker, Mary Jo Cooley; Palisano, Robert J

2014-08-01

Classification systems in health care are usually based on current understanding of the condition. They are often derived empirically and adopted applying sound principles of measurement science to assess whether they are reliable (consistent) and valid (true) for the purposes to which they are applied. In the past 15 years, the authors have developed and validated classification systems for specific aspects of everyday function in people with cerebral palsy--gross motor function, manual abilities, and communicative function. This article describes the approaches used to conceptualize each aspect of function, develop the tools, and assess their reliability and validity. We report on the utility of each system with respect to clinical applicability, use of these tools for research, and the uptake and impact that they have had around the world. We hope that readers will find these accounts interesting, relevant, and applicable to their daily work with children and youth with disabilities. © The Author(s) 2014.

Interobserver Agreement of the Gross Motor Function Classification System in an Ambulant Population of Children with Cerebral Palsy

ERIC Educational Resources Information Center

McDowell, Brona C.; Kerr, Claire; Parkes, Jackie

2007-01-01

Gross Motor Function Classification System (GMFCS) level was reported by three independent assessors in a population of children with cerebral palsy (CP) aged between 4 and 18 years (n=184; 112 males, 72 females; mean age 10y 10mo [SD 3y 7mo]). A software algorithm also provided a computed GMFCS level from a regional CP registry. Participants had…

[New International Classification of Chronic Pancreatitis (M-ANNHEIM multifactor classification system, 2007): principles, merits, and demerits].

PubMed

Tsimmerman, Ia S

2008-01-01

The new International Classification of Chronic Pancreatitis (designated as M-ANNHEIM) proposed by a group of German specialists in late 2007 is reviewed. All its sections are subjected to analysis (risk group categories, clinical stages and phases, variants of clinical course, diagnostic criteria for "established" and "suspected" pancreatitis, instrumental methods and functional tests used in the diagnosis, evaluation of the severity of the disease using a scoring system, stages of elimination of pain syndrome). The new classification is compared with the earlier classification proposed by the author. Its merits and demerits are discussed.

The Transporter Classification Database: recent advances.

PubMed

Saier, Milton H; Yen, Ming Ren; Noto, Keith; Tamang, Dorjee G; Elkan, Charles

2009-01-01

The Transporter Classification Database (TCDB), freely accessible at http://www.tcdb.org, is a relational database containing sequence, structural, functional and evolutionary information about transport systems from a variety of living organisms, based on the International Union of Biochemistry and Molecular Biology-approved transporter classification (TC) system. It is a curated repository for factual information compiled largely from published references. It uses a functional/phylogenetic system of classification, and currently encompasses about 5000 representative transporters and putative transporters in more than 500 families. We here describe novel software designed to support and extend the usefulness of TCDB. Our recent efforts render it more user friendly, incorporate machine learning to input novel data in a semiautomatic fashion, and allow analyses that are more accurate and less time consuming. The availability of these tools has resulted in recognition of distant phylogenetic relationships and tremendous expansion of the information available to TCDB users.

Fire severity classification: Uses and abuses

Treesearch

Theresa B. Jain; Russell T. Graham

2003-01-01

Burn severity (also referred to as fire severity) is not a single definition, but rather a concept and its classification is a function of the measured units unique to the system of interest. The systems include: flora and fauna, soil microbiology and hydrologic processes, atmospheric inputs, fire management, and society. Depending on the particular system of interest...

Classification of speech and language profiles in 4-year old children with cerebral palsy: A prospective preliminary study

PubMed Central

Hustad, Katherine C.; Gorton, Kristin; Lee, Jimin

2010-01-01

Purpose Little is known about the speech and language abilities of children with cerebral palsy (CP) and there is currently no system for classifying speech and language profiles. Such a system would have epidemiological value and would have the potential to advance the development of interventions that improve outcomes. In this study, we propose and test a preliminary speech and language classification system by quantifying how well speech and language data differentiate among children classified into different hypothesized profile groups. Method Speech and language assessment data were collected in a laboratory setting from 34 children with CP (18 males; 16 females) who were a mean age of 54 months (SD 1.8 months). Measures of interest were vowel area, speech rate, language comprehension scores, and speech intelligibility ratings. Results Canonical discriminant function analysis showed that three functions accounted for 100% of the variance among profile groups, with speech variables accounting for 93% of the variance. Classification agreement varied from 74% to 97% using four different classification paradigms. Conclusions Results provide preliminary support for the classification of speech and language abilities of children with CP into four initial profile groups. Further research is necessary to validate the full classification system. PMID:20643795

Cognitive-motivational deficits in ADHD: development of a classification system.

PubMed

Gupta, Rashmi; Kar, Bhoomika R; Srinivasan, Narayanan

2011-01-01

The classification systems developed so far to detect attention deficit/hyperactivity disorder (ADHD) do not have high sensitivity and specificity. We have developed a classification system based on several neuropsychological tests that measure cognitive-motivational functions that are specifically impaired in ADHD children. A total of 240 (120 ADHD children and 120 healthy controls) children in the age range of 6-9 years and 32 Oppositional Defiant Disorder (ODD) children (aged 9 years) participated in the study. Stop-Signal, Task-Switching, Attentional Network, and Choice Delay tests were administered to all the participants. Receiver operating characteristic (ROC) analysis indicated that percentage choice of long-delay reward best classified the ADHD children from healthy controls. Single parameters were not helpful in making a differential classification of ADHD with ODD. Multinominal logistic regression (MLR) was performed with multiple parameters (data fusion) that produced improved overall classification accuracy. A combination of stop-signal reaction time, posterror-slowing, mean delay, switch cost, and percentage choice of long-delay reward produced an overall classification accuracy of 97.8%; with internal validation, the overall accuracy was 92.2%. Combining parameters from different tests of control functions not only enabled us to accurately classify ADHD children from healthy controls but also in making a differential classification with ODD. These results have implications for the theories of ADHD.

Identification of Putative Cardiovascular System Developmental Toxicants using a Classification Model based on Signaling Pathway-Adverse Outcome Pathways

EPA Science Inventory

An important challenge for an integrative approach to developmental systems toxicology is associating putative molecular initiating events (MIEs), cell signaling pathways, cell function and modeled fetal exposure kinetics. We have developed a chemical classification model based o...

Autonomic cardiovascular control and sports classification in Paralympic athletes with spinal cord injury.

PubMed

West, Christopher R; Krassioukov, Andrei V

2017-01-01

Purpose To investigate the relationship between the classification systems used in wheelchair sports and cardiovascular function in Paralympic athletes with spinal cord injury (SCI). Methods 26 wheelchair rugby (C3-C8) and 14 wheelchair basketball (T3-L1) were assessed for their International Wheelchair Rugby and Basketball Federation sports classification. Next, athletes were assessed for resting and reflex cardiovascular and autonomic function via the change (delta) in systolic blood pressure (SBP) and heart rate (HR) in response to sit-up, and sympathetic skin responses (SSRs), respectively. Results There were no differences in supine, seated, or delta SBP and HR between different sport classes in rugby or basketball (all p > 0.23). Athletes with autonomically complete injuries (SSR score 0-1) exhibited a lower supine SBP, seated SBP and delta SBP compared to those with autonomically incomplete injuries (SSR score >1; all p < 0.010), independent of sport played. There was no association between self-report OH and measured OH (χ 2  =   1.63, p = 0.20). Conclusion We provide definitive evidence that sports specific classification is not related to the degree of remaining autonomic cardiovascular control in Paralympic athletes with SCI. We suggest that testing for remaining autonomic function, which is closely related to the degree of cardiovascular control, should be incorporated into sporting classification. Implications for Rehabilitation Spinal cord injury is a debilitating condition that affects the function of almost every physiological system. It is becoming increasingly apparent that spinal cord injury induced changes in autonomic and cardiovascular function are important determinants of sports performance in athletes with spinal cord injury. This study shows that the current sports classification systems used in wheelchair rugby and basketball do not accurately reflect autonomic and cardiovascular function and thus are placing some athletes at a distinct disadvantage/advantage within their respective sport.

Map Classification: A Comparison of Schemes with Special Reference to the Continent of Africa. Occasional Papers, Number 154.

ERIC Educational Resources Information Center

Merrett, Christopher E.

This guide to the theory and practice of map classification begins with a discussion of the filing of maps and the function of map classification based on area and theme as illustrated by four maps of Africa. The description of the various classification systems which follows is divided into book schemes with provision for maps (including Dewey…

A Functional-Phylogenetic Classification System for Transmembrane Solute Transporters

PubMed Central

Saier, Milton H.

2000-01-01

A comprehensive classification system for transmembrane molecular transporters has been developed and recently approved by the transport panel of the nomenclature committee of the International Union of Biochemistry and Molecular Biology. This system is based on (i) transporter class and subclass (mode of transport and energy coupling mechanism), (ii) protein phylogenetic family and subfamily, and (iii) substrate specificity. Almost all of the more than 250 identified families of transporters include members that function exclusively in transport. Channels (115 families), secondary active transporters (uniporters, symporters, and antiporters) (78 families), primary active transporters (23 families), group translocators (6 families), and transport proteins of ill-defined function or of unknown mechanism (51 families) constitute distinct categories. Transport mode and energy coupling prove to be relatively immutable characteristics and therefore provide primary bases for classification. Phylogenetic grouping reflects structure, function, mechanism, and often substrate specificity and therefore provides a reliable secondary basis for classification. Substrate specificity and polarity of transport prove to be more readily altered during evolutionary history and therefore provide a tertiary basis for classification. With very few exceptions, a phylogenetic family of transporters includes members that function by a single transport mode and energy coupling mechanism, although a variety of substrates may be transported, sometimes with either inwardly or outwardly directed polarity. In this review, I provide cross-referencing of well-characterized constituent transporters according to (i) transport mode, (ii) energy coupling mechanism, (iii) phylogenetic grouping, and (iv) substrates transported. The structural features and distribution of recognized family members throughout the living world are also evaluated. The tabulations should facilitate familial and functional assignments of newly sequenced transport proteins that will result from future genome sequencing projects. PMID:10839820

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

Multiprofessional evaluation in clinical practice: establishing a core set of outcome measures for children with cerebral palsy.

PubMed

Mäenpää, Helena; Autti-Rämö, Ilona; Varho, Tarja; Forsten, Wivi; Haataja, Leena

2017-03-01

To develop a national consensus on outcome measures that define functional ability in children with cerebral palsy (CP) according to the International Classification of Functioning, Disability and Health (ICF) framework. The project started in 2008 in neuropaediatric units of two university hospitals and one outpatient clinic. Each professional group selected representatives to be knowledge brokers for their own specialty. Based on the evidence, expert opinion, and the ICF framework, multiprofessional teams selected the most valid measures used in clinical practice (2009-2010). Data from 269 children with CP were analysed, classified by the Gross Motor Function Classification System, Manual Ability Classification System, and Communication Function Classification System, and evaluated. The process aimed at improving and unifying clinical practice in Finland through a national consensus on the core set of measures. The selected measures were presented by professional groups, and consensus was reached on the recommended core set of measures to be used in all hospitals treating children with CP in Finland. A national consensus on relevant and feasible measures is essential for identifying differences in the effectiveness of local practices, and for conducting multisite intervention studies. This project showed that multiprofessional rehabilitation practices can be improved through respect for and inclusion of everyone involved. © 2016 Mac Keith Press.

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.

Return to play after thigh muscle injury in elite football players: implementation and validation of the Munich muscle injury classification

PubMed Central

Ekstrand, Jan; Askling, Carl; Magnusson, Henrik; Mithoefer, Kai

2013-01-01

Background Owing to the complexity and heterogeneity of muscle injuries, a generally accepted classification system is still lacking. Aims To prospectively implement and validate a novel muscle injury classification and to evaluate its predictive value for return to professional football. Methods The recently described Munich muscle injury classification was prospectively evaluated in 31 European professional male football teams during the 2011/2012 season. Thigh muscle injury types were recorded by team medical staff and correlated to individual player exposure and resultant time-loss. Results In total, 393 thigh muscle injuries occurred. The muscle classification system was well received with a 100% response rate. Two-thirds of thigh muscle injuries were classified as structural and were associated with longer lay-off times compared to functional muscle disorders (p<0.001). Significant differences were observed between structural injury subgroups (minor partial, moderate partial and complete injuries) with increasing lay-off time associated with more severe structural injury. Median lay-off time of functional disorders was 5–8 days without significant differences between subgroups. There was no significant difference in the absence time between anterior and posterior thigh injuries. Conclusions The Munich muscle classification demonstrates a positive prognostic validity for return to play after thigh muscle injury in professional male football players. Structural injuries are associated with longer average lay-off times than functional muscle disorders. Subclassification of structural injuries correlates with return to play, while subgrouping of functional disorders shows less prognostic relevance. Functional disorders are often underestimated clinically and require further systematic study. PMID:23645834

The Landscape of long non-coding RNA classification

PubMed Central

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

2015-01-01

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

[CT morphometry for calcaneal fractures and comparison of the Zwipp and Sanders classifications].

PubMed

Andermahr, J; Jesch, A B; Helling, H J; Jubel, A; Fischbach, R; Rehm, K E

2002-01-01

The aim of the study is to correlate the CT-morphological changes of fractured calcaneus and the classifications of Zwipp and Sanders with the clinical outcome. In a retrospective clinical study, the preoperative CT scans of 75 calcaneal fractures were analysed. The morphometry of the fractures was determined by measuring height, length diameter and calcaneo-cuboidal angle in comparison to the intact contralateral side. At a mean of 38 months after trauma 44 patients were clinically followed-up. The data of CT image morphometry were correlated with the severity of fracture classified by Zwipp or Sanders as well as with the functional outcome. There was a good correlation between the fracture classifications and the morphometric data. Both fracture classifying systems have a predictive impact for functional outcome. The more exacting and accurate Zwipp classification considers the most important cofactors like involvement of the calcaneo-cuboidal joint, soft tissue damage, additional fractures etc. The Sanders classification is easier to use during clinical routine. The Zwipp classification includes more relevant cofactors (fracture of the calcaneo-cuboidal-joint, soft tissue swelling, etc.) and presents a higher correlation to the choice of therapy. Both classification systems present a prognostic impact concerning the clinical outcome.

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Use of collateral information to improve LANDSAT classification accuracies

NASA Technical Reports Server (NTRS)

Strahler, A. H. (Principal Investigator)

1981-01-01

Methods to improve LANDSAT classification accuracies were investigated including: (1) the use of prior probabilities in maximum likelihood classification as a methodology to integrate discrete collateral data with continuously measured image density variables; (2) the use of the logit classifier as an alternative to multivariate normal classification that permits mixing both continuous and categorical variables in a single model and fits empirical distributions of observations more closely than the multivariate normal density function; and (3) the use of collateral data in a geographic information system as exercised to model a desired output information layer as a function of input layers of raster format collateral and image data base layers.

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

PubMed

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

2017-12-28

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

The functional therapeutic chemical classification system.

PubMed

Croset, Samuel; Overington, John P; Rebholz-Schuhmann, Dietrich

2014-03-15

Drug repositioning is the discovery of new indications for compounds that have already been approved and used in a clinical setting. Recently, some computational approaches have been suggested to unveil new opportunities in a systematic fashion, by taking into consideration gene expression signatures or chemical features for instance. We present here a novel method based on knowledge integration using semantic technologies, to capture the functional role of approved chemical compounds. In order to computationally generate repositioning hypotheses, we used the Web Ontology Language to formally define the semantics of over 20 000 terms with axioms to correctly denote various modes of action (MoA). Based on an integration of public data, we have automatically assigned over a thousand of approved drugs into these MoA categories. The resulting new resource is called the Functional Therapeutic Chemical Classification System and was further evaluated against the content of the traditional Anatomical Therapeutic Chemical Classification System. We illustrate how the new classification can be used to generate drug repurposing hypotheses, using Alzheimers disease as a use-case. https://www.ebi.ac.uk/chembl/ftc; https://github.com/loopasam/ftc. croset@ebi.ac.uk Supplementary data are available at Bioinformatics online.

Information as Commodity and Economic Sector: Its Emergence in the Discourse of Industrial Classification.

ERIC Educational Resources Information Center

Malone, Cheryl Knott; Elichirigoity, Fernando

2003-01-01

Provides a critical analysis of the development and deployment of the North American Industry Classification System (NAICS), focusing on discourse surrounding creation of the system's "information" category. Suggests that it functions to position information as a major sector of the economy and to organize data about information as a…

Improved wavelet packet classification algorithm for vibrational intrusions in distributed fiber-optic monitoring systems

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Pi, Shaohua; Sun, Qi; Jia, Bo

2015-05-01

An improved classification algorithm that considers multiscale wavelet packet Shannon entropy is proposed. Decomposition coefficients at all levels are obtained to build the initial Shannon entropy feature vector. After subtracting the Shannon entropy map of the background signal, components of the strongest discriminating power in the initial feature vector are picked out to rebuild the Shannon entropy feature vector, which is transferred to radial basis function (RBF) neural network for classification. Four types of man-made vibrational intrusion signals are recorded based on a modified Sagnac interferometer. The performance of the improved classification algorithm has been evaluated by the classification experiments via RBF neural network under different diffusion coefficients. An 85% classification accuracy rate is achieved, which is higher than the other common algorithms. The classification results show that this improved classification algorithm can be used to classify vibrational intrusion signals in an automatic real-time monitoring system.

Improved GART neural network model for pattern classification and rule extraction with application to power systems.

PubMed

Yap, Keem Siah; Lim, Chee Peng; Au, Mau Teng

2011-12-01

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

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.

A "TNM" classification system for cancer pain: the Edmonton Classification System for Cancer Pain (ECS-CP).

PubMed

Fainsinger, Robin L; Nekolaichuk, Cheryl L

2008-06-01

The purpose of this paper is to provide an overview of the development of a "TNM" cancer pain classification system for advanced cancer patients, the Edmonton Classification System for Cancer Pain (ECS-CP). Until we have a common international language to discuss cancer pain, understanding differences in clinical and research experience in opioid rotation and use remains problematic. The complexity of the cancer pain experience presents unique challenges for the classification of pain. To date, no universally accepted pain classification measure can accurately predict the complexity of pain management, particularly for patients with cancer pain that is difficult to treat. In response to this gap in clinical assessment, the Edmonton Staging System (ESS), a classification system for cancer pain, was developed. Difficulties in definitions and interpretation of some aspects of the ESS restricted acceptance and widespread use. Construct, inter-rater reliability, and predictive validity evidence have contributed to the development of the ECS-CP. The five features of the ECS-CP--Pain Mechanism, Incident Pain, Psychological Distress, Addictive Behavior and Cognitive Function--have demonstrated value in predicting pain management complexity. The development of a standardized classification system that is comprehensive, prognostic and simple to use could provide a common language for clinical management and research of cancer pain. An international study to assess the inter-rater reliability and predictive value of the ECS-CP is currently in progress.

Using the manual ability classification system in young adults with cerebral palsy and normal intelligence.

PubMed

van Meeteren, Jetty; Nieuwenhuijsen, Channah; de Grund, Arthur; Stam, Henk J; Roebroeck, Marij E

2010-01-01

The study aimed to establish whether the manual ability classification system (MACS), a valid classification system for manual ability in children with cerebral palsy (CP), is applicable in young adults with CP and normal intelligence. The participants (n = 83) were young adults with CP and normal intelligence and had a mean age of 19.9 years. In this study, inter observer reliability of the MACS was determined. We investigated relationships between the MACS level and patient characteristics (such as the gross motor function classification system (GMFCS) level, limb distribution of the spastic paresis and educational level) and with functional activities of the upper extremity (assessed with the Melbourne assessment, the Abilhand questionnaire and the domain self-care of the functional independence measure (FIM)). Furthermore, with a linear regression analysis it was determined whether the MACS is a significant determinant of activity limitations and participation restrictions. The reliability was good (intraclass correlation coefficient 0.83). The Spearman correlation coefficients with GMFCS level, limb distribution of the spastic paresis and educational level were 0.53, 0.46, and 0.26, respectively. MACS level correlated moderately with outcome measures of functional activities (correlations ranging from -0.38 to -0.55). MACS level is, in addition to the GMFCS level, an important determinant for limitations in activities and restrictions in participation. We conclude that the MACS is a feasible method to classify manual ability in young adults with CP and normal intelligence with a good manual ability.

Adverse events following cervical manipulative therapy: consensus on classification among Dutch medical specialists, manual therapists, and patients.

PubMed

Kranenburg, Hendrikus A; Lakke, Sandra E; Schmitt, Maarten A; Van der Schans, Cees P

2017-12-01

To obtain consensus-based agreement on a classification system of adverse events (AE) following cervical spinal manipulation. The classification system should be comprised of clear definitions, include patients' and clinicians' perspectives, and have an acceptable number of categories. Design : A three-round Delphi study. Participants : Thirty Dutch participants (medical specialists, manual therapists, and patients) participated in an online survey. Procedure : Participants inventoried AE and were asked about their preferences for either a three- or a four-category classification system. The identified AE were classified by two analysts following the International Classification of Functioning, Disability and Health (ICF), and the International Classification of Diseases and Related Health Problems (ICD-10). Participants were asked to classify the severity for all AE in relation to the time duration. Consensus occurred in a three-category classification system. There was strong consensus for 16 AE in all severities (no, minor, and major AE) and all three time durations [hours, days, weeks]. The 16 AE included anxiety, flushing, skin rash, fainting, dizziness, coma, altered sensation, muscle tenderness, pain, increased pain during movement, radiating pain, dislocation, fracture, transient ischemic attack, stroke, and death. Mild to strong consensus was reached for 13 AE. A consensus-based classification system of AE is established which includes patients' and clinicians' perspectives and has three categories. The classification comprises a precise description of potential AE in accordance with internationally accepted classifications. After international validation, clinicians and researchers may use this AE classification system to report AE in clinical practice and research.

Resource utilization groups. A patient classification system for long-term care.

PubMed

Fries, B E; Cooney, L M

1985-02-01

The ability to understand, control, manage, regulate, and reimburse nursing home care has been hampered by the unavailability of a classification system of long-term care patients. A study of 1,469 patients in Connecticut nursing homes has resulted in such a classification system that clusters patients with similar relative needs for resources, in particular, for nursing time. The nine groups formed can be used to develop a case-mix profile of the relative care needs of these patients, and their development demonstrates that only a few measures of the functional status of patients, rather than diagnosis or psychosocial/behavioral problems, are sufficient to form such a system.

Position Between Trunk and Pelvis During Gait Depending on the Gross Motor Function Classification System.

PubMed

Sanz-Mengibar, Jose Manuel; Altschuck, Natalie; Sanchez-de-Muniain, Paloma; Bauer, Christian; Santonja-Medina, Fernando

2017-04-01

To understand whether there is a trunk postural control threshold in the sagittal plane for the transition between the Gross Motor Function Classification System (GMFCS) levels measured with 3-dimensional gait analysis. Kinematics from 97 children with spastic bilateral cerebral palsy from spine angles according to Plug-In Gait model (Vicon) were plotted relative to their GMFCS level. Only average and minimum values of the lumbar spine segment correlated with GMFCS levels. Maximal values at loading response correlated independently with age at all functional levels. Average and minimum values were significant when analyzing age in combination with GMFCS level. There are specific postural control patterns in the average and minimum values for the position between trunk and pelvis in the sagittal plane during gait, for the transition among GMFCS I-III levels. Higher classifications of gross motor skills correlate with more extended spine angles.

A novel clinical decision support system using improved adaptive genetic algorithm for the assessment of fetal well-being.

PubMed

Ravindran, Sindhu; Jambek, Asral Bahari; Muthusamy, Hariharan; Neoh, Siew-Chin

2015-01-01

A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concepts to enhance population diversity. Also, this search algorithm utilizes three different fitness functions (two single objective fitness functions and multi-objective fitness function) to assess its performance. The classification results unfold that promising classification accuracy of 94% is obtained with an optimal feature subset using IAGA. Also, the classification results are compared with those of other Feature Reduction techniques to substantiate its exhaustive search towards the global optimum. Besides, five other benchmark datasets are used to gauge the strength of the proposed IAGA algorithm.

Functional classification of pulmonary hypertension in children: Report from the PVRI pediatric taskforce, Panama 2011.

PubMed

Lammers, Astrid E; Adatia, Ian; Cerro, Maria Jesus Del; Diaz, Gabriel; Freudenthal, Alexandra Heath; Freudenthal, Franz; Harikrishnan, S; Ivy, Dunbar; Lopes, Antonio A; Raj, J Usha; Sandoval, Julio; Stenmark, Kurt; Haworth, Sheila G

2011-08-02

The members of the Pediatric Task Force of the Pulmonary Vascular Research Institute (PVRI) were aware of the need to develop a functional classification of pulmonary hypertension in children. The proposed classification follows the same pattern and uses the same criteria as the Dana Point pulmonary hypertension specific classification for adults. Modifications were necessary for children, since age, physical growth and maturation influences the way in which the functional effects of a disease are expressed. It is essential to encapsulate a child's clinical status, to make it possible to review progress with time as he/she grows up, as consistently and as objectively as possible. Particularly in younger children we sought to include objective indicators such as thriving, need for supplemental feeds and the record of school or nursery attendance. This helps monitor the clinical course of events and response to treatment over the years. It also facilitates the development of treatment algorithms for children. We present a consensus paper on a functional classification system for children with pulmonary hypertension, discussed at the Annual Meeting of the PVRI in Panama City, February 2011.

Deep learning application: rubbish classification with aid of an android device

NASA Astrophysics Data System (ADS)

Liu, Sijiang; Jiang, Bo; Zhan, Jie

2017-06-01

Deep learning is a very hot topic currently in pattern recognition and artificial intelligence researches. Aiming at the practical problem that people usually don't know correct classifications some rubbish should belong to, based on the powerful image classification ability of the deep learning method, we have designed a prototype system to help users to classify kinds of rubbish. Firstly the CaffeNet Model was adopted for our classification network training on the ImageNet dataset, and the trained network was deployed on a web server. Secondly an android app was developed for users to capture images of unclassified rubbish, upload images to the web server for analyzing backstage and retrieve the feedback, so that users can obtain the classification guide by an android device conveniently. Tests on our prototype system of rubbish classification show that: an image of one single type of rubbish with origin shape can be better used to judge its classification, while an image containing kinds of rubbish or rubbish with changed shape may fail to help users to decide rubbish's classification. However, the system still shows promising auxiliary function for rubbish classification if the network training strategy can be optimized further.

Oregon Hydrologic Landscapes: A Classification Framework

EPA Science Inventory

There is a growing need for hydrologic classification systems that can provide a basis for broad-scale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors such as climate change. We developed a hydrologic landscape (HL) classifica...

Using the International Classification of Functioning, Disability and Health Children and Youth version in education systems: a new approach to eligibility.

PubMed

Hollenweger, Judith; Moretti, Marta

2012-02-01

In developed countries, establishing eligibility for persons with disabilities is a requirement for accessing specialized services or benefits. The underlying conceptualizations of disability are often problematic because they concentrate on deficits but try to promote social participation and focus on dependence while trying to strengthen independence. In addition, such conceptualizations are unable to respond to the rights-based approach of the UN Convention on the Rights of Persons with Disabilities. The International Classification of Functioning, Disability and Health Version for Children and Youth provides a model and classification that allows relating disease- or impairment-specific information to participation in the life domains relevant for a specific policy area. Establishing eligibility in education systems needs to be compatible with the principles of inclusive education, participation, and social justice. In addition, the overall goals of education and individualized goals for a specific child with disabilities need to be taken into account. Using the International Classification of Functioning, Disability and Health Version for Children and Youth as a model and classification, the different factors influencing eligibility-related decisions (impairments, activity/participation, environment, personal factors) can be made transparent to provide the basis for a decision-making process to which parents and the child actively contribute.

Classification of Microarray Data Using Kernel Fuzzy Inference System

PubMed Central

Kumar Rath, Santanu

2014-01-01

The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function. PMID:27433543

Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

PubMed Central

Huo, Guanying

2017-01-01

As a typical deep-learning model, Convolutional Neural Networks (CNNs) can be exploited to automatically extract features from images using the hierarchical structure inspired by mammalian visual system. For image classification tasks, traditional CNN models employ the softmax function for classification. However, owing to the limited capacity of the softmax function, there are some shortcomings of traditional CNN models in image classification. To deal with this problem, a new method combining Biomimetic Pattern Recognition (BPR) with CNNs is proposed for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. The proposed method is evaluated on three famous image classification benchmarks, that is, MNIST, AR, and CIFAR-10. The classification accuracies of the proposed method for the three datasets are 99.01%, 98.40%, and 87.11%, respectively, which are much higher in comparison with the other four methods in most cases. PMID:28316614

EUCLID: automatic classification of proteins in functional classes by their database annotations.

PubMed

Tamames, J; Ouzounis, C; Casari, G; Sander, C; Valencia, A

1998-01-01

A tool is described for the automatic classification of sequences in functional classes using their database annotations. The Euclid system is based on a simple learning procedure from examples provided by human experts. Euclid is freely available for academics at http://www.gredos.cnb.uam.es/EUCLID, with the corresponding dictionaries for the generation of three, eight and 14 functional classes. E-mail: valencia@cnb.uam.es The results of the EUCLID classification of different genomes are available at http://www.sander.ebi.ac. uk/genequiz/. A detailed description of the different applications mentioned in the text is available at http://www.gredos.cnb.uam. es/EUCLID/Full_Paper

Wavelet SVM in Reproducing Kernel Hilbert Space for hyperspectral remote sensing image classification

NASA Astrophysics Data System (ADS)

Du, Peijun; Tan, Kun; Xing, Xiaoshi

2010-12-01

Combining Support Vector Machine (SVM) with wavelet analysis, we constructed wavelet SVM (WSVM) classifier based on wavelet kernel functions in Reproducing Kernel Hilbert Space (RKHS). In conventional kernel theory, SVM is faced with the bottleneck of kernel parameter selection which further results in time-consuming and low classification accuracy. The wavelet kernel in RKHS is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. Implications on semiparametric estimation are proposed in this paper. Airborne Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing image with 64 bands and Reflective Optics System Imaging Spectrometer (ROSIS) data with 115 bands were used to experiment the performance and accuracy of the proposed WSVM classifier. The experimental results indicate that the WSVM classifier can obtain the highest accuracy when using the Coiflet Kernel function in wavelet transform. In contrast with some traditional classifiers, including Spectral Angle Mapping (SAM) and Minimum Distance Classification (MDC), and SVM classifier using Radial Basis Function kernel, the proposed wavelet SVM classifier using the wavelet kernel function in Reproducing Kernel Hilbert Space is capable of improving classification accuracy obviously.

The clinical outcomes of deep gray matter injury in children with cerebral palsy in relation with brain magnetic resonance imaging.

PubMed

Choi, Ja Young; Choi, Yoon Seong; Rha, Dong-Wook; Park, Eun Sook

2016-08-01

In the present study we investigated the nature and extent of clinical outcomes using various classifications and analyzed the relationship between brain magnetic resonance imaging (MRI) findings and the extent of clinical outcomes in children with cerebral palsy (CP) with deep gray matter injury. The deep gray matter injuries of 69 children were classified into hypoxic ischemic encephalopathy (HIE) and kernicterus patterns. HIE patterns were divided into four groups (I-IV) based on severity. Functional classification was investigated using the gross motor function classification system-expanded and revised, manual ability classification system, communication function classification system, and tests of cognitive function, and other associated problems. The severity of HIE pattern on brain MRI was strongly correlated with the severity of clinical outcomes in these various domains. Children with a kernicterus pattern showed a wide range of clinical outcomes in these areas. Children with severe HIE are at high risk of intellectual disability (ID) or epilepsy and children with a kernicterus pattern are at risk of hearing impairment and/or ID. Grading severity of HIE pattern on brain MRI is useful for predicting overall outcomes. The clinical outcomes of children with a kernicterus pattern range widely from mild to severe. Delineation of the clinical outcomes of children with deep gray matter injury, which are a common abnormal brain MRI finding in children with CP, is necessary. The present study provides clinical outcomes for various domains in children with deep gray matter injury on brain MRI. The deep gray matter injuries were divided into two major groups; HIE and kernicterus patterns. Our study showed that severity of HIE pattern on brain MRI was strongly associated with the severity of impairments in gross motor function, manual ability, communication function, and cognition. These findings suggest that severity of HIE pattern can be useful for predicting the severity of impairments. Conversely, children with a kernicterus pattern showed a wide range of clinical outcomes in various domains. Children with severe HIE pattern are at high risk of ID or epilepsy and children with kernicterus pattern are at risk of hearing impairment or ID. The strength of our study was the assessment of clinical outcomes after 3 years of age using standardized classification systems in various domains in children with deep gray matter injury. Copyright © 2016 Elsevier Ltd. All rights reserved.

An evidence-based diagnostic classification system for low back pain

PubMed Central

Vining, Robert; Potocki, Eric; Seidman, Michael; Morgenthal, A. Paige

2013-01-01

Introduction: While clinicians generally accept that musculoskeletal low back pain (LBP) can arise from specific tissues, it remains difficult to confirm specific sources. Methods: Based on evidence supported by diagnostic utility studies, doctors of chiropractic functioning as members of a research clinic created a diagnostic classification system, corresponding exam and checklist based on strength of evidence, and in-office efficiency. Results: The diagnostic classification system contains one screening category, two pain categories: Nociceptive, Neuropathic, one functional evaluation category, and one category for unknown or poorly defined diagnoses. Nociceptive and neuropathic pain categories are each divided into 4 subcategories. Conclusion: This article describes and discusses the strength of evidence surrounding diagnostic categories for an in-office, clinical exam and checklist tool for LBP diagnosis. The use of a standardized tool for diagnosing low back pain in clinical and research settings is encouraged. PMID:23997245

Portugal's special education law: implementing the International Classification of Functioning, Disability and Health in policy and practice.

PubMed

Sanches-Ferreira, Manuela; Simeonsson, Rune J; Silveira-Maia, Mónica; Alves, Sílvia; Tavares, Ana; Pinheiro, Sara

2013-05-01

The International Classification of Functioning, Disability and Health (ICF) was introduced in Portuguese education law as the compulsory system to guide eligibility policy and practice in special education. This paper describes the implementation of the ICF and its utility in the assessment process and eligibility determination of students for special education. A study to evaluate the utility of the ICF was commissioned by the Portuguese Ministry of Education and carried out by an external evaluation team. A document analysis was made of the assessment and eligibility processes of 237 students, selected from a nationally representative sample. The results provided support for the use of the ICF in student assessment and in the multidimensional approach of generating student functioning profiles as the basis for determining eligibility. The use of the ICF contributed to the differentiation of eligible and non eligible students based on their functioning profiles. The findings demonstrate the applicability of the ICF framework and classification system for determining eligibility for special education services on the basis of student functioning rather than medical or psychological diagnose. The use of the International Classification of Functioning, Disability and Health (ICF) framework in special education policy is as follows: • The functional perspective of the ICF offers a more comprehensive, holistic assessment of student needs than medical diagnoses. • ICF-based assessment of the nature and severity of functioning can serve as the basis for determining eligibility for special education and habilitation. • Profiles of functioning can support decision making in designing appropriate educational interventions for students.

Ototoxicity (cochleotoxicity) classifications: A review.

PubMed

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

2016-01-01

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

Oregon Hydrologic Landscapes: An Approach for Broadscale Hydrologic Classification

EPA Science Inventory

Gaged streams represent only a small percentage of watershed hydrologic conditions throughout the Unites States and globe, but there is a growing need for hydrologic classification systems that can serve as the foundation for broad-scale assessments of the hydrologic functions of...

On-board multispectral classification study. Volume 2: Supplementary tasks. [adaptive control

NASA Technical Reports Server (NTRS)

Ewalt, D.

1979-01-01

The operational tasks of the onboard multispectral classification study were defined. These tasks include: sensing characteristics for future space applications; information adaptive systems architectural approaches; data set selection criteria; and onboard functional requirements for interfacing with global positioning satellites.

[The functional state classification and evaluation of the stability level in mental loads based on the factor structure of heart rate variability parameters].

PubMed

Mashin, V A; Mashina, M N

2004-12-01

In the paper, outcomes of the researches devoted to factor analysis of heart rate variability parameters and definition of the most informative parameters for diagnostics of functional states and an evaluation of level of stability to mental loads, are presented. The factor structure of parameters, which unclude integral level of heart rate variability (1), balance between activity of vagus and brain cortical-limbic systems (2), integrated level of cardiovascular system functioning (3), is substantiated. Factor analysis outcomes have been used for construction of functional state classification, for their differential diagnostics, and for development and check of algorithm for evaluation of the stability level in mental loads.

Perceptual-motor skill learning in Gilles de la Tourette syndrome. Evidence for multiple procedural learning and memory systems.

PubMed

Marsh, Rachel; Alexander, Gerianne M; Packard, Mark G; Zhu, Hongtu; Peterson, Bradley S

2005-01-01

Procedural learning and memory systems likely comprise several skills that are differentially affected by various illnesses of the central nervous system, suggesting their relative functional independence and reliance on differing neural circuits. Gilles de la Tourette syndrome (GTS) is a movement disorder that involves disturbances in the structure and function of the striatum and related circuitry. Recent studies suggest that patients with GTS are impaired in performance of a probabilistic classification task that putatively involves the acquisition of stimulus-response (S-R)-based habits. Assessing the learning of perceptual-motor skills and probabilistic classification in the same samples of GTS and healthy control subjects may help to determine whether these various forms of procedural (habit) learning rely on the same or differing neuroanatomical substrates and whether those substrates are differentially affected in persons with GTS. Therefore, we assessed perceptual-motor skill learning using the pursuit-rotor and mirror tracing tasks in 50 patients with GTS and 55 control subjects who had previously been compared at learning a task of probabilistic classifications. The GTS subjects did not differ from the control subjects in performance of either the pursuit rotor or mirror-tracing tasks, although they were significantly impaired in the acquisition of a probabilistic classification task. In addition, learning on the perceptual-motor tasks was not correlated with habit learning on the classification task in either the GTS or healthy control subjects. These findings suggest that the differing forms of procedural learning are dissociable both functionally and neuroanatomically. The specific deficits in the probabilistic classification form of habit learning in persons with GTS are likely to be a consequence of disturbances in specific corticostriatal circuits, but not the same circuits that subserve the perceptual-motor form of habit learning.

Promoting consistent use of the communication function classification system (CFCS).

PubMed

Cunningham, Barbara Jane; Rosenbaum, Peter; Hidecker, Mary Jo Cooley

2016-01-01

We developed a Knowledge Translation (KT) intervention to standardize the way speech-language pathologists working in Ontario Canada's Preschool Speech and Language Program (PSLP) used the Communication Function Classification System (CFCS). This tool was being used as part of a provincial program evaluation and standardizing its use was critical for establishing reliability and validity within the provincial dataset. Two theoretical foundations - Diffusion of Innovations and the Communication Persuasion Matrix - were used to develop and disseminate the intervention to standardize use of the CFCS among a cohort speech-language pathologists. A descriptive pre-test/post-test study was used to evaluate the intervention. Fifty-two participants completed an electronic pre-test survey, reviewed intervention materials online, and then immediately completed an electronic post-test survey. The intervention improved clinicians' understanding of how the CFCS should be used, their intentions to use the tool in the standardized way, and their abilities to make correct classifications using the tool. Findings from this work will be shared with representatives of the Ontario PSLP. The intervention may be disseminated to all speech-language pathologists working in the program. This study can be used as a model for developing and disseminating KT interventions for clinicians in paediatric rehabilitation. The Communication Function Classification System (CFCS) is a new tool that allows speech-language pathologists to classify children's skills into five meaningful levels of function. There is uncertainty and inconsistent practice in the field about the methods for using this tool. This study used combined two theoretical frameworks to develop an intervention to standardize use of the CFCS among a cohort of speech-language pathologists. The intervention effectively increased clinicians' understanding of the methods for using the CFCS, ability to make correct classifications, and intention to use the tool in the standardized way in the future.

CHANGING OUR DIAGNOSTIC PARADIGM: MOVEMENT SYSTEM DIAGNOSTIC CLASSIFICATION

PubMed Central

Kamonseki, Danilo H.; Staker, Justin L.; Lawrence, Rebekah L.; Braman, Jonathan P.

2017-01-01

Proper diagnosis is a first step in applying best available treatments, and prognosticating outcomes for clients. Currently, the majority of musculoskeletal diagnoses are classified according to pathoanatomy. However, the majority of physical therapy treatments are applied toward movement system impairments or pain. While advocated within the physical therapy profession for over thirty years, diagnostic classification within a movement system framework has not been uniformly developed or adopted. We propose a basic framework and rationale for application of a movement system diagnostic classification for atraumatic shoulder pain conditions, as a case for the broader development of movement system diagnostic labels. Shifting our diagnostic paradigm has potential to enhance communication, improve educational efficiency, facilitate research, directly link to function, improve clinical care, and accelerate preventive interventions. PMID:29158950

A statistical approach to root system classification

PubMed Central

Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

2013-01-01

Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for “plant functional type” identification in ecology can be applied to the classification of root systems. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems) is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement techniques are essential. PMID:23914200

A statistical approach to root system classification.

PubMed

Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

2013-01-01

Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for "plant functional type" identification in ecology can be applied to the classification of root systems. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems) is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement techniques are essential.

A modular case-mix classification system for medical rehabilitation illustrated.

PubMed

Stineman, M G; Granger, C V

1997-01-01

The authors present a modular set of patient classification systems designed for medical rehabilitation that predict resource use and outcomes for clinically similar groups of individuals. The systems, based on the Functional Independence Measure, are referred to as Function-Related Groups (FIM-FRGs). Using data from 23,637 lower extremity fracture patients from 458 inpatient medical rehabilitation facilities, 1995 benchmarks are provided and illustrated for length of stay, functional outcome, and discharge to home and skilled nursing facilities (SNFs). The FIM-FRG modules may be used in parallel to study interactions between resource use and quality and could ultimately yield an integrated strategy for payment and outcomes measurement. This could position the rehabilitation community to take a pioneering role in the application of outcomes-based clinical indicators.

[The use of "cognitive" in health terminology. A latent controversy].

PubMed

Salvador-Carulla, Luis; Aguilera, Francisco

2010-10-01

The adjective «cognitive» has a double meaning and it is used for naming two disciplines with separate activities: Cognitive neuroscience and cognitive psychotherapy. This has an unrecognised impact on the health terminology and the classification systems. The current use of this term is reviewed in a series of key dictionaries, scientific books, databases (OldMedline and PsycINFO) and specific web searchers (Google Scholar). The history of this term and its etymology is also reviewed and compared to other alternatives (i.e. noetic) as well as its use in international classifications (e.g. the International Classification of Functioning - ICF). The modern use of the term «cognitive» in Neurosciences can be traced back to Hebb in a 1955 one year before that recorded at official version. The different meaning of this term in psychology can be traced back to the same decade. Departing from the ICF framework of mental functions, «cognitive» can be regarded as a generic term that encompasses both neurocognitive and meta-cognitive functions and should not be used for classification purposes. A hierarchy is suggested for the use of «neurocognitive» in the classification of mental functions. The polysemic use of this name reveals a latent controversy in health sciences which has implications for its use in the international classification systems. There is an need to improve the standard definition and the semantic hierarchy of the term «cognitive», «neurocognitive» and other related terms within the context of International Health Terminology Standards Development Organisation (IHTSO). Copyright © 2010 SEP y SEPB. Published by Elsevier Espana. All rights reserved.

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

PubMed

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

2012-10-15

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

Classification and Subject Cataloguing Section. Bibliographic Control Division. Papers.

ERIC Educational Resources Information Center

International Federation of Library Associations, The Hague (Netherlands).

Papers on classification and subject cataloging which were presented at the 1983 International Federation of Library Associations (IFLA) conference include: (1) "PRECIS: Basic Principles, Function, and Use," in which Derek Austin (United Kingdom) describes the automated subject indexing system developed for use in the "British…

13 CFR 124.3 - What definitions are important in the 8(a) BD program?

Code of Federal Regulations, 2013 CFR

2013-01-01

... the marketing, production, sales, and administrative functions of the firm. Immediate family member... Native Hawaiians. Negative control is defined in part 121 of this title. Non-disadvantaged individual.... Primary industry classification means the six digit North American Industry Classification System (NAICS...

13 CFR 124.3 - What definitions are important in the 8(a) BD program?

Code of Federal Regulations, 2012 CFR

2012-01-01

... the marketing, production, sales, and administrative functions of the firm. Immediate family member... Native Hawaiians. Negative control is defined in part 121 of this title. Non-disadvantaged individual.... Primary industry classification means the six digit North American Industry Classification System (NAICS...

Developing a dementia-specific health state classification system for a new preference-based instrument AD-5D.

PubMed

Nguyen, Kim-Huong; Mulhern, Brendan; Kularatna, Sanjeewa; Byrnes, Joshua; Moyle, Wendy; Comans, Tracy

2017-01-25

With an ageing population, the number of people with dementia is rising. The economic impact on the health care system is considerable and new treatment methods and approaches to dementia care must be cost effective. Economic evaluation requires valid patient reported outcome measures, and this study aims to develop a dementia-specific health state classification system based on the Quality of Life for Alzheimer's disease (QOL-AD) instrument (nursing home version). This classification system will subsequently be valued to generate a preference-based measure for use in the economic evaluation of interventions for people with dementia. We assessed the dimensionality of the QOL-AD to develop a new classification system. This was done using exploratory and confirmatory factor analysis and further assessment of the structure of the measure to ensure coverage of the key areas of quality of life. Secondly, we used Rasch analysis to test the psychometric performance of the items, and select item(s) to describe each dimension. This was done on 13 items of the QOL-AD (excluding two general health items) using a sample of 284 residents living in long-term care facilities in Australia who had a diagnosis of dementia. A five dimension classification system is proposed resulting from the three factor structure (defined as 'interpersonal environment', 'physical health' and 'self-functioning') derived from the factor analysis and two factors ('memory' and 'mood') from the accompanying review. For the first three dimensions, Rasch analysis selected three questions of the QOL-AD ('living situation', 'physical health', and 'do fun things') with memory and mood questions representing their own dimensions. The resulting classification system (AD-5D) includes many of the health-related quality of life dimensions considered important to people with dementia, including mood, global function and skill in daily living. The development of the AD-5D classification system is an important step in the future application of the widely used QOL-AD in economic evaluations. Future valuation studies will enable this tool to be used to calculate quality adjusted life years to evaluate treatments and interventions for people diagnosed with mild to moderate dementia.

PREDICT-CP: study protocol of implementation of comprehensive surveillance to predict outcomes for school-aged children with cerebral palsy

PubMed Central

Boyd, Roslyn N; Davies, Peter SW; Ziviani, Jenny; Trost, Stewart; Barber, Lee; Ware, Robert; Rose, Stephen; Whittingham, Koa; Bell, Kristie; Carty, Christopher; Obst, Steven; Benfer, Katherine; Reedman, Sarah; Edwards, Priya; Kentish, Megan; Copeland, Lisa; Weir, Kelly; Davenport, Camilla; Brooks, Denise; Coulthard, Alan; Pelekanos, Rebecca; Guzzetta, Andrea; Fiori, Simona; Wynter, Meredith; Finn, Christine; Burgess, Andrea; Morris, Kym; Walsh, John; Lloyd, Owen; Whitty, Jennifer A; Scuffham, Paul A

2017-01-01

Objectives Cerebral palsy (CP) remains the world’s most common childhood physical disability with total annual costs of care and lost well-being of $A3.87b. The PREDICT-CP (NHMRC 1077257 Partnership Project: Comprehensive surveillance to PREDICT outcomes for school age children with CP) study will investigate the influence of brain structure, body composition, dietary intake, oropharyngeal function, habitual physical activity, musculoskeletal development (hip status, bone health) and muscle performance on motor attainment, cognition, executive function, communication, participation, quality of life and related health resource use costs. The PREDICT-CP cohort provides further follow-up at 8–12 years of two overlapping preschool-age cohorts examined from 1.5 to 5 years (NHMRC 465128 motor and brain development; NHMRC 569605 growth, nutrition and physical activity). Methods and analyses This population-based cohort study undertakes state-wide surveillance of 245 children with CP born in Queensland (birth years 2006–2009). Children will be classified for Gross Motor Function Classification System; Manual Ability Classification System, Communication Function Classification System and Eating and Drinking Ability Classification System. Outcomes include gross motor function, musculoskeletal development (hip displacement, spasticity, muscle contracture), upper limb function, communication difficulties, oropharyngeal dysphagia, dietary intake and body composition, participation, parent-reported and child-reported quality of life and medical and allied health resource use. These detailed phenotypical data will be compared with brain macrostructure and microstructure using 3 Tesla MRI (3T MRI). Relationships between brain lesion severity and outcomes will be analysed using multilevel mixed-effects models. Ethics and dissemination The PREDICT-CP protocol is a prospectively registered and ethically accepted study protocol. The study combines data at 1.5–5 then 8–12 years of direct clinical assessment to enable prediction of outcomes and healthcare needs essential for tailoring interventions (eg, rehabilitation, orthopaedic surgery and nutritional supplements) and the projected healthcare utilisation. Trial registration number ACTRN: 12616001488493 PMID:28706091

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

NASA Astrophysics Data System (ADS)

Krupp, Alexander; Müller, Wolfgang

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

A neuromorphic network for generic multivariate data classification

PubMed Central

Schmuker, Michael; Pfeil, Thomas; Nawrot, Martin Paul

2014-01-01

Computational neuroscience has uncovered a number of computational principles used by nervous systems. At the same time, neuromorphic hardware has matured to a state where fast silicon implementations of complex neural networks have become feasible. En route to future technical applications of neuromorphic computing the current challenge lies in the identification and implementation of functional brain algorithms. Taking inspiration from the olfactory system of insects, we constructed a spiking neural network for the classification of multivariate data, a common problem in signal and data analysis. In this model, real-valued multivariate data are converted into spike trains using “virtual receptors” (VRs). Their output is processed by lateral inhibition and drives a winner-take-all circuit that supports supervised learning. VRs are conveniently implemented in software, whereas the lateral inhibition and classification stages run on accelerated neuromorphic hardware. When trained and tested on real-world datasets, we find that the classification performance is on par with a naïve Bayes classifier. An analysis of the network dynamics shows that stable decisions in output neuron populations are reached within less than 100 ms of biological time, matching the time-to-decision reported for the insect nervous system. Through leveraging a population code, the network tolerates the variability of neuronal transfer functions and trial-to-trial variation that is inevitably present on the hardware system. Our work provides a proof of principle for the successful implementation of a functional spiking neural network on a configurable neuromorphic hardware system that can readily be applied to real-world computing problems. PMID:24469794

A classification of ecological boundaries

USGS Publications Warehouse

Strayer, D.L.; Power, M.E.; Fagan, W.F.; Pickett, S.T.A.; Belnap, J.

2003-01-01

Ecologists use the term boundary to refer to a wide range of real and conceptual structures. Because imprecise terminology may impede the search for general patterns and theories about ecological boundaries, we present a classification of the attributes of ecological boundaries to aid in communication and theory development. Ecological boundaries may differ in their origin and maintenance, their spatial structure, their function, and their temporal dynamics. A classification system based on these attributes should help ecologists determine whether boundaries are truly comparable. This system can be applied when comparing empirical studies, comparing theories, and testing theoretical predictions against empirical results.

Muscle Injuries in Sports: A New Evidence-Informed and Expert Consensus-Based Classification with Clinical Application.

PubMed

Valle, Xavier; Alentorn-Geli, Eduard; Tol, Johannes L; Hamilton, Bruce; Garrett, William E; Pruna, Ricard; Til, Lluís; Gutierrez, Josep Antoni; Alomar, Xavier; Balius, Ramón; Malliaropoulos, Nikos; Monllau, Joan Carles; Whiteley, Rodney; Witvrouw, Erik; Samuelsson, Kristian; Rodas, Gil

2017-07-01

Muscle injuries are among the most common injuries in sport and continue to be a major concern because of training and competition time loss, challenging decision making regarding treatment and return to sport, and a relatively high recurrence rate. An adequate classification of muscle injury is essential for a full understanding of the injury and to optimize its management and return-to-play process. The ongoing failure to establish a classification system with broad acceptance has resulted from factors such as limited clinical applicability, and the inclusion of subjective findings and ambiguous terminology. The purpose of this article was to describe a classification system for muscle injuries with easy clinical application, adequate grouping of injuries with similar functional impairment, and potential prognostic value. This evidence-informed and expert consensus-based classification system for muscle injuries is based on a four-letter initialism system: MLG-R, respectively referring to the mechanism of injury (M), location of injury (L), grading of severity (G), and number of muscle re-injuries (R). The goal of the classification is to enhance communication between healthcare and sports-related professionals and facilitate rehabilitation and return-to-play decision making.

The Functional Classification of Brain Damage-Related Vision Loss

ERIC Educational Resources Information Center

Colenbrander, August

2009-01-01

This article provides a terminological framework to show the relationships among different types of visual deficits. It distinguishes between visual functions, which describe how the eye and the lower visual system function, and functional vision, which describes how a person functions. When visual functions are disturbed, the term "visual…

Classification of weld defect based on information fusion technology for radiographic testing system

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

Jiang, Hongquan; Liang, Zeming, E-mail: heavenlzm@126.com; Gao, Jianmin

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster–Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defectmore » feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.« less

Classification of weld defect based on information fusion technology for radiographic testing system.

PubMed

Jiang, Hongquan; Liang, Zeming; Gao, Jianmin; Dang, Changying

2016-03-01

Improving the efficiency and accuracy of weld defect classification is an important technical problem in developing the radiographic testing system. This paper proposes a novel weld defect classification method based on information fusion technology, Dempster-Shafer evidence theory. First, to characterize weld defects and improve the accuracy of their classification, 11 weld defect features were defined based on the sub-pixel level edges of radiographic images, four of which are presented for the first time in this paper. Second, we applied information fusion technology to combine different features for weld defect classification, including a mass function defined based on the weld defect feature information and the quartile-method-based calculation of standard weld defect class which is to solve a sample problem involving a limited number of training samples. A steam turbine weld defect classification case study is also presented herein to illustrate our technique. The results show that the proposed method can increase the correct classification rate with limited training samples and address the uncertainties associated with weld defect classification.

Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

PubMed

Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

2013-08-01

Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

Classification of ligand molecules in PDB with graph match-based structural superposition.

PubMed

Shionyu-Mitsuyama, Clara; Hijikata, Atsushi; Tsuji, Toshiyuki; Shirai, Tsuyoshi

2016-12-01

The fast heuristic graph match algorithm for small molecules, COMPLIG, was improved by adding a structural superposition process to verify the atom-atom matching. The modified method was used to classify the small molecule ligands in the Protein Data Bank (PDB) by their three-dimensional structures, and 16,660 types of ligands in the PDB were classified into 7561 clusters. In contrast, a classification by a previous method (without structure superposition) generated 3371 clusters from the same ligand set. The characteristic feature in the current classification system is the increased number of singleton clusters, which contained only one ligand molecule in a cluster. Inspections of the singletons in the current classification system but not in the previous one implied that the major factors for the isolation were differences in chirality, cyclic conformations, separation of substructures, and bond length. Comparisons between current and previous classification systems revealed that the superposition-based classification was effective in clustering functionally related ligands, such as drugs targeted to specific biological processes, owing to the strictness of the atom-atom matching.

Particle Swarm Optimization approach to defect detection in armour ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2017-03-01

In this research, various extracted features were used in the development of an automated ultrasonic sensor based inspection system that enables defect classification in each ceramic component prior to despatch to the field. Classification is an important task and large number of irrelevant, redundant features commonly introduced to a dataset reduces the classifiers performance. Feature selection aims to reduce the dimensionality of the dataset while improving the performance of a classification system. In the context of a multi-criteria optimization problem (i.e. to minimize classification error rate and reduce number of features) such as one discussed in this research, the literature suggests that evolutionary algorithms offer good results. Besides, it is noted that Particle Swarm Optimization (PSO) has not been explored especially in the field of classification of high frequency ultrasonic signals. Hence, a binary coded Particle Swarm Optimization (BPSO) technique is investigated in the implementation of feature subset selection and to optimize the classification error rate. In the proposed method, the population data is used as input to an Artificial Neural Network (ANN) based classification system to obtain the error rate, as ANN serves as an evaluator of PSO fitness function. Copyright © 2016. Published by Elsevier B.V.

Predicting functional communication ability in children with cerebral palsy at school entry.

PubMed

Coleman, Andrea; Weir, Kelly; Ware, Robert S; Boyd, Roslyn

2015-03-01

To explore the value of demographic, environmental, and early clinical characteristics in predicting functional communication in children with cerebral palsy (CP) at school entry. Data are from an Australian prospective longitudinal study of children with CP. Children assessed at 18 to 24 and 48 to 60 months corrected age were included in the study. Functional communication was classified at 48 to 60 months using the Communication Function Classification System (CFCS). Predictive variables included communication skills at 18 to 24 months, evaluated using the Communication and Symbolic Behavioural Scales Developmental Profile (CSBS-DP) Infant-Toddler Checklist. Early Gross Motor Function Classification System (GMFCS), Manual Ability Classification System, and motor type and distribution were evaluated by two physiotherapists. Demographic and comorbid variables were obtained through parent interview with a paediatrician or rehabilitation specialist. A total of 114 children (76 males, 38 females) were included in the study. At 18 to 24 months the mean CSBS-DP was 84.9 (SD 19.0). The CFCS distribution at 48 to 60 months was I=36(32%), II=25(22%), III=20(18%), IV=19(17%), and V=14(12%). In multivariable regression analysis, only CSBS-DP (p<0.01) and GMFCS (p<0.01) at 18 to 24 months were predictors of functional communication at school entry. Body structure and function and not environmental factors impact functional communication at school entry in children with CP. This provides valuable guidance for early screening, parent education, and future planning of intervention programs to improve functional communication. © 2014 Mac Keith Press.

Development of soil taxation and soil classification as furthered by the Austrian Soil Science Society

NASA Astrophysics Data System (ADS)

Baumgarten, Andreas

2013-04-01

Soil taxation and soil classification are important drivers of soil science in Austria. However, the tasks are quite different: whereas soil taxation aims at the evaluation of the productivity potential of the soil, soil classification focusses on the natural development and - especially nowadays - on functionality of the soil. Since the foundation of the Austrian Soil Science Society (ASSS), representatives both directions of the description of the soil have been involved in the common actions of the society. In the first years it was a main target to improve and standardize field descriptions of the soil. Although both systems differ in the general layout, the experts should comply with identical approaches. According to this work, a lot of effort has been put into the standardization of the soil classification system, thus ensuring a common basis. The development, state of the art and further development of both classification and taxation systems initiated and carried out by the ASSS will be shown.

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

Looking at the ICF and human communication through the lens of classification theory.

PubMed

Walsh, Regina

2011-08-01

This paper explores the insights that classification theory can provide about the application of the International Classification of Functioning, Disability and Health (ICF) to communication. It first considers the relationship between conceptual models and classification systems, highlighting that classification systems in speech-language pathology (SLP) have not historically been based on conceptual models of human communication. It then overviews the key concepts and criteria of classification theory. Applying classification theory to the ICF and communication raises a number of issues, some previously highlighted through clinical application. Six focus questions from classification theory are used to explore these issues, and to propose the creation of an ICF-related conceptual model of communicating for the field of communication disability, which would address some of the issues raised. Developing a conceptual model of communication for SLP purposes closely articulated with the ICF would foster productive intra-professional discourse, while at the same time allow the profession to continue to use the ICF for purposes in inter-disciplinary discourse. The paper concludes by suggesting the insights of classification theory can assist professionals to apply the ICF to communication with the necessary rigour, and to work further in developing a conceptual model of human communication.

Integrative analysis of environmental sequences using MEGAN4.

PubMed

Huson, Daniel H; Mitra, Suparna; Ruscheweyh, Hans-Joachim; Weber, Nico; Schuster, Stephan C

2011-09-01

A major challenge in the analysis of environmental sequences is data integration. The question is how to analyze different types of data in a unified approach, addressing both the taxonomic and functional aspects. To facilitate such analyses, we have substantially extended MEGAN, a widely used taxonomic analysis program. The new program, MEGAN4, provides an integrated approach to the taxonomic and functional analysis of metagenomic, metatranscriptomic, metaproteomic, and rRNA data. While taxonomic analysis is performed based on the NCBI taxonomy, functional analysis is performed using the SEED classification of subsystems and functional roles or the KEGG classification of pathways and enzymes. A number of examples illustrate how such analyses can be performed, and show that one can also import and compare classification results obtained using others' tools. MEGAN4 is freely available for academic purposes, and installers for all three major operating systems can be downloaded from www-ab.informatik.uni-tuebingen.de/software/megan.

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.

Effects of different seating equipment on postural control and upper extremity function in children with cerebral palsy.

PubMed

Sahinoğlu, Dilek; Coskun, Gürsoy; Bek, Nilgün

2017-02-01

Adaptive seating supports for cerebral palsy are recommended to develop and maintain optimum posture, and functional use of upper extremities. To compare the effectiveness of different seating adaptations regarding postural alignment and related functions and to investigate the effects of these seating adaptations on different motor levels. Prospective study. A total of 20 children with spastic cerebral palsy (Gross Motor Function Classification System 3-5) were included. Postural control and function (Seated Postural Control Measure, Sitting Assessment Scale) were measured in three different systems: standard chair, adjustable seating system and custom-made orthosis. In results of all participants ungrouped, there was a significant difference in most parameters of both measurement tools in favor of custom-made orthosis and adjustable seating system when compared to standard chair ( p < 0.0017). There was a difference among interventions in most of the Seated Postural Control Measure results in Level 4 when subjects were grouped according to Gross Motor Function Classification System levels. A difference was observed between standard chair and adjustable seating system in foot control, arm control, and total Sitting Assessment Scale scores; and between standard chair and custom-made orthosis in trunk control, arm control, and total Sitting Assessment Scale score in Level 4. There was no difference in adjustable seating system and custom-made orthosis in Sitting Assessment Scale in this group of children ( p < 0.017). Although custom-made orthosis fabrication is time consuming, it is still recommended since it is custom made, easy to use, and low-cost. On the other hand, the adjustable seating system can be modified according to a patient's height and weight. Clinical relevance It was found that Gross Motor Function Classification System Level 4 children benefitted most from the seating support systems. It was presented that standard chair is sufficient in providing postural alignment. Both custom-made orthosis and adjustable seating system have pros and cons and the best solution for each will be dependent on a number of factors.

Classification of "multipole" superconductivity in multiorbital systems and its implications

NASA Astrophysics Data System (ADS)

Nomoto, T.; Hattori, K.; Ikeda, H.

2016-11-01

Motivated by a growing interest in multiorbital superconductors with spin-orbit interactions, we perform the group-theoretical classification of various unconventional superconductivity emerging in symmorphic O , D4, and D6 space groups. The generalized Cooper pairs, which we here call "multipole" superconductivity, possess spin-orbital coupled (multipole) degrees of freedom, instead of the conventional spin singlet/triplet in single-orbital systems. From the classification, we obtain the following key consequences, which have never been focused in the long history of research in this field: (1) A superconducting gap function with Γ9⊗Γ9 in D6 possesses nontrivial momentum dependence different from the usual spin-1/2 classification. (2) Unconventional gap structure can be realized in the BCS approximation of purely local (onsite) interactions irrespective of attraction/repulsion. It implies the emergence of an electron-phonon (e-ph) driven unconventional superconductivity. (3) Reflecting symmetry of orbital basis functions there appear not symmetry protected but inevitable line nodes/gap minima, and thus, anisotropic s -wave superconductivity can be naturally explained even in the absence of competing fluctuations.

Bimanual Fine Motor Function (BFMF) Classification in Children with Cerebral Palsy: Aspects of Construct and Content Validity.

PubMed

Elvrum, Ann-Kristin G; Andersen, Guro L; Himmelmann, Kate; Beckung, Eva; Öhrvall, Ann-Marie; Lydersen, Stian; Vik, Torstein

2016-01-01

The Bimanual Fine Motor Function (BFMF) is currently the principal classification of hand function recorded by the Surveillance of Cerebral Palsy in Europe (SCPE) register. The BFMF is used in a number of epidemiological studies, but has not yet been validated. To examine aspects of construct and content validity of the BFMF. Construct validity of the BFMF was assessed by comparison with the Manual Ability Classification System (MACS) using register-based data from 539 children born 1999-2003 (304 boys; 4-12 years). The high correlation with the MACS (Spearman's rho = 0.89, CI: 0.86-0.91, p<.001) supports construct validity of the BFMF. The content of the BFMF was appraised through literature review, and by using the ICF-CY as a framework to compare the BFMF and MACS. The items hold, grasp and manipulate were found to be relevant to describe increasingly advanced fine motor abilities in children with CP, but the description of the BFMF does not state whether it is a classification of fine motor capacity or performance. Our results suggest that the BFMF may provide complementary information to the MACS regarding fine motor function and actual use of the hands, particularly if used as a classification of fine motor capacity.

A bioturbation classification of European marine infaunal invertebrates

PubMed Central

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

2013-01-01

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

A two-layered classifier based on the radial basis function for the screening of thalassaemia.

PubMed

Masala, G L; Golosio, B; Cutzu, R; Pola, R

2013-11-01

The thalassaemias are blood disorders with hereditary transmission. Their distribution is global, with particular incidence in areas affected by malaria. Their diagnosis is mainly based on haematologic and genetic analyses. The aim of this study was to differentiate between persons with the thalassaemia trait and normal subjects by inspecting characteristics of haemochromocytometric data. The paper proposes an original method that is useful in screening activity for thalassaemia classification. A complete working system with a friendly graphical user interface is presented. A unique feature of the presented work is the adoption of a two-layered classification system based on Radial basis function, which improves the performance of the system. © 2013 Elsevier Ltd. All rights reserved.

[The physiological classification of human thermal states under high environmental temperatures].

PubMed

Bobrov, A F; Kuznets, E I

1995-01-01

The paper deals with the physiological classification of human thermal states in a hot environment. A review of the basic systems of classifications of thermal states is given, their main drawbacks are discussed. On the basis of human functional state research in a broad range of environmental temperatures the system of evaluation and classification of human thermal states is proposed. New integral one-dimensional multi-parametric criteria for evaluation are used. For the development of these criteria methods of factor, cluster and canonical correlation analyses are applied. Stochastic nomograms capable of identification of human thermal state for different intensity of influence are given. In this case evaluation of intensity is estimated according to one-dimensional criteria taking into account environmental temperature, physical load and time of man's staying in overheating conditions.

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

PubMed

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance (similarity) measures. Results with the larger consistency will be more reliable.

[The informational support of statistical observation related to children disability].

PubMed

Son, I M; Polikarpov, A V; Ogrizko, E V; Golubeva, T Yu

2016-01-01

Within the framework of the Convention on rights of the disabled the revision is specified concerning criteria of identification of disability of children and reformation of system of medical social expertise according international standards of indices of health and indices related to health. In connection with it, it is important to consider the relationship between alterations in forms of the Federal statistical monitoring in the part of registration of disabled children in the Russian Federation and classification of health indices and indices related to health applied at identification of disability. The article presents analysis of relationship between alterations in forms of the Federal statistical monitoring in the part of registration of disabled children in the Russian Federation and applied classifications used at identification of disability (International classification of impairments, disabilities and handicap (ICDH), international classification of functioning, disability and health (ICF), international classification of functioning, disability and health, version for children and youth (ICF-CY). The intersectorial interaction is considered within the framework of statistics of children disability.

Characteristics of dysphagia in children with cerebral palsy, related to gross motor function.

PubMed

Kim, Joon-Sung; Han, Zee-A; Song, Dae Heon; Oh, Hyun-Mi; Chung, Myung Eun

2013-10-01

The aim of this study was to report the characteristics of dysphagia in children with cerebral palsy (CP), related to gross motor function. Videofluoroscopic swallow study was performed in 29 children with CP, according to the manual of Logemann. Five questions about oromotor dysfunction were answered. Gross motor function level was classified by the Gross Motor Function Classification System Expanded and Revised. The results of the videofluoroscopic swallowing studies showed that reduced lip closure, inadequate bolus formation, residue in the oral cavity, delayed triggering of pharyngeal swallow, reduced larynx elevation, coating on the pharyngeal wall, delayed pharyngeal transit time, multiple swallow, and aspiration were significantly more common in the severe group (Gross Motor Function Classification System Expanded and Revised IV or V). As for aspiration, 50% of the children with severe CP had problems, but only 14.3% of them with moderate (Gross Motor Function Classification System Expanded and Revised III) CP and none of them with mild CP had abnormalities. In addition, five of the seven aspiration cases occurred silently. This study shows that dysphagia is closely related to gross motor function in children with CP. Silent aspiration was observed in the moderate to severe CP groups. Aspiration is an important cause of medical problems such as acute and chronic lung disease, and associated respiratory complications contribute significantly in increasing morbidity and mortality in these patient groups. Therefore, the authors suggest that early dysphagia evaluation including videofluoroscopic swallow study is necessary in managing feeding problems and may prevent chronic aspiration, malnutrition, and infections.

Mapping the Content of the Patient Reported Outcomes Measurement Information System (PROMIS®) Using the International Classification of Functioning, Health and Disability

PubMed Central

Tucker, Carole A; Escorpizo, Reuben; Cieza, Alarcos; Lai, Jin Shei; Stucki, Gerold; Ustun, T. Bedirhan; Kostanjsek, Nenad; Cella, David; Forrest, Christopher B.

2014-01-01

Background The Patient Reported Outcomes Measurement Information System (PROMIS®) is a U.S. National Institutes of Health initiative that has produced self-reported item banks for physical, mental, and social health. Objective To describe the content of PROMIS at the item level using the World Health Organization’s International Classification of Functioning, Disability and Health (ICF). Methods All PROMIS adult items (publicly available as of 2012) were assigned to relevant ICF concepts. The content of the PROMIS adult item banks were then described using the mapped ICF code descriptors. Results The 1006 items in the PROMIS instruments could all be mapped to ICF concepts at the second level of classification, with the exception of 3 items of global or general health that mapped across the first-level classification of ICF activity and participation component (d categories). Individual PROMIS item banks mapped from 1 to 5 separate ICF codes indicating one-to-one, one-to-many and many-to-one mappings between PROMIS item banks and ICF second level classification codes. PROMIS supports measurement of the majority of major concepts in the ICF Body Functions (b) and Activity & Participation (d) components using PROMIS item banks or subsets of PROMIS items that could, with care, be used to develop customized instruments. Given the focus of PROMIS is on measurement of person health outcomes, concepts in body structures (s) and some body functions (b), as well as many ICF environmental factor have minimal coverage in PROMIS. Discussion The PROMIS-ICF mapped items provide a basis for users to evaluate the ICF related content of specific PROMIS instruments, and to select PROMIS instruments in ICF based measurement applications. PMID:24760532

PREDICT-CP: study protocol of implementation of comprehensive surveillance to predict outcomes for school-aged children with cerebral palsy.

PubMed

Boyd, Roslyn N; Davies, Peter Sw; Ziviani, Jenny; Trost, Stewart; Barber, Lee; Ware, Robert; Rose, Stephen; Whittingham, Koa; Sakzewski, Leanne; Bell, Kristie; Carty, Christopher; Obst, Steven; Benfer, Katherine; Reedman, Sarah; Edwards, Priya; Kentish, Megan; Copeland, Lisa; Weir, Kelly; Davenport, Camilla; Brooks, Denise; Coulthard, Alan; Pelekanos, Rebecca; Guzzetta, Andrea; Fiori, Simona; Wynter, Meredith; Finn, Christine; Burgess, Andrea; Morris, Kym; Walsh, John; Lloyd, Owen; Whitty, Jennifer A; Scuffham, Paul A

2017-07-12

Cerebral palsy (CP) remains the world's most common childhood physical disability with total annual costs of care and lost well-being of $A3.87b. The PREDICT-CP (NHMRC 1077257 Partnership Project: Comprehensive surveillance to PREDICT outcomes for school age children with CP) study will investigate the influence of brain structure, body composition, dietary intake, oropharyngeal function, habitual physical activity, musculoskeletal development (hip status, bone health) and muscle performance on motor attainment, cognition, executive function, communication, participation, quality of life and related health resource use costs. The PREDICT-CP cohort provides further follow-up at 8-12 years of two overlapping preschool-age cohorts examined from 1.5 to 5 years (NHMRC 465128 motor and brain development; NHMRC 569605 growth, nutrition and physical activity). This population-based cohort study undertakes state-wide surveillance of 245 children with CP born in Queensland (birth years 2006-2009). Children will be classified for Gross Motor Function Classification System; Manual Ability Classification System, Communication Function Classification System and Eating and Drinking Ability Classification System. Outcomes include gross motor function, musculoskeletal development (hip displacement, spasticity, muscle contracture), upper limb function, communication difficulties, oropharyngeal dysphagia, dietary intake and body composition, participation, parent-reported and child-reported quality of life and medical and allied health resource use. These detailed phenotypical data will be compared with brain macrostructure and microstructure using 3 Tesla MRI (3T MRI). Relationships between brain lesion severity and outcomes will be analysed using multilevel mixed-effects models. The PREDICT-CP protocol is a prospectively registered and ethically accepted study protocol. The study combines data at 1.5-5 then 8-12 years of direct clinical assessment to enable prediction of outcomes and healthcare needs essential for tailoring interventions (eg, rehabilitation, orthopaedic surgery and nutritional supplements) and the projected healthcare utilisation. ACTRN: 12616001488493. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Moving research tools into practice: the successes and challenges in promoting uptake of classification tools.

PubMed

Cunningham, Barbara Jane; Hidecker, Mary Jo Cooley; Thomas-Stonell, Nancy; Rosenbaum, Peter

2018-05-01

In this paper, we present our experiences - both successes and challenges - in implementing evidence-based classification tools into clinical practice. We also make recommendations for others wanting to promote the uptake and application of new research-based assessment tools. We first describe classification systems and the benefits of using them in both research and practice. We then present a theoretical framework from Implementation Science to report strategies we have used to implement two research-based classification tools into practice. We also illustrate some of the challenges we have encountered by reporting results from an online survey investigating 58 Speech-language Pathologists' knowledge and use of the Communication Function Classification System (CFCS), a new tool to classify children's functional communication skills. We offer recommendations for researchers wanting to promote the uptake of new tools in clinical practice. Specifically, we identify structural, organizational, innovation, practitioner, and patient-related factors that we recommend researchers address in the design of implementation interventions. Roles and responsibilities of both researchers and clinicians in making implementations science a success are presented. Implications for rehabilitation Promoting uptake of new and evidence-based tools into clinical practice is challenging. Implementation science can help researchers to close the knowledge-to-practice gap. Using concrete examples, we discuss our experiences in implementing evidence-based classification tools into practice within a theoretical framework. Recommendations are provided for researchers wanting to implement new tools in clinical practice. Implications for researchers and clinicians are presented.

Proposal for a functional classification system of heart failure in patients with end-stage renal disease: proceedings of the acute dialysis quality initiative (ADQI) XI workgroup.

PubMed

Chawla, Lakhmir S; Herzog, Charles A; Costanzo, Maria Rosa; Tumlin, James; Kellum, John A; McCullough, Peter A; Ronco, Claudio

2014-04-08

Structural heart disease is highly prevalent in patients with chronic kidney disease requiring dialysis. More than 80% of patients with end-stage renal disease (ESRD) are reported to have cardiovascular disease. This observation has enormous clinical relevance because the leading causes of death for patients with ESRD are of cardiovascular disease etiology, including heart failure, myocardial infarction, and sudden cardiac death. The 2 systems most commonly used to classify the severity of heart failure are the New York Heart Association (NYHA) functional classification and the American Heart Association (AHA)/American College of Cardiology (ACC) staging system. With rare exceptions, patients with ESRD who do not receive renal replacement therapy (RRT) develop signs and symptoms of heart failure, including dyspnea and edema due to inability of the severely diseased kidneys to excrete sodium and water. Thus, by definition, nearly all patients with ESRD develop a symptomatology consistent with heart failure if fluid removal by RRT is delayed. Neither the AHA/ACC heart failure staging nor the NYHA functional classification system identifies the variable symptomatology that patients with ESRD experience depending upon whether evaluation occurs before or after fluid removal by RRT. Consequently, the incidence, severity, and outcomes of heart failure in patients with ESRD are poorly characterized. The 11th Acute Dialysis Quality Initiative has identified this issue as a critical unmet need for the proper evaluation and treatment of heart failure in patients with ESRD. We propose a classification schema based on patient-reported dyspnea assessed both pre- and post-ultrafiltration, in conjunction with echocardiography. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

23 CFR 470.115 - Approval authority.

Code of Federal Regulations, 2010 CFR

2010-04-01

... FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION PLANNING AND RESEARCH HIGHWAY SYSTEMS Federal... Federal-aid highway system actions involving the designation, or revision, of routes on the Interstate...) The Federal Highway Administrator will approve functional classification actions. ...

A comparison of the International Classification of Functioning, Disability, and Health to the disability tax credit.

PubMed

Conti-Becker, Angela; Doralp, Samantha; Fayed, Nora; Kean, Crystal; Lencucha, Raphael; Leyshon, Rhysa; Mersich, Jackie; Robbins, Shawn; Doyle, Phillip C

2007-01-01

The Disability Tax Credit (DTC) Certification is an assessment tool used to provide Canadians with disability tax relief The International Classification of Functioning, Disability and Health (ICF) provides a universal framework for defining disability. The purpose of this study was to evaluate the DTC and familiarize occupational therapists with the process of mapping measures to the ICF classification system. Concepts within the DTC were identified and mapped to appropriate ICF codes (Cieza et al., 2005). The DTC was linked to 45 unique ICF codes (16 Body Functions, 19 Activities and Participation, and 8 Environmental Factors). The DTC encompasses various domains of the ICF; however, there is no consideration of Personal Factors, Body Structures, and key aspects of Activities and Participation. Refining the DTC to address these aspects will provide an opportunity for fair and just determinations for those who experience disability.

Validation of a systems-actuarial computer process for multidimensional classification of child psychopathology.

PubMed

McDermott, P A; Hale, R L

1982-07-01

Tested diagnostic classifications of child psychopathology produced by a computerized technique known as multidimensional actuarial classification (MAC) against the criterion of expert psychological opinion. The MAC program applies series of statistical decision rules to assess the importance of and relationships among several dimensions of classification, i.e., intellectual functioning, academic achievement, adaptive behavior, and social and behavioral adjustment, to perform differential diagnosis of children's mental retardation, specific learning disabilities, behavioral and emotional disturbance, possible communication or perceptual-motor impairment, and academic under- and overachievement in reading and mathematics. Classifications rendered by MAC are compared to those offered by two expert child psychologists for cases of 73 children referred for psychological services. Experts' agreement with MAC was significant for all classification areas, as was MAC's agreement with the experts held as a conjoint reference standard. Whereas the experts' agreement with MAC averaged 86.0% above chance, their agreement with one another averaged 76.5% above chance. Implications of the findings are explored and potential advantages of the systems-actuarial approach are discussed.

Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images.

PubMed

Schwartzkopf, Wade C; Bovik, Alan C; Evans, Brian L

2005-12-01

Traditional chromosome imaging has been limited to grayscale images, but recently a 5-fluorophore combinatorial labeling technique (M-FISH) was developed wherein each class of chromosomes binds with a different combination of fluorophores. This results in a multispectral image, where each class of chromosomes has distinct spectral components. In this paper, we develop new methods for automatic chromosome identification by exploiting the multispectral information in M-FISH chromosome images and by jointly performing chromosome segmentation and classification. We (1) develop a maximum-likelihood hypothesis test that uses multispectral information, together with conventional criteria, to select the best segmentation possibility; (2) use this likelihood function to combine chromosome segmentation and classification into a robust chromosome identification system; and (3) show that the proposed likelihood function can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies, which can be indicators of radiation damage, cancer, and a wide variety of inherited diseases. We show that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes. We also show that it outperforms past M-FISH classification techniques that do not use segmentation information.

Density functional theory study of β-hairpins in antiparallel β-sheets, a new classification based upon H-bond topology.

PubMed

Roy, Dipankar; Pohl, Gabor; Ali-Torres, Jorge; Marianski, Mateusz; Dannenberg, J J

2012-07-10

We present a new classification of β-turns specific to antiparallel β-sheets based upon the topology of H-bond formation. This classification results from ONIOM calculations using B3LYP/D95** density functional theory and AM1 semiempirical calculations as the high and low levels, respectively. We chose acetyl(Ala)(6)NH(2) as a model system as it is the simplest all-alanine system that can form all the H-bonds required for a β-turn in a sheet. Of the 10 different conformations we have found, the most stable structures have C(7) cyclic H-bonds in place of the C(10) interactions specified in the classic definition. Also, the chiralities specified for residues i + 1 and i + 2 in the classic definition disappear when the structures are optimized using our techniques, as the energetic differences among the four diastereomers of each structure are not substantial for 8 of the 10 conformations.

Analysis of design attributes and crashes on the Oregon highway system : final report.

DOT National Transportation Integrated Search

2001-08-01

This report has investigated the statistical relationship between crash activity and roadway design attributes on the Oregon state : highway system. Crash models were estimated from highway segments distinguished by functional classification (freeway...

Fascia: a morphological description and classification system based on a literature review

PubMed Central

Kumka, Myroslava; Bonar, Jason

2012-01-01

Fascia is virtually inseparable from all structures in the body and acts to create continuity amongst tissues to enhance function and support. In the past fascia has been difficult to study leading to ambiguities in nomenclature, which have only recently been addressed. Through review of the available literature, advances in fascia research were compiled, and issues related to terminology, descriptions, and clinical relevance of fascia were addressed. Our multimodal search strategy was conducted in Medline and PubMed databases, with other targeted searches in Google Scholar and by hand, utilizing reference lists and conference proceedings. In an effort to organize nomenclature for fascial structures provided by the Federative International Committee on Anatomical Terminology (FICAT), we developed a functional classification system which includes four categories of fascia: i) linking, ii) fascicular, iii) compression, and iv) separating fasciae. Each category was developed from descriptions in the literature on gross anatomy, histology, and biomechanics; the category names reflect the function of the fascia. An up-to-date definition of fascia is provided, as well as descriptions of its function and clinical features. Our classification demonstrates the use of internationally accepted terminology in an ontology which can improve understanding of major terms in each category of fascia. PMID:22997468

Systems engineering principles for the design of biomedical signal processing systems.

PubMed

Faust, Oliver; Acharya U, Rajendra; Sputh, Bernhard H C; Min, Lim Choo

2011-06-01

Systems engineering aims to produce reliable systems which function according to specification. In this paper we follow a systems engineering approach to design a biomedical signal processing system. We discuss requirements capturing, specification definition, implementation and testing of a classification system. These steps are executed as formal as possible. The requirements, which motivate the system design, are based on diabetes research. The main requirement for the classification system is to be a reliable component of a machine which controls diabetes. Reliability is very important, because uncontrolled diabetes may lead to hyperglycaemia (raised blood sugar) and over a period of time may cause serious damage to many of the body systems, especially the nerves and blood vessels. In a second step, these requirements are refined into a formal CSP‖ B model. The formal model expresses the system functionality in a clear and semantically strong way. Subsequently, the proven system model was translated into an implementation. This implementation was tested with use cases and failure cases. Formal modeling and automated model checking gave us deep insight in the system functionality. This insight enabled us to create a reliable and trustworthy implementation. With extensive tests we established trust in the reliability of the implementation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

[Classification and organization technologies in public health].

PubMed

Filatov, V B; Zhiliaeva, E P; Kal'fa, Iu I

2000-01-01

The authors discuss the impact and main characteristics of organization technologies in public health and the processes of their development and evaluation. They offer an original definition of the notion "organization technologies" with approaches to their classification. A system of logical bases is offered, which can be used for classification. These bases include the level of organization maturity and stage of development of organization technology, its destination to a certain level of management, type of influence and concentration of trend, mechanism of effect, functional group, and methods of development.

An XML-based system for the flexible classification and retrieval of clinical practice guidelines.

PubMed Central

Ganslandt, T.; Mueller, M. L.; Krieglstein, C. F.; Senninger, N.; Prokosch, H. U.

2002-01-01

Beneficial effects of clinical practice guidelines (CPGs) have not yet reached expectations due to limited routine adoption. Electronic distribution and reminder systems have the potential to overcome implementation barriers. Existing electronic CPG repositories like the National Guideline Clearinghouse (NGC) provide individual access but lack standardized computer-readable interfaces necessary for automated guideline retrieval. The aim of this paper was to facilitate automated context-based selection and presentation of CPGs. Using attributes from the NGC classification scheme, an XML-based metadata repository was successfully implemented, providing document storage, classification and retrieval functionality. Semi-automated extraction of attributes was implemented for the import of XML guideline documents using XPath. A hospital information system interface was exemplarily implemented for diagnosis-based guideline invocation. Limitations of the implemented system are discussed and possible future work is outlined. Integration of standardized computer-readable search interfaces into existing CPG repositories is proposed. PMID:12463831

A proposed food breakdown classification system to predict food behavior during gastric digestion.

PubMed

Bornhorst, Gail M; Ferrua, Maria J; Singh, R Paul

2015-05-01

The pharmaceutical industry has implemented the Biopharmaceutics Classification System (BCS), which is used to classify drug products based on their solubility and intestinal permeability. The BCS can help predict drug behavior in vivo, the rate-limiting mechanism of absorption, and the likelihood of an in vitro-in vivo correlation. Based on this analysis, we have proposed a Food Breakdown Classification System (FBCS) framework that can be used to classify solid foods according to their initial hardness and their rate of softening during physiological gastric conditions. The proposed FBCS will allow for prediction of food behavior during gastric digestion. The applicability of the FBCS framework in differentiating between dissimilar solid foods was demonstrated using four example foods: raw carrot, boiled potato, white rice, and brown rice. The initial hardness and rate of softening parameter (softening half time) were determined for these foods as well as their hypothesized FBCS class. In addition, we have provided future suggestions as to the methodological and analytical challenges that need to be overcome prior to widespread use and adoption of this classification system. The FBCS gives a framework that may be used to classify food products based on their material properties and their behavior during in vitro gastric digestion, and may also be used to predict in vivo food behavior. As consumer demand increases for functional and "pharma" food products, the food industry will need widespread testing of food products for their structural and functional performance during digestion. © 2015 Institute of Food Technologists®

14 CFR Section 9 - Functional Classification-Operating Revenues

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Functional Classification-Operating... AIR CARRIERS Profit and Loss Classification Section 9 Functional Classification—Operating Revenues 3900Transport Revenues. This classification is prescribed for all air carrier groups and shall include all...

An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2016-04-01

When assessing hydrogeological conditions at the regional scale, the analyst is often confronted with uncertainty of structures, inputs and processes while having to base inference on scarce and patchy data. Haaf and Barthel (2015) proposed a concept for handling this predicament by developing a groundwater systems classification framework, where information is transferred from similar, but well-explored and better understood to poorly described systems. The concept is based on the central hypothesis that similar systems react similarly to the same inputs and vice versa. It is conceptually related to PUB (Prediction in ungauged basins) where organization of systems and processes by quantitative methods is intended and used to improve understanding and prediction. Furthermore, using the framework it is expected that regional conceptual and numerical models can be checked or enriched by ensemble generated data from neighborhood-based estimators. In a first step, groundwater hydrographs from a large dataset in Southern Germany are compared in an effort to identify structural similarity in groundwater dynamics. A number of approaches to group hydrographs, mostly based on a similarity measure - which have previously only been used in local-scale studies, can be found in the literature. These are tested alongside different global feature extraction techniques. The resulting classifications are then compared to a visual "expert assessment"-based classification which serves as a reference. A ranking of the classification methods is carried out and differences shown. Selected groups from the classifications are related to geological descriptors. Here we present the most promising results from a comparison of classifications based on series correlation, different series distances and series features, such as the coefficients of the discrete Fourier transform and the intrinsic mode functions of empirical mode decomposition. Additionally, we show examples of classes corresponding to geological descriptors. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria.

What Attributes Determine Severity of Function in Autism? A Web-Based Survey of Stakeholders

ERIC Educational Resources Information Center

Di Rezze, Briano; Rosenbaum, Peter; Zwaigenbaum, Lonnie

2012-01-01

Service providers and researchers in autism spectrum disorders (ASD) are challenged to categorize clinical variation in function. Classification systems for children with cerebral palsy have enabled clinicians and families to describe levels of function. A web-based survey engaged international ASD stakeholders to advise on considerations of…

Using Loss Functions for DIF Detection: An Empirical Bayes Approach.

ERIC Educational Resources Information Center

Zwick, Rebecca; Thayer, Dorothy; Lewis, Charles

2000-01-01

Studied a method for flagging differential item functioning (DIF) based on loss functions. Builds on earlier research that led to the development of an empirical Bayes enhancement to the Mantel-Haenszel DIF analysis. Tested the method through simulation and found its performance better than some commonly used DIF classification systems. (SLD)

A personality classification system for eating disorders: a longitudinal study.

PubMed

Thompson-Brenner, Heather; Eddy, Kamryn T; Franko, Debra L; Dorer, David J; Vashchenko, Maryna; Kass, Andrea E; Herzog, David B

2008-01-01

Studies of eating disorders (EDs) suggest that empirically derived personality subtypes may explain heterogeneity in ED samples that is not captured by the current diagnostic system. Longitudinal outcomes for personality subtypes have not been examined. In this study, personality pathology was assessed by clinical interview in 213 individuals with anorexia nervosa and bulimia nervosa at baseline. Interview data on EDs, comorbid diagnoses, global functioning, and treatment utilization were collected at baseline and at 6-month follow-up intervals over a median of 9 years. Q-factor analysis of the participants based on personality items produced a 5-prototype system, including high-functioning, behaviorally dysregulated, emotionally dysregulated, avoidant-insecure, and obsessional-sensitive types. Dimensional prototype scores were associated with baseline functioning and longitudinal outcome. Avoidant-Insecure scores showed consistent associations with poor functioning and outcome, including failure to show ED improvement, poor global functioning after 5 years, and high treatment utilization after 5 years. Behavioral dysregulation was associated with poor baseline functioning but did not show strong associations with ED or global outcome when histories of major depression and substance use disorder were covaried. Emotional dysregulation and obsessional-sensitivity were not associated with negative outcomes. High-functioning prototype scores were consistently associated with positive outcomes. Longitudinal results support the importance of personality subtypes to ED classification.

The National Ecosystem Services Classification System: A Framework for Identifying and Reducing Relevant Uncertainties

NASA Astrophysics Data System (ADS)

Rhodes, C. R.; Sinha, P.; Amanda, N.

2013-12-01

In recent years the gap between what scientists know and what policymakers should appreciate in environmental decision making has received more attention, as the costs of the disconnect have become more apparent to both groups. Particularly for water-related policies, the EPA's Office of Water has struggled with benefit estimates held low by the inability to quantify ecological and economic effects that theory, modeling, and anecdotal or isolated case evidence suggest may prove to be larger. Better coordination with ecologists and hydrologists is being explored as a solution. The ecosystem services (ES) concept now nearly two decades old links ecosystem functions and processes to the human value system. But there remains no clear mapping of which ecosystem goods and services affect which individual or economic values. The National Ecosystem Services Classification System (NESCS, 'nexus') project brings together ecologists, hydrologists, and social scientists to do this mapping for aquatic and other ecosystem service-generating systems. The objective is to greatly reduce the uncertainty in water-related policy making by mapping and ultimately quantifying the various functions and products of aquatic systems, as well as how changes to aquatic systems impact the human economy and individual levels of non-monetary appreciation for those functions and products. Primary challenges to fostering interaction between scientists, social scientists, and policymakers are lack of a common vocabulary, and the need for a cohesive comprehensive framework that organizes concepts across disciplines and accommodates scientific data from a range of sources. NESCS builds the vocabulary and the framework so both may inform a scalable transdisciplinary policy-making application. This talk presents for discussion the process and progress in developing both this vocabulary and a classifying framework capable of bridging the gap between a newer but existing ecosystem services classification system, and a standardized industrial classification system. Our goal is to model then predict the effects of a policy choice on the environment, from impacts on ecological components and processes all the way through to endpoints in the human value chain.

Validation of accelerometer cut points in toddlers with and without cerebral palsy.

PubMed

Oftedal, Stina; Bell, Kristie L; Davies, Peter S W; Ware, Robert S; Boyd, Roslyn N

2014-09-01

The purpose of this study was to validate uni- and triaxial ActiGraph cut points for sedentary time in toddlers with cerebral palsy (CP) and typically developing children (TDC). Children (n = 103, 61 boys, mean age = 2 yr, SD = 6 months, range = 1 yr 6 months-3 yr) were divided into calibration (n = 65) and validation (n = 38) samples with separate analyses for TDC (n = 28) and ambulant (Gross Motor Function Classification System I-III, n = 51) and nonambulant (Gross Motor Function Classification System IV-V, n = 25) children with CP. An ActiGraph was worn during a videotaped assessment. Behavior was coded as sedentary or nonsedentary. Receiver operating characteristic-area under the curve analysis determined the classification accuracy of accelerometer data. Predictive validity was determined using the Bland-Altman analysis. Classification accuracy for uniaxial data was fair for the ambulatory CP and TDC group but poor for the nonambulatory CP group. Triaxial data showed good classification accuracy for all groups. The uniaxial ambulatory CP and TDC cut points significantly overestimated sedentary time (bias = -10.5%, 95% limits of agreement [LoA] = -30.2% to 9.1%; bias = -17.3%, 95% LoA = -44.3% to 8.3%). The triaxial ambulatory and nonambulatory CP and TDC cut points provided accurate group-level measures of sedentary time (bias = -1.5%, 95% LoA = -20% to 16.8%; bias = 2.1%, 95% LoA = -17.3% to 21.5%; bias = -5.1%, 95% LoA = -27.5% to 16.1%). Triaxial accelerometers provide useful group-level measures of sedentary time in children with CP across the spectrum of functional abilities and TDC. Uniaxial cut points are not recommended.

DFT description of the magnetic properties and electron localization in dinuclear di-mu-oxo-bridged manganese complexes.

PubMed

Barone, Vincenzo; Bencini, Alessandro; Gatteschi, Dante; Totti, Federico

2002-11-04

Density functional theory (DFT) was applied to describe the magnetic and electron-transfer properties of dinuclear systems containing the [MnO2Mn]n+ core, with n=0,1,2,3,4. The calculation of the potential energy surfaces (PESs) of the mixed-valence species (n=1,3) allowed the classification of these systems according to the extent of valence localization as Class II compounds, in the Robin-Day classification scheme. The fundamental frequencies corresponding to the asymmetric breathing vibration were also computed.

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

PubMed

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

2001-01-01

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

Classification of underground pipe scanned images using feature extraction and neuro-fuzzy algorithm.

PubMed

Sinha, S K; Karray, F

2002-01-01

Pipeline surface defects such as holes and cracks cause major problems for utility managers, particularly when the pipeline is buried under the ground. Manual inspection for surface defects in the pipeline has a number of drawbacks, including subjectivity, varying standards, and high costs. Automatic inspection system using image processing and artificial intelligence techniques can overcome many of these disadvantages and offer utility managers an opportunity to significantly improve quality and reduce costs. A recognition and classification of pipe cracks using images analysis and neuro-fuzzy algorithm is proposed. In the preprocessing step the scanned images of pipe are analyzed and crack features are extracted. In the classification step the neuro-fuzzy algorithm is developed that employs a fuzzy membership function and error backpropagation algorithm. The idea behind the proposed approach is that the fuzzy membership function will absorb variation of feature values and the backpropagation network, with its learning ability, will show good classification efficiency.

Classification of ion mobility spectra by functional groups using neural networks

NASA Technical Reports Server (NTRS)

Bell, S.; Nazarov, E.; Wang, Y. F.; Eiceman, G. A.

1999-01-01

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Using social capital to construct a conceptual International Classification of Functioning, Disability, and Health Children and Youth version-based framework for stronger inclusive education policies in Europe.

PubMed

Maxwell, Gregor; Koutsogeorgou, Eleni

2012-02-01

Inclusive education is part of social inclusion; therefore, social capital can be linked to an inclusive education policy and practice. This association is explored in this article, and a practical measure is proposed. Specifically, the World Health Organization's International Classification of Functioning, Disability and Health Children and Youth Version (ICF-CY) is proposed as the link between social capital and inclusive education. By mapping participation and trust indicators of social capital to the ICF-CY and by using the Matrix to Analyse Functioning in Education Systems (MAFES) to analyze the functioning of inclusive education policies and systems, a measure for stronger inclusive education policies is proposed. Such a tool can be used for policy planning and monitoring to ensure better inclusive education environments. In conclusion, combining enhanced social capital linked to stronger inclusive education policies, by using the ICF-CY, can lead to better health and well-being for all.

Annotation and Classification of CRISPR-Cas Systems

PubMed Central

Makarova, Kira S.; Koonin, Eugene V.

2018-01-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated proteins) is a prokaryotic adaptive immune system that is represented in most archaea and many bacteria. Among the currently known prokaryotic defense systems, the CRISPR-Cas genomic loci show unprecedented complexity and diversity. Classification of CRISPR-Cas variants that would capture their evolutionary relationships to the maximum possible extent is essential for comparative genomic and functional characterization of this theoretically and practically important system of adaptive immunity. To this end, a multipronged approach has been developed that combines phylogenetic analysis of the conserved Cas proteins with comparison of gene repertoires and arrangements in CRISPR-Cas loci. This approach led to the current classification of CRISPR-Cas systems into three distinct types and ten subtypes for each of which signature genes have been identified. Comparative genomic analysis of the CRISPR-Cas systems in new archaeal and bacterial genomes performed over the 3 years elapsed since the development of this classification makes it clear that new types and subtypes of CRISPR-Cas need to be introduced. Moreover, this classification system captures only part of the complexity of CRISPR-Cas organization and evolution, due to the intrinsic modularity and evolutionary mobility of these immunity systems, resulting in numerous recombinant variants. Moreover, most of the cas genes evolve rapidly, complicating the family assignment for many Cas proteins and the use of family profiles for the recognition of CRISPR-Cas subtype signatures. Further progress in the comparative analysis of CRISPR-Cas systems requires integration of the most sensitive sequence comparison tools, protein structure comparison, and refined approaches for comparison of gene neighborhoods. PMID:25981466

Annotation and Classification of CRISPR-Cas Systems.

PubMed

Makarova, Kira S; Koonin, Eugene V

2015-01-01

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas (CRISPR-associated proteins) is a prokaryotic adaptive immune system that is represented in most archaea and many bacteria. Among the currently known prokaryotic defense systems, the CRISPR-Cas genomic loci show unprecedented complexity and diversity. Classification of CRISPR-Cas variants that would capture their evolutionary relationships to the maximum possible extent is essential for comparative genomic and functional characterization of this theoretically and practically important system of adaptive immunity. To this end, a multipronged approach has been developed that combines phylogenetic analysis of the conserved Cas proteins with comparison of gene repertoires and arrangements in CRISPR-Cas loci. This approach led to the current classification of CRISPR-Cas systems into three distinct types and ten subtypes for each of which signature genes have been identified. Comparative genomic analysis of the CRISPR-Cas systems in new archaeal and bacterial genomes performed over the 3 years elapsed since the development of this classification makes it clear that new types and subtypes of CRISPR-Cas need to be introduced. Moreover, this classification system captures only part of the complexity of CRISPR-Cas organization and evolution, due to the intrinsic modularity and evolutionary mobility of these immunity systems, resulting in numerous recombinant variants. Moreover, most of the cas genes evolve rapidly, complicating the family assignment for many Cas proteins and the use of family profiles for the recognition of CRISPR-Cas subtype signatures. Further progress in the comparative analysis of CRISPR-Cas systems requires integration of the most sensitive sequence comparison tools, protein structure comparison, and refined approaches for comparison of gene neighborhoods.

Classification systems for causes of stillbirth and neonatal death, 2009-2014: an assessment of alignment with characteristics for an effective global system.

PubMed

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

2016-09-15

To reduce the burden of 5.3 million stillbirths and neonatal deaths annually, an understanding of causes of deaths is critical. A systematic review identified 81 systems for classification of causes of stillbirth (SB) and neonatal death (NND) between 2009 and 2014. The large number of systems hampers efforts to understand and prevent these deaths. This study aimed to assess the alignment of current classification systems with expert-identified characteristics for a globally effective classification system. Eighty-one classification systems were assessed for alignment with 17 characteristics previously identified through expert consensus as necessary for an effective global system. Data were extracted independently by two authors. Systems were assessed against each characteristic and weighted and unweighted scores assigned to each. Subgroup analyses were undertaken by system use, setting, type of death included and type of characteristic. None of the 81 systems were aligned with more than 9 of the 17 characteristics; most (82 %) were aligned with four or fewer. On average, systems were aligned with 19 % of characteristics. The most aligned system (Frøen 2009-Codac) still had an unweighted score of only 9/17. Alignment with individual characteristics ranged from 0 to 49 %. Alignment was somewhat higher for widely used as compared to less used systems (22 % v 17 %), systems used only in high income countries as compared to only in low and middle income countries (20 % vs 16 %), and systems including both SB and NND (23 %) as compared to NND-only (15 %) and SB-only systems (13 %). Alignment was higher with characteristics assessing structure (23 %) than function (15 %). There is an unmet need for a system exhibiting all the characteristics of a globally effective system as defined by experts in the use of systems, as none of the 81 contemporary classification systems assessed was highly aligned with these characteristics. A particular concern in terms of global effectiveness is the lack of alignment with "ease of use" among all systems, including even the most-aligned. A system which meets the needs of users would have the potential to become the first truly globally effective classification system.

Practice, science and governance in interaction: European effort for the system-wide implementation of the International Classification of Functioning, Disability and Health (ICF) in Physical and Rehabilitation Medicine.

PubMed

Stucki, Gerold; Zampolini, Mauro; Juocevicius, Alvydas; Negrini, Stefano; Christodoulou, Nicolas

2017-04-01

Since its launch in 2001, relevant international, regional and national PRM bodies have aimed to implement the International Classification of Functioning, Disability and Health (ICF) in Physical and Rehabilitation Medicine (PRM), whereby contributing to the development of suitable practical tools. These tools are available for implementing the ICF in day-to-day clinical practice, standardized reporting of functioning outcomes in quality management and research, and guiding evidence-informed policy. Educational efforts have reinforced PRM physicians' and other rehabilitation professionals' ICF knowledge, and numerous implementation projects have explored how the ICF is applied in clinical practice, research and policy. Largely lacking though is the system-wide implementation of ICF in day-to-day practice across all rehabilitation services of national health systems. In Europe, system-wide implementation of ICF requires the interaction between practice, science and governance. Considering its mandate, the UEMS PRM Section and Board have decided to lead a European effort towards system-wide ICF implementation in PRM, rehabilitation and health care at large, in interaction with governments, non-governmental actors and the private sector, and aligned with ISPRM's collaboration plan with WHO. In this paper we present the current PRM internal and external policy agenda towards system-wide ICF implementation and the corresponding implementation action plan, while highlighting priority action steps - promotion of ICF-based standardized reporting in national quality management and assurance programs, development of unambiguous rehabilitation service descriptions using the International Classification System for Service Organization in Health-related Rehabilitation, development of Clinical Assessment Schedules, qualitative linkage and quantitative mapping of data to the ICF, and the cultural adaptation of the ICF Clinical Data Collection Tool in European languages.

Predicting heart failure mortality in frail seniors: comparing the NYHA functional classification with the Resident Assessment Instrument (RAI) 2.0.

PubMed

Tjam, Erin Y; Heckman, George A; Smith, Stuart; Arai, Bruce; Hirdes, John; Poss, Jeff; McKelvie, Robert S

2012-02-23

Though the NYHA functional classification is recommended in clinical settings, concerns have been raised about its reliability particularly among older patients. The RAI 2.0 is a comprehensive assessment system specifically developed for frail seniors. We hypothesized that a prognostic model for heart failure (HF) developed from the RAI 2.0 would be superior to the NYHA classification. The purpose of this study was to determine whether a HF-specific prognostic model based on the RAI 2.0 is superior to the NYHA functional classification in predicting mortality in frail older HF patients. Secondary analysis of data from a prospective cohort study of a HF education program for care providers in long-term care and retirement homes. Univariate analyses identified RAI 2.0 variables predicting death at 6 months. These and the NYHA classification were used to develop logistic models. Two RAI 2.0 models were derived. The first includes six items: "weight gain of 5% or more of total body weight over 30 days", "leaving 25% or more food uneaten", "unable to lie flat", "unstable cognitive, ADL, moods, or behavioural patterns", "change in cognitive function" and "needing help to walk in room"; the C statistic was 0.866. The second includes the CHESS health instability scale and the item "requiring help walking in room"; the C statistic was 0.838. The C statistic for the NYHA scale was 0.686. These results suggest that data from the RAI 2.0, an instrument for comprehensive assessment of frail seniors, can better predict mortality than the NYHA classification. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Casemix classification payment for sub-acute and non-acute inpatient care, Thailand.

PubMed

Khiaocharoen, Orathai; Pannarunothai, Supasit; Zungsontiporn, Chairoj; Riewpaiboon, Wachara

2010-07-01

There is a need to develop other casemix classifications, apart from DRG for sub-acute and non-acute inpatient care payment mechanism in Thailand. To develop a casemix classification for sub-acute and non-acute inpatient service. The study began with developing a classification system, analyzing cost, assigning payment weights, and ended with testing the validity of this new casemix system. Coefficient of variation, reduction in variance, linear regression, and split-half cross-validation were employed. The casemix for sub-acute and non-acute inpatient services contained 98 groups. Two percent of them had a coefficient of variation of the cost of higher than 1.5. The reduction in variance of cost after the classification was 32%. Two classification variables (physical function and the rehabilitation impairment categories) were key determinants of the cost (adjusted R2 = 0.749, p = .001). Validity results of split-half cross-validation of sub-acute and non-acute inpatient service were high. The present study indicated that the casemix for sub-acute and non-acute inpatient services closely predicted the hospital resource use and should be further developed for payment of the inpatients sub-acute and non-acute phase.

Classifying human operator functional state based on electrophysiological and performance measures and fuzzy clustering method.

PubMed

Zhang, Jian-Hua; Peng, Xiao-Di; Liu, Hua; Raisch, Jörg; Wang, Ru-Bin

2013-12-01

The human operator's ability to perform their tasks can fluctuate over time. Because the cognitive demands of the task can also vary it is possible that the capabilities of the operator are not sufficient to satisfy the job demands. This can lead to serious errors when the operator is overwhelmed by the task demands. Psychophysiological measures, such as heart rate and brain activity, can be used to monitor operator cognitive workload. In this paper, the most influential psychophysiological measures are extracted to characterize Operator Functional State (OFS) in automated tasks under a complex form of human-automation interaction. The fuzzy c-mean (FCM) algorithm is used and tested for its OFS classification performance. The results obtained have shown the feasibility and effectiveness of the FCM algorithm as well as the utility of the selected input features for OFS classification. Besides being able to cope with nonlinearity and fuzzy uncertainty in the psychophysiological data it can provide information about the relative importance of the input features as well as the confidence estimate of the classification results. The OFS pattern classification method developed can be incorporated into an adaptive aiding system in order to enhance the overall performance of a large class of safety-critical human-machine cooperative systems.

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

PubMed

Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

2016-12-01

Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Classification of spontaneous EEG signals in migraine

NASA Astrophysics Data System (ADS)

Bellotti, R.; De Carlo, F.; de Tommaso, M.; Lucente, M.

2007-08-01

We set up a classification system able to detect patients affected by migraine without aura, through the analysis of their spontaneous EEG patterns. First, the signals are characterized by means of wavelet-based features, than a supervised neural network is used to classify the multichannel data. For the feature extraction, scale-dependent and scale-independent methods are considered with a variety of wavelet functions. Both the approaches provide very high and almost comparable classification performances. A complete separation of the two groups is obtained when the data are plotted in the plane spanned by two suitable neural outputs.

Classification of attractors for systems of identical coupled Kuramoto oscillators

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

Engelbrecht, Jan R.; Mirollo, Renato

2014-03-15

We present a complete classification of attractors for networks of coupled identical Kuramoto oscillators. In such networks, each oscillator is driven by the same first-order trigonometric function, with coefficients given by symmetric functions of the entire oscillator ensemble. For N≠3 oscillators, there are four possible types of attractors: completely synchronized fixed points or limit cycles, and fixed points or limit cycles where all but one of the oscillators are synchronized. The case N = 3 is exceptional; systems of three identical Kuramoto oscillators can also posses attracting fixed points or limit cycles with all three oscillators out of sync, as well asmore » chaotic attractors. Our results rely heavily on the invariance of the flow for such systems under the action of the three-dimensional group of Möbius transformations, which preserve the unit disc, and the analysis of the possible limiting configurations for this group action.« less

Evaluation of different classification methods for the diagnosis of schizophrenia based on functional near-infrared spectroscopy.

PubMed

Li, Zhaohua; Wang, Yuduo; Quan, Wenxiang; Wu, Tongning; Lv, Bin

2015-02-15

Based on near-infrared spectroscopy (NIRS), recent converging evidence has been observed that patients with schizophrenia exhibit abnormal functional activities in the prefrontal cortex during a verbal fluency task (VFT). Therefore, some studies have attempted to employ NIRS measurements to differentiate schizophrenia patients from healthy controls with different classification methods. However, no systematic evaluation was conducted to compare their respective classification performances on the same study population. In this study, we evaluated the classification performance of four classification methods (including linear discriminant analysis, k-nearest neighbors, Gaussian process classifier, and support vector machines) on an NIRS-aided schizophrenia diagnosis. We recruited a large sample of 120 schizophrenia patients and 120 healthy controls and measured the hemoglobin response in the prefrontal cortex during the VFT using a multichannel NIRS system. Features for classification were extracted from three types of NIRS data in each channel. We subsequently performed a principal component analysis (PCA) for feature selection prior to comparison of the different classification methods. We achieved a maximum accuracy of 85.83% and an overall mean accuracy of 83.37% using a PCA-based feature selection on oxygenated hemoglobin signals and support vector machine classifier. This is the first comprehensive evaluation of different classification methods for the diagnosis of schizophrenia based on different types of NIRS signals. Our results suggested that, using the appropriate classification method, NIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

Changing beliefs for changing movement and pain: Classification-based cognitive functional therapy (CB-CFT) for chronic non-specific low back pain.

PubMed

Meziat Filho, N

2016-02-01

This case report presents the effect of classification-based cognitive functional therapy in a patient with chronic disabling low back pain. The patient was assessed using a multidimensional biopsychosocial classification system and was classified as having flexion pattern of movement impairment disorder. Management of this patient was to change her belief that bending over and sitting would cause damage to her disc, combined with active exercises for graded exposure to lumbar flexion to restore normal movement. Three months after the first appointment, the treatment resulted in reduced pain, the mitigation of fear avoidance beliefs and the remediation of functional disability. The patient returned to work and was walking for one hour a day on a treadmill. The cognitive intervention to change the patient's negative beliefs related to the biomedical model was important to make the graded exercises and the lifestyle changes possible. Copyright © 2015 Elsevier Ltd. All rights reserved.

A tool for enhancing strategic health planning: a modeled use of the International Classification of Functioning, Disability and Health

PubMed Central

Sinclair, Lisa Bundara; Fox, Michael H.; Betts, Donald R.

2015-01-01

SUMMARY This article describes use of the International Classification of Functioning, Disability and Health (ICF) as a tool for strategic planning. The ICF is the international classification system for factors that influence health, including Body Structures, Body Functions, Activities and Participation and Environmental Factors. An overview of strategic planning and the ICF are provided. Selected ICF concepts and nomenclature are used to demonstrate its utility in helping develop a classic planning framework, objectives, measures and actions. Some issues and resolutions for applying the ICF are described. Applying the ICF for strategic health planning is an innovative approach that fosters the inclusion of social ecological health determinants and broad populations. If employed from the onset of planning, the ICF can help public health organizations systematically conceptualize, organize and communicate a strategic health plan. This article is a US Government work and is in the public domain in the USA. PMID:23147247

Validation of Accelerometer Cut-Points in Children With Cerebral Palsy Aged 4 to 5 Years.

PubMed

Keawutan, Piyapa; Bell, Kristie L; Oftedal, Stina; Davies, Peter S W; Boyd, Roslyn N

2016-01-01

To derive and validate triaxial accelerometer cut-points in children with cerebral palsy (CP) and compare these with previously established cut-points in children with typical development. Eighty-four children with CP aged 4 to 5 years wore the ActiGraph during a play-based gross motor function measure assessment that was video-taped for direct observation. Receiver operating characteristic and Bland-Altman plots were used for analyses. The ActiGraph had good classification accuracy in Gross Motor Function Classification System (GMFCS) levels III and V and fair classification accuracy in GMFCS levels I, II, and IV. These results support the use of the previously established cut-points for sedentary time of 820 counts per minute in children with CP aged 4 to 5 years across all functional abilities. The cut-point provides an objective measure of sedentary and active time in children with CP. The cut-point is applicable to group data but not for individual children.

A tool for enhancing strategic health planning: a modeled use of the International Classification of Functioning, Disability and Health.

PubMed

Sinclair, Lisa Bundara; Fox, Michael H; Betts, Donald R

2013-01-01

This article describes use of the International Classification of Functioning, Disability and Health (ICF) as a tool for strategic planning. The ICF is the international classification system for factors that influence health, including Body Structures, Body Functions, Activities and Participation and Environmental Factors. An overview of strategic planning and the ICF are provided. Selected ICF concepts and nomenclature are used to demonstrate its utility in helping develop a classic planning framework, objectives, measures and actions. Some issues and resolutions for applying the ICF are described. Applying the ICF for strategic health planning is an innovative approach that fosters the inclusion of social ecological health determinants and broad populations. If employed from the onset of planning, the ICF can help public health organizations systematically conceptualize, organize and communicate a strategic health plan. Published 2012. This article is a US Government work and is in the public domain in the USA.

Designing a training tool for imaging mental models

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Jayaram, Geetha

1990-01-01

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

Model-based object classification using unification grammars and abstract representations

NASA Astrophysics Data System (ADS)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

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

Using the International Classification of Functioning, Disability, and Health to identify outcome domains for a core outcome set for aphasia: a comparison of stakeholder perspectives.

PubMed

Wallace, Sarah J; Worrall, Linda; Rose, Tanya; Le Dorze, Guylaine

2017-11-12

This study synthesised the findings of three separate consensus processes exploring the perspectives of key stakeholder groups about important aphasia treatment outcomes. This process was conducted to generate recommendations for outcome domains to be included in a core outcome set for aphasia treatment trials. International Classification of Functioning, Disability, and Health codes were examined to identify where the groups of: (1) people with aphasia, (2) family members, (3) aphasia researchers, and (4) aphasia clinicians/managers, demonstrated congruence in their perspectives regarding important treatment outcomes. Codes were contextualized using qualitative data. Congruence across three or more stakeholder groups was evident for ICF chapters: Mental functions; Communication; and Services, systems, and policies. Quality of life was explicitly identified by clinicians/managers and researchers, while people with aphasia and their families identified outcomes known to be determinants of quality of life. Core aphasia outcomes include: language, emotional wellbeing, communication, patient-reported satisfaction with treatment and impact of treatment, and quality of life. International Classification of Functioning, Disability, and Health coding can be used to compare stakeholder perspectives and identify domains for core outcome sets. Pairing coding with qualitative data may ensure important nuances of meaning are retained. Implications for rehabilitation The outcomes measured in treatment research should be relevant to stakeholders and support health care decision making. Core outcome sets (agreed, minimum set of outcomes, and outcome measures) are increasingly being used to ensure the relevancy and consistency of the outcomes measured in treatment studies. Important aphasia treatment outcomes span all components of the International Classification of Functioning, Disability, and Health. Stakeholders demonstrated congruence in the identification of important outcomes which related Mental functions; Communication; Services, systems, and policies; and Quality of life. A core outcome set for aphasia treatment research should include measures relating to: language, emotional wellbeing, communication, patient-reported satisfaction with treatment and impact of treatment, and quality of life. Coding using the International Classification of Functioning, Disability, and Health, presents a novel methodology for the comparison of stakeholder perspectives to inform recommendations for outcome constructs to be included in a core outcome set. Coding can be paired with qualitative data to ensure nuances of meaning are retained.

Pediatric aquatic therapy on motor function and enjoyment in children diagnosed with cerebral palsy of various motor severities.

PubMed

Lai, Chih-Jou; Liu, Wen-Yu; Yang, Tsui-Fen; Chen, Chia-Ling; Wu, Ching-Yi; Chan, Rai-Chi

2015-02-01

This study investigates the effects of pediatric aquatic therapy on motor function, enjoyment, activities of daily living, and health-related quality of life for children with spastic cerebral palsy of various motor severities. Children with spastic cerebral palsy were assigned to a pediatric aquatic therapy group (n = 11; mean age = 85.0 ± 33.1 months; male : female = 4 : 7) or a control group (n = 13; mean age = 87.6 ± 34.0 months; male : female = 9 : 4). The statistic results indicate that the pediatric aquatic therapy group had greater average 66-item Gross Motor Function Measure following intervention than the control group (η(2) = 0.308, P = .007), even for children with Gross Motor Function Classification System level IV (5.0 vs 1.3). The pediatric aquatic therapy group had higher Physical Activity Enjoyment Scale scores than the control group at post-treatment (P = .015). These findings demonstrate that pediatric aquatic therapy can be an effective and alternative therapy for children with cerebral palsy even with poor Gross Motor Function Classification System level. © The Author(s) 2014.

An alternative respiratory sounds classification system utilizing artificial neural networks.

PubMed

Oweis, Rami J; Abdulhay, Enas W; Khayal, Amer; Awad, Areen

2015-01-01

Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills. This work revolves around exploiting autocorrelation in the feature extraction stage. All process stages were implemented in MATLAB. The classification process was performed comparatively using both artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) toolboxes. The methods have been applied to 10 different respiratory sounds for classification. The ANN was superior to the ANFIS system and returned superior performance parameters. Its accuracy, specificity, and sensitivity were 98.6%, 100%, and 97.8%, respectively. The obtained parameters showed superiority to many recent approaches. The promising proposed method is an efficient fast tool for the intended purpose as manifested in the performance parameters, specifically, accuracy, specificity, and sensitivity. Furthermore, it may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.

Common occupational classification system - revision 3

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

Stahlman, E.J.; Lewis, R.E.

1996-05-01

Workforce planning has become an increasing concern within the DOE community as the Office of Environmental Restoration and Waste Management (ER/WM or EM) seeks to consolidate and refocus its activities and the Office of Defense Programs (DP) closes production sites. Attempts to manage the growth and skills mix of the EM workforce while retaining the critical skills of the DP workforce have been difficult due to the lack of a consistent set of occupational titles and definitions across the complex. Two reasons for this difficulty may be cited. First, classification systems commonly used in industry often fail to cover inmore » sufficient depth the unique demands of DOE`s nuclear energy and research community. Second, the government practice of contracting the operation of government facilities to the private sector has introduced numerous contractor-specific classification schemes to the DOE complex. As a result, sites/contractors report their workforce needs using unique classification systems. It becomes difficult, therefore, to roll these data up to the national level necessary to support strategic planning and analysis. The Common Occupational Classification System (COCS) is designed to overcome these workforce planning barriers. The COCS is based on earlier workforce planning activities and the input of technical, workforce planning, and human resource managers from across the DOE complex. It provides a set of mutually-exclusive occupation titles and definitions that cover the broad range of activities present in the DOE complex. The COCS is not a required record-keeping or data management guide. Neither is it intended to replace contractor/DOE-specific classification systems. Instead, the system provides a consistent, high- level, functional structure of occupations to which contractors can crosswalk (map) their job titles.« less

Prevalence of physical activity, screen time, and obesity among US children by the service type of special health care needs.

PubMed

Kim, Juhee; Greaney, Mary L

2014-07-01

Children with special health care needs (SHCN) may be at greater risk of obesity than children without SHCN. A new classification system categorizes SHCN among children by service type using the following categories: No-SHCN, medication use only, services use only, medication + service use, and functional limitations. Research is needed to examine obesity and obesity-related behaviors among children using the new classification system. To determine the prevalence of inadequate vigorous physical activity (VPA), high screen time and obesity by SHCN category using the new classification system. Multivariate regression models were fitted for inadequate VPA, high screen time, and obesity to determine if there were differences in these outcomes by SHCN category, adjusting for multistage-sampling and survey-design effects using a nationally representative sample of children in the National Survey of Children's Health 2007. 22.9% of the sample was classified as having SHCN: 9% medication use only, 5% medication + service use, 4% service use only, and 5% functional limitations. Children in the medication use only and medication + service use groups were not at increased risk for inadequate VPA, high screen time, or obesity. Children in the service use only and functional limitation groups had increased odds of high screen time and obesity, which disappeared after controlling for confounders. However, the higher odds of inadequate VPA remained significant in the service use only [OR (95% CI) = 2.00 (1.34-3.00)] and the functional limitations groups with 2.21 (1.55-3.15). Physical activity promotion programs are needed for children with SHCN, especially children with functional limitations and those who require service use only and do not use prescribed medication. Copyright © 2014 Elsevier Inc. All rights reserved.

Descriptive and Functional Classifications of Drug Abusers

ERIC Educational Resources Information Center

Carlin, Albert S.; Stauss, Fred F.

1977-01-01

Polydrug (non-opiate-drug) abusers have previously been classified by a variety of typologies that can be characterized as either descriptive, functional, or a combination of both. This investigation proposes two objective scoring systems that classify polydrug users on a streetwise/straight dimension and on a self-medication/recreational-use…

Developing a classification system of social communication functioning of preschool children with autism spectrum disorder.

PubMed

Di Rezze, Briano; Rosenbaum, Peter; Zwaigenbaum, Lonnie; Hidecker, Mary Jo Cooley; Stratford, Paul; Cousins, Martha; Camden, Chantal; Law, Mary

2016-09-01

Impairments in social communication are the hallmark of autism spectrum disorder (ASD). Operationalizing 'severity' in ASD has been challenging; thus, stratifying by functioning has not been possible. The purpose of this study is to describe the development of the Autism Classification System of Functioning: Social Communication (ACSF:SC) and to evaluate its consistency within and between parent and professional ratings. (1) ACSF:SC development based on focus groups and surveys involving parents, educators, and clinicians familiar with preschoolers with ASD; and (2) evaluation of the intra- and interrater agreement of the ACSF:SC using weighted kappa (кw ). Seventy-six participants were involved in the development process. Core characteristics of social communication were ascertained: communicative intent; communicative skills and reciprocity; and impact of environment. Five ACSF:SC levels were created and content-validated across participants. Best capacity and typical performance agreement ratings varied as follows: intrarater agreement on 41 children was кw =0.61 to 0.69 for parents, and кw =0.71 to 0.95 for professionals; interrater agreement between professionals was кw =0.47 to 0.61, and between parents and professionals was кw =0.33 to 0.53. Perspectives from parents and professionals informed ACSF:SC development, providing common descriptions of the levels of everyday communicative abilities of children with ASD to complement the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Rater agreement demonstrates that the ACSF:SC can be used with acceptable consistency compared with other functional classification systems. © 2016 Mac Keith Press.

Iatrogenic Bone and Soft Tissue Trauma in Robotic-Arm Assisted Total Knee Arthroplasty Compared With Conventional Jig-Based Total Knee Arthroplasty: A Prospective Cohort Study and Validation of a New Classification System.

PubMed

Kayani, Babar; Konan, Sujith; Pietrzak, Jurek R T; Haddad, Fares S

2018-03-27

The objective of this study was to compare macroscopic bone and soft tissue injury between robotic-arm assisted total knee arthroplasty (RA-TKA) and conventional jig-based total knee arthroplasty (CJ-TKA) and create a validated classification system for reporting iatrogenic bone and periarticular soft tissue injury after TKA. This study included 30 consecutive CJ-TKAs followed by 30 consecutive RA-TKAs performed by a single surgeon. Intraoperative photographs of the femur, tibia, and periarticular soft tissues were taken before implantation of prostheses. Using these outcomes, the macroscopic soft tissue injury (MASTI) classification system was developed to grade iatrogenic bone and soft tissue injuries. Interobserver and Intraobserver validity of the proposed classification system was assessed. Patients undergoing RA-TKA had reduced medial soft tissue injury in both passively correctible (P < .05) and noncorrectible varus deformities (P < .05); more pristine femoral (P < .05) and tibial (P < .05) bone resection cuts; and improved MASTI scores compared to CJ-TKA (P < .05). There was high interobserver (intraclass correlation coefficient 0.92 [95% confidence interval: 0.88-0.96], P < .05) and intraobserver agreement (intraclass correlation coefficient 0.94 [95% confidence interval: 0.92-0.97], P < .05) of the proposed MASTI classification system. There is reduced bone and periarticular soft tissue injury in patients undergoing RA-TKA compared to CJ-TKA. The proposed MASTI classification system is a reproducible grading scheme for describing iatrogenic bone and soft tissue injury in TKA. RA-TKA is associated with reduced bone and soft tissue injury compared with conventional jig-based TKA. The proposed MASTI classification may facilitate further research correlating macroscopic soft tissue injury during TKA to long-term clinical and functional outcomes. Copyright © 2018 Elsevier Inc. All rights reserved.

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

Fusion of multiple quadratic penalty function support vector machines (QPFSVM) for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-08-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. The Quadratic Penalty Function Support Vector Machine (QPFSVM) algorithm to aid in the automated detection and classification of sea mines is introduced in this paper. The QPFSVM algorithm is easy to train, simple to implement, and robust to feature space dimension. Outputs of successive SVM algorithms are cascaded in stages (fused) to improve the Probability of Classification (Pc) and reduce the number of false alarms. Even though our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to fusion of any D/C problem (e.g., automated medical diagnosis or automatic target recognition for ballistic missile defense).

21 CFR 874.1800 - Air or water caloric stimulator.

Code of Federal Regulations, 2010 CFR

2010-04-01

... vestibular function testing of a patient's body balance system. The vestibular stimulation of the...) Classification. Class I (general controls). The device is exempt from the premarket notification procedures in...

Four Levels of Moral Conflict in ISD

NASA Astrophysics Data System (ADS)

Vartiainen, Tero

This study introduces a literature-based classification of moral conflicts in information systems development (ISD). The classification describes what moral conflicts an IS professional confronts in ISD as a whole and includes intentional, functional, managerial, and societal levels. The internal structure of moral conflicts is exemplified by means of a philosophical and a business ethics theory. The limitations of the study are considered and practical implications for the teaching of computer ethics are discussed.

School Refusal Behavior: Classification, Assessment, and Treatment Issues.

ERIC Educational Resources Information Center

Lee, Marcella I.; Miltenberger, Raymond G.

1996-01-01

Discusses diagnostic and functional classification, assessment, and treatment approaches for school refusal behavior. Diagnostic classification focuses on separation anxiety disorder, specific phobia, social phobia, depression, and truancy. Functional classification focuses on the maintaining consequences of the behavior, such as avoidance of…

Supervised pixel classification using a feature space derived from an artificial visual system

NASA Technical Reports Server (NTRS)

Baxter, Lisa C.; Coggins, James M.

1991-01-01

Image segmentation involves labelling pixels according to their membership in image regions. This requires the understanding of what a region is. Using supervised pixel classification, the paper investigates how groups of pixels labelled manually according to perceived image semantics map onto the feature space created by an Artificial Visual System. Multiscale structure of regions are investigated and it is shown that pixels form clusters based on their geometric roles in the image intensity function, not by image semantics. A tentative abstract definition of a 'region' is proposed based on this behavior.

18 CFR 367.30 - Cost accumulation system for associate companies.

Code of Federal Regulations, 2010 CFR

2010-04-01

... the functional processes of the associate companies served. To permit the classification, each service... all service company employees in order to support the accounting allocation of all expenses assignable...

Hand Function in Relation to Brain Lesions and Corticomotor-Projection Pattern in Children with Unilateral Cerebral Palsy

ERIC Educational Resources Information Center

Holmstrom, Linda; Vollmer, Brigitte; Tedroff, Kristina; Islam, Mominul; Persson, Jonas Ke; Kits, Annika; Forssberg, Hans; Eliasson, Ann-Christin

2010-01-01

Aim: To investigate relationships between hand function, brain lesions, and corticomotor projections in children with unilateral cerebral palsy (CP). Method: The study included 17 children (nine males, eight females; mean age 11.4 [SD 2.4] range 7-16y), with unilateral CP at Gross Motor Function Classification System level I and Manual Ability…

A systematic literature review of the situation of the International Classification of Functioning, Disability, and Health and the International Classification of Functioning, Disability, and Health-Children and Youth version in education: a useful tool or a flight of fancy?

PubMed

Moretti, Marta; Alves, Ines; Maxwell, Gregor

2012-02-01

This article presents the outcome of a systematic literature review exploring the applicability of the International Classification of Functioning, Disability, and Health (ICF) and its Children and Youth version (ICF-CY) at various levels and in processes within the education systems in different countries. A systematic database search using selected search terms has been used. The selection of studies was then refined further using four protocols: inclusion and exclusion protocols at abstract and full text and extraction levels along with a quality protocol. Studies exploring the direct relationship between education and the ICF/ICF-CY were sought.As expected, the results show a strong presence of studies from English-speaking countries, namely from Europe and North America. The articles were mainly published in noneducational journals. The most used ICF/ICF-CY components are activity and participation, participation, and environmental factors. From the analysis of the papers included, the results show that the ICF/ICF-CY is currently used as a research tool, theoretical framework, and tool for implementing educational processes. The ICF/ICF-CY can provide a useful language to the education field where there is currently a lot of disparity in theoretical, praxis, and research issues. Although the systematic literature review does not report a high incidence of the use of the ICF/ICF-CY in education, the results show that the ICF/ICF-CY model and classification have potential to be applied in education systems.

Mining disease fingerprints from within genetic pathways.

PubMed

Nabhan, Ahmed Ragab; Sarkar, Indra Neil

2012-01-01

Mining biological networks can be an effective means to uncover system level knowledge out of micro level associations, such as encapsulated in genetic pathways. Analysis of human disease genetic pathways can lead to the identification of major mechanisms that may underlie disorders at an abstract functional level. The focus of this study was to develop an approach for structural pattern analysis and classification of genetic pathways of diseases. A probabilistic model was developed to capture characteristic components ('fingerprints') of functionally annotated pathways. A probability estimation procedure of this model searched for fingerprints in each disease pathway while improving probability estimates of model parameters. The approach was evaluated on data from the Kyoto Encyclopedia of Genes and Genomes (consisting of 56 pathways across seven disease categories). Based on the achieved average classification accuracy of up to ~77%, the findings suggest that these fingerprints may be used for classification and discovery of genetic pathways.

Mining Disease Fingerprints From Within Genetic Pathways

PubMed Central

Nabhan, Ahmed Ragab; Sarkar, Indra Neil

2012-01-01

Mining biological networks can be an effective means to uncover system level knowledge out of micro level associations, such as encapsulated in genetic pathways. Analysis of human disease genetic pathways can lead to the identification of major mechanisms that may underlie disorders at an abstract functional level. The focus of this study was to develop an approach for structural pattern analysis and classification of genetic pathways of diseases. A probabilistic model was developed to capture characteristic components (‘fingerprints’) of functionally annotated pathways. A probability estimation procedure of this model searched for fingerprints in each disease pathway while improving probability estimates of model parameters. The approach was evaluated on data from the Kyoto Encyclopedia of Genes and Genomes (consisting of 56 pathways across seven disease categories). Based on the achieved average classification accuracy of up to ∼77%, the findings suggest that these fingerprints may be used for classification and discovery of genetic pathways. PMID:23304411

Image classification at low light levels

NASA Astrophysics Data System (ADS)

Wernick, Miles N.; Morris, G. Michael

1986-12-01

An imaging photon-counting detector is used to achieve automatic sorting of two image classes. The classification decision is formed on the basis of the cross correlation between a photon-limited input image and a reference function stored in computer memory. Expressions for the statistical parameters of the low-light-level correlation signal are given and are verified experimentally. To obtain a correlation-based system for two-class sorting, it is necessary to construct a reference function that produces useful information for class discrimination. An expression for such a reference function is derived using maximum-likelihood decision theory. Theoretically predicted results are used to compare on the basis of performance the maximum-likelihood reference function with Fukunaga-Koontz basis vectors and average filters. For each method, good class discrimination is found to result in milliseconds from a sparse sampling of the input image.

Classification of cardiac patient states using artificial neural networks

PubMed Central

Kannathal, N; Acharya, U Rajendra; Lim, Choo Min; Sadasivan, PK; Krishnan, SM

2003-01-01

Electrocardiogram (ECG) is a nonstationary signal; therefore, the disease indicators may occur at random in the time scale. This may require the patient be kept under observation for long intervals in the intensive care unit of hospitals for accurate diagnosis. The present study examined the classification of the states of patients with certain diseases in the intensive care unit using their ECG and an Artificial Neural Networks (ANN) classification system. The states were classified into normal, abnormal and life threatening. Seven significant features extracted from the ECG were fed as input parameters to the ANN for classification. Three neural network techniques, namely, back propagation, self-organizing maps and radial basis functions, were used for classification of the patient states. The ANN classifier in this case was observed to be correct in approximately 99% of the test cases. This result was further improved by taking 13 features of the ECG as input for the ANN classifier. PMID:19649222

Design of Medians for Principal Arterials

DOT National Transportation Integrated Search

2001-08-01

Public highways and streets have dual but competing roles: to provide property access and to move through traffic. Highway functional classification systems recognize the competition between access and flow, generally specifying that principal arteri...

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy

PubMed Central

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system. PMID:27835638

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PubMed

Ling, Qing-Hua; Song, Yu-Qing; Han, Fei; Yang, Dan; Huang, De-Shuang

2016-01-01

For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is one of suitable base-classifiers for ensemble systems because of its fast learning speed, simple structure and good generalization performance. In this paper, to obtain a more compact ensemble system with improved convergence performance, an improved ensemble of RVFL based on attractive and repulsive particle swarm optimization (ARPSO) with double optimization strategy is proposed. In the proposed method, ARPSO is applied to select and combine the candidate RVFL. As for using ARPSO to select the optimal base RVFL, ARPSO considers both the convergence accuracy on the validation data and the diversity of the candidate ensemble system to build the RVFL ensembles. In the process of combining RVFL, the ensemble weights corresponding to the base RVFL are initialized by the minimum norm least-square method and then further optimized by ARPSO. Finally, a few redundant RVFL is pruned, and thus the more compact ensemble of RVFL is obtained. Moreover, in this paper, theoretical analysis and justification on how to prune the base classifiers on classification problem is presented, and a simple and practically feasible strategy for pruning redundant base classifiers on both classification and regression problems is proposed. Since the double optimization is performed on the basis of the single optimization, the ensemble of RVFL built by the proposed method outperforms that built by some single optimization methods. Experiment results on function approximation and classification problems verify that the proposed method could improve its convergence accuracy as well as reduce the complexity of the ensemble system.

Self-care and mobility skills in children with cerebral palsy, related to their manual ability and gross motor function classifications.

PubMed

Öhrvall, Ann-Marie; Eliasson, Ann-Christin; Löwing, Kristina; Ödman, Pia; Krumlinde-Sundholm, Lena

2010-11-01

The aim of this study was to investigate the acquisition of self-care and mobility skills in children with cerebral palsy (CP) in relation to their manual ability and gross motor function. Data from the Pediatric Evaluation of Disability Inventory (PEDI) self-care and mobility functional skill scales, the Manual Ability Classification System (MACS), and the Gross Motor Function Classification System (GMFCS) were collected from 195 children with CP (73 females, 122 males; mean age 8 y 1 mo; SD 3 y 11 mo; range 3-15 y); 51% had spastic bilateral CP, 36% spastic unilateral CP, 8% dyskinetic CP, and 3% ataxic CP. The percentage of children classified as MACS levels I to V was 28%, 34%, 17%, 7%, and 14% respectively, and classified as GMFCS levels I to V was 46%, 16%, 15%, 11%, and 12% respectively. Children classified as MACS and GMFCS levels I or II scored higher than children in MACS and GMFCS levels III to V on both the self-care and mobility domains of the PEDI, with significant differences between all classification levels (p<0.001). The stepwise multiple regression analysis verified that MACS was the strongest predictor of self-care skills (66%) and that GMFCS was the strongest predictor of mobility skills (76%). A strong correlation between age and self-care ability was found among children classified as MACS level I or II and between age and mobility among children classified as GMFCS level I. Many of these children achieved independence, but at a later age than typically developing children. Children at other MACS and GMFCS levels demonstrated minimal progress with age. Knowledge of a child's MACS and GMFCS level can be useful when discussing expectations of, and goals for, the development of functional skills. © The Authors. Journal compilation © Mac Keith Press 2010.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, J.; Wei, T.Y.C.

1993-11-23

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, Jaques; Wei, Thomas Y. C.

1993-01-01

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

Ensemble of classifiers for ontology enrichment

NASA Astrophysics Data System (ADS)

Semenova, A. V.; Kureichik, V. M.

2018-05-01

A classifier is a basis of ontology learning systems. Classification of text documents is used in many applications, such as information retrieval, information extraction, definition of spam. A new ensemble of classifiers based on SVM (a method of support vectors), LSTM (neural network) and word embedding are suggested. An experiment was conducted on open data, which allows us to conclude that the proposed classification method is promising. The implementation of the proposed classifier is performed in the Matlab using the functions of the Text Analytics Toolbox. The principal difference between the proposed ensembles of classifiers is the high quality of classification of data at acceptable time costs.

Performance of resonant radar target identification algorithms using intra-class weighting functions

NASA Astrophysics Data System (ADS)

Mustafa, A.

The use of calibrated resonant-region radar cross section (RCS) measurements of targets for the classification of large aircraft is discussed. Errors in the RCS estimate of full scale aircraft flying over an ocean, introduced by the ionospheric variability and the sea conditions were studied. The Weighted Target Representative (WTR) classification algorithm was developed, implemented, tested and compared with the nearest neighbor (NN) algorithm. The WTR-algorithm has a low sensitivity to the uncertainty in the aspect angle of the unknown target returns. In addition, this algorithm was based on the development of a new catalog of representative data which reduces the storage requirements and increases the computational efficiency of the classification system compared to the NN-algorithm. Experiments were designed to study and evaluate the characteristics of the WTR- and the NN-algorithms, investigate the classifiability of targets and study the relative behavior of the number of misclassifications as a function of the target backscatter features. The classification results and statistics were shown in the form of performance curves, performance tables and confusion tables.

Classification and Quality Evaluation of Tobacco Leaves Based on Image Processing and Fuzzy Comprehensive Evaluation

PubMed Central

Zhang, Fan; Zhang, Xinhong

2011-01-01

Most of classification, quality evaluation or grading of the flue-cured tobacco leaves are manually operated, which relies on the judgmental experience of experts, and inevitably limited by personal, physical and environmental factors. The classification and the quality evaluation are therefore subjective and experientially based. In this paper, an automatic classification method of tobacco leaves based on the digital image processing and the fuzzy sets theory is presented. A grading system based on image processing techniques was developed for automatically inspecting and grading flue-cured tobacco leaves. This system uses machine vision for the extraction and analysis of color, size, shape and surface texture. Fuzzy comprehensive evaluation provides a high level of confidence in decision making based on the fuzzy logic. The neural network is used to estimate and forecast the membership function of the features of tobacco leaves in the fuzzy sets. The experimental results of the two-level fuzzy comprehensive evaluation (FCE) show that the accuracy rate of classification is about 94% for the trained tobacco leaves, and the accuracy rate of the non-trained tobacco leaves is about 72%. We believe that the fuzzy comprehensive evaluation is a viable way for the automatic classification and quality evaluation of the tobacco leaves. PMID:22163744

A Temporal Mining Framework for Classifying Un-Evenly Spaced Clinical Data: An Approach for Building Effective Clinical Decision-Making System.

PubMed

Jane, Nancy Yesudhas; Nehemiah, Khanna Harichandran; Arputharaj, Kannan

2016-01-01

Clinical time-series data acquired from electronic health records (EHR) are liable to temporal complexities such as irregular observations, missing values and time constrained attributes that make the knowledge discovery process challenging. This paper presents a temporal rough set induced neuro-fuzzy (TRiNF) mining framework that handles these complexities and builds an effective clinical decision-making system. TRiNF provides two functionalities namely temporal data acquisition (TDA) and temporal classification. In TDA, a time-series forecasting model is constructed by adopting an improved double exponential smoothing method. The forecasting model is used in missing value imputation and temporal pattern extraction. The relevant attributes are selected using a temporal pattern based rough set approach. In temporal classification, a classification model is built with the selected attributes using a temporal pattern induced neuro-fuzzy classifier. For experimentation, this work uses two clinical time series dataset of hepatitis and thrombosis patients. The experimental result shows that with the proposed TRiNF framework, there is a significant reduction in the error rate, thereby obtaining the classification accuracy on an average of 92.59% for hepatitis and 91.69% for thrombosis dataset. The obtained classification results prove the efficiency of the proposed framework in terms of its improved classification accuracy.

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.

PubMed

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

NASA Astrophysics Data System (ADS)

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Improved Classification of Lung Cancer Using Radial Basis Function Neural Network with Affine Transforms of Voss Representation.

PubMed

Adetiba, Emmanuel; Olugbara, Oludayo O

2015-01-01

Lung cancer is one of the diseases responsible for a large number of cancer related death cases worldwide. The recommended standard for screening and early detection of lung cancer is the low dose computed tomography. However, many patients diagnosed die within one year, which makes it essential to find alternative approaches for screening and early detection of lung cancer. We present computational methods that can be implemented in a functional multi-genomic system for classification, screening and early detection of lung cancer victims. Samples of top ten biomarker genes previously reported to have the highest frequency of lung cancer mutations and sequences of normal biomarker genes were respectively collected from the COSMIC and NCBI databases to validate the computational methods. Experiments were performed based on the combinations of Z-curve and tetrahedron affine transforms, Histogram of Oriented Gradient (HOG), Multilayer perceptron and Gaussian Radial Basis Function (RBF) neural networks to obtain an appropriate combination of computational methods to achieve improved classification of lung cancer biomarker genes. Results show that a combination of affine transforms of Voss representation, HOG genomic features and Gaussian RBF neural network perceptibly improves classification accuracy, specificity and sensitivity of lung cancer biomarker genes as well as achieving low mean square error.

23 CFR 470.105 - Urban area boundaries and highway functional classification.

Code of Federal Regulations, 2010 CFR

2010-04-01

... classification. 470.105 Section 470.105 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION... criteria and procedures are provided in the FHWA publication “Highway Functional Classification—Concepts... functional classification shall be mapped and submitted to the Federal Highway Administration (FHWA) for...

Challenges of rehabilitation case mix measurement in Ontario hospitals.

PubMed

Sutherland, Jason Murray; Walker, Jan

2008-03-01

Case mix classification systems have been adopted in many countries as a method to manage and finance healthcare in acute care settings; the most popular systems are based on diagnosis related groups. The most successful of those case mix systems differentiate patient types by reflecting both the intensity of resources consumed and patient acuity. Case mix systems for use with non-acute hospital activity have not been as wide-spread; other than in the United States, little attention has been directed towards case mix classification for rehabilitation activity. In a province with over 13 million inhabitants with 2496 rehabilitation beds, inpatient rehabilitation is an important component of hospital care in Ontario, Canada, and consists of the spectrum of intensive rehabilitation activities intended to restore function. Although case mix adjusted activity has been the currency in Ontario's Integrated Population Based Allocation hospital funding formula, rehabilitation activity has not been subjected to case mix measurement. A project to examine case mix classification for adult inpatient rehabilitation activity was initiated by the Ontario Ministry of Health and Long-Term Care whose outcome was a case mix system and associated cost weights that would result in rehabilitation activity being incorporated into the hospital funding formula. The process described in this study provides Ontario's provincial government with a case mix classification system for adult inpatient rehabilitation activity although there remain areas for improvement.

Reproducibility of neuroimaging analyses across operating systems

PubMed Central

Glatard, Tristan; Lewis, Lindsay B.; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C.

2015-01-01

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed. PMID:25964757

Reproducibility of neuroimaging analyses across operating systems.

PubMed

Glatard, Tristan; Lewis, Lindsay B; Ferreira da Silva, Rafael; Adalat, Reza; Beck, Natacha; Lepage, Claude; Rioux, Pierre; Rousseau, Marc-Etienne; Sherif, Tarek; Deelman, Ewa; Khalili-Mahani, Najmeh; Evans, Alan C

2015-01-01

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed.

Inference of Ancestry in Forensic Analysis II: Analysis of Genetic Data.

PubMed

Santos, Carla; Phillips, Chris; Gomez-Tato, A; Alvarez-Dios, J; Carracedo, Ángel; Lareu, Maria Victoria

2016-01-01

Three approaches applicable to the analysis of forensic ancestry-informative marker data-STRUCTURE, principal component analysis, and the Snipper Bayesian classification system-are reviewed. Detailed step-by-step guidance is provided for adjusting parameter settings in STRUCTURE with particular regard to their effect when differentiating populations. Several enhancements to the Snipper online forensic classification portal are described, highlighting the added functionality they bring to particular aspects of ancestry-informative SNP analysis in a forensic context.

Functional Constructivism: In Search of Formal Descriptors.

PubMed

Trofimova, Irina

2017-10-01

The Functional Constructivism (FC) paradigm is an alternative to behaviorism and considers behavior as being generated every time anew, based on an individual's capacities, environmental resources and demands. Walter Freeman's work provided us with evidence supporting the FC principles. In this paper we make parallels between gradual construction processes leading to the formation of individual behavior and habits, and evolutionary processes leading to the establishment of biological systems. Referencing evolutionary theory, several formal descriptors of such processes are proposed. These FC descriptors refer to the most universal aspects for constructing consistent structures: expansion of degrees of freedom, integration processes based on internal and external compatibility between systems and maintenance processes, all given in four different classes of systems: (a) Zone of Proximate Development (poorly defined) systems; (b) peer systems with emerging reproduction of multiple siblings; (c) systems with internalized integration of behavioral elements ('cruise controls'); and (d) systems capable of handling low-probability, not yet present events. The recursive dynamics within this set of descriptors acting on (traditional) downward, upward and horizontal directions of evolution, is conceptualized as diagonal evolution, or di-evolution. Two examples applying these FC descriptors to taxonomy are given: classification of the functionality of neuro-transmitters and temperament traits; classification of mental disorders. The paper is an early step towards finding a formal language describing universal tendencies in highly diverse, complex and multi-level transient systems known in ecology and biology as 'contingency cycles.'

The distance function effect on k-nearest neighbor classification for medical datasets.

PubMed

Hu, Li-Yu; Huang, Min-Wei; Ke, Shih-Wen; Tsai, Chih-Fong

2016-01-01

K-nearest neighbor (k-NN) classification is conventional non-parametric classifier, which has been used as the baseline classifier in many pattern classification problems. It is based on measuring the distances between the test data and each of the training data to decide the final classification output. Since the Euclidean distance function is the most widely used distance metric in k-NN, no study examines the classification performance of k-NN by different distance functions, especially for various medical domain problems. Therefore, the aim of this paper is to investigate whether the distance function can affect the k-NN performance over different medical datasets. Our experiments are based on three different types of medical datasets containing categorical, numerical, and mixed types of data and four different distance functions including Euclidean, cosine, Chi square, and Minkowsky are used during k-NN classification individually. The experimental results show that using the Chi square distance function is the best choice for the three different types of datasets. However, using the cosine and Euclidean (and Minkowsky) distance function perform the worst over the mixed type of datasets. In this paper, we demonstrate that the chosen distance function can affect the classification accuracy of the k-NN classifier. For the medical domain datasets including the categorical, numerical, and mixed types of data, K-NN based on the Chi square distance function performs the best.

Systemic Analysis of Brain Mechanisms Underlying Learning Disabilities: An Introduction to the Brain Behavior Relationship.

ERIC Educational Resources Information Center

Scaramella-Nowinski, Valerie L.

The paper presents a discussion of human mental processes as they relate to learning disabilities. Pathognomonic symptoms associated with disturbances to brain areas or functional systems are discussed, as well as treatment procedures. This brain behavior relationship is offered as a basis for a classification system that is seen to more clearly…

General RMP Guidance - Appendix B: Selected NAICS Codes

EPA Pesticide Factsheets

This appendix contains a list of selected 2002 North American Industry Classification System (NAICS) codes used by Federal statistical agencies, in designating business types or functions in categories such as farming, manufacturing, and waste management.

Change in mobility function and its causes in adults with cerebral palsy by Gross Motor Function Classification System level: A cross-sectional questionnaire study.

PubMed

Himuro, Nobuaki; Mishima, Reiko; Seshimo, Takashi; Morishima, Toshibumi; Kosaki, Keisuke; Ibe, Shigeharu; Asagai, Yoshimi; Minematsu, Koji; Kurita, Kazuhiro; Okayasu, Tsutomu; Shimura, Tsukasa; Hoshino, Kotaro; Suzuki, Toshiro; Yanagizono, Taiichiro

2018-04-07

The prognosis for mobility function by Gross Motor Function Classification System (GMFCS) level is vital as a guide to rehabilitation for people with cerebral palsy. This study sought to investigate change in mobility function and its causes in adults with cerebral palsy by GMFCS level. We conducted a cross-sectional questionnaire study. A total of 386 participants (26 y 8 m, SD 5 y 10 m) with cerebral palsy were analyzed. Participant numbers by GMFCS level were: I (53), II (139), III (74) and IV (120). The median age of participants with peak mobility function in GMFCS level III was younger than that in the other levels. 48% had experienced a decline in mobility. A Kaplan-Meier plot showed the risk of mobility decline increased in GMFCS level III; the hazard ratio was 1.97 (95% CI, 1.20-3.23) compared with level I. The frequently reported causes of mobility decline were changes in environment, and illness and injury in GMFCS level III, stiffness and deformity in level IV, and reduced physical activity in level II and III. Peak mobility function and mobility decline occurred at a younger age in GMFCS level III, with the cause of mobility decline differing by GMFCS level.

Introduction of the gross motor function classification system in Venezuela--a model for knowledge dissemination.

PubMed

Löwing, Kristina; Arredondo, Ynes C; Tedroff, Marika; Tedroff, Kristina

2015-09-04

A current worldwide common goal is to optimize the health and well-being of children with cerebral palsy (CP). In order to reach that goal, for this heterogeneous group, a common language and classification systems are required to predict development and offer evidence based interventions. In most countries in Africa, South America, Asia and Eastern Europe the classification systems for CP are unfamiliar and rarely used. Education and implementation are required. The specific aims of this study were to examine a model in order to introduce the Gross Motor Function Classification System (GMFCS-E&R) in Venezuela, and to examine the validity and the reliability. Children with CP, registered at a National child rehabilitation centre in Venezuela, were invited to participate. The Spanish version of GMFCS-E&R was used. The Wilson mobility scale was translated and used to examine the concurrent validity. A structured questionnaire, comprising aspects of mobility and gross motor function, was constructed. In addition, each child was filmed. A paediatrician in Venezuela received supervised self-education in GMFCS-E&R and the Wilson mobility scale. A Swedish student was educated in GMFCS-E&R and the Wilson mobility scale prior to visiting Venezuela. In Venezuela, all children were classified and scored by the paediatrician and student independently. An experienced paediatric physiotherapist (PT) in Sweden made independent GMFCS-E&R classifications and Wilson mobility scale scorings, accomplished through merging data from the structured questionnaire with observations of the films. Descriptive statistics were used and reliability was presented with weighted Kappa (Kw). Spearman's correlation coefficient was calculated to explore the concurrent validity between GMFCS-E&R and Wilson mobility scale. Eighty-eight children (56 boys), mean age 10 years (3-18), with CP participated. The inter-rater reliability of GMFCS-E&R between; the paediatrician and the PT was Kw = 0.85 (95% CI: 0.75-0.88), the PT and student was Kw = 0.91 (95% CI: 0.86-0.95) and the paediatrician and student was Kw = 0.85 (95 % CI: 0.79-0.90). The correlations between GMFCS-E&R and Wilson mobility scale were high rs =0.94-0.95 (p < 0.001). In a setting with no previous knowledge of GMFCS-E&R, the model with education, supervised self-education and practice was efficient and resulted in very good reliability and validity.

Treatment based on the type of infected TKA improves infection control.

PubMed

Kim, Young-Hoo; Choi, Yoowang; Kim, Jun-Shik

2011-04-01

A classification system with four types of infected TKAs has been commonly used to determine treatment, especially with regard to whether the prosthesis should be removed or retained. We asked whether (1) the classification-dictated treatment of the four types of infection after TKA would control infection and maintain functional TKA; (2) repeated débridement and two-stage TKA would further improve the infection control rate after initial treatment; and (3) fixation of TKA prosthesis to the host bone was achieved. We retrospectively reviewed 114 patients with 116 infected TKAs. We determined the infection control rate after initial treatment, repeated débridement and two-stage TKA. We evaluated the functional and radiographic results using the Knee Society and Hospital for Special Surgery knee scoring systems. The minimum followup was 2 years (mean, 5.6 years; range, 2-8 years). The overall infection control rate was 100% in all patients. All patients with early superficial postoperative infection, 94% of patients with early deep postoperative infection, 96% of patients with late chronic infection, and 86% of patients with acute hematogenous infection maintained functioning knee prosthesis at the final followup. One hundred nine of the 114 patients could walk with no or only slight pain and maintained functioning knee prostheses. These 109 patients had stable fixation of the TKA prosthesis to host bone. The techniques proposed by the classification effectively controlled infection and maintained functional TKA with firm fixation of the TKA prosthesis in most patients. Repeated débridement and two-stage TKA further improved the control of infection and functional TKA after initial treatment. Level IV, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.

DIF Trees: Using Classification Trees to Detect Differential Item Functioning

ERIC Educational Resources Information Center

Vaughn, Brandon K.; Wang, Qiu

2010-01-01

A nonparametric tree classification procedure is used to detect differential item functioning for items that are dichotomously scored. Classification trees are shown to be an alternative procedure to detect differential item functioning other than the use of traditional Mantel-Haenszel and logistic regression analysis. A nonparametric…

[Spatial-temporal analysis and clinical findings of gait: comparison of two modalities of treatment in children with cerebral palsy-spastic hemiplegia. Preliminary report].

PubMed

Arellano-Martínez, Irma Tamara; Rodríguez-Reyes, Gerardo; Quiñones-Uriostegui, Ivet; Arellano-Saldaña, María Elena

2013-01-01

Cerebral palsy is the most common cause of disability among children. Parent's main concerns are the acquisition and improvement of gait. The aim of this study was to compare long term results of the effect of two modalities of gait training. Quantitative measurement of gait and clinical assessment of the gross motor function classification system and Modified Ashworth Scale were perfomed in 14 patients with Cerebral palsy -spastic hemiplegia and randomizedly assigned into two groups of treatment: the first one using a driven gait orthosis (Lokomat(®)) and the second a gait training a long a rail inside a hydrotherapy tank. Measurements and assessments, above described, were performed immediately and one year after the treatment concluded. Significant change was observed in the gross motor function classification system from II to I among children (p=0.042) and a positive correlation between the shape functional of the march and the gross motor function classification system (r = 0.54, p = 0.042). Patients on the Lokomat(®) training improved on gait symmetry over patients on the conventional therapy (p = 0.05). A year after, this intervention showed tendency to kept the gait patterns only on patients treated with the Lokomat(®) Benefit obtained with either modality was evident for both groups. However, residual effects observed on the Lokomat group, either in clinical assessment or gait parameters, were more promising than in the conventional therapy. Due to the size of the sample used in this study the results are not conclusive and more research must be done on this subject in long term time horizon.

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

Classification of Airflow Limitation Based on z-Score Underestimates Mortality in Patients with Chronic Obstructive Pulmonary Disease.

PubMed

Tejero, Elena; Prats, Eva; Casitas, Raquel; Galera, Raúl; Pardo, Paloma; Gavilán, Adelaida; Martínez-Cerón, Elisabet; Cubillos-Zapata, Carolina; Del Peso, Luis; García-Río, Francisco

2017-08-01

Global Lung Function Initiative recommends reporting lung function measures as z-score, and a classification of airflow limitation (AL) based on this parameter has recently been proposed. To evaluate the prognostic capacity of the AL classifications based on z-score or percentage predicted of FEV 1 in patients with chronic obstructive pulmonary disease (COPD). A cohort of 2,614 patients with COPD recruited outside the hospital setting was examined after a mean (± SD) of 57 ± 13 months of follow-up, totaling 10,322 person-years. All-cause mortality was analyzed, evaluating the predictive capacity of several AL staging systems. Based on Global Initiative for Chronic Obstructive Lung Disease guidelines, 461 patients (17.6%) had mild, 1,452 (55.5%) moderate, 590 (22.6%) severe, and 111 (4.2%) very severe AL. According to z-score classification, 66.3% of patients remained with the same severity, whereas 23.7% worsened and 10.0% improved. Unlike other staging systems, patients with severe AL according to z-score had higher mortality than those with very severe AL (increase of risk by 5.2 and 3.9 times compared with mild AL, respectively). The predictive capacity for 5-year survival was slightly higher for FEV 1 expressed as percentage of predicted than as z-score (area under the curve: 0.714-0.760 vs. 0.649-0.708, respectively). A severity-dependent relationship between AL grades by z-score and mortality was only detected in patients younger than age 60 years. In patients with COPD, the AL classification based on z-score predicts worse mortality than those based on percentage of predicted. It is possible that the z-score underestimates AL severity in patients older than 60 years of age with severe functional impairment.

Autonomous learning by simple dynamical systems with a discrete-time formulation

NASA Astrophysics Data System (ADS)

Bilen, Agustín M.; Kaluza, Pablo

2017-05-01

We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.

Comparison of World Health Organization and Asia-Pacific body mass index classifications in COPD patients.

PubMed

Lim, Jeong Uk; Lee, Jae Ha; Kim, Ju Sang; Hwang, Yong Il; Kim, Tae-Hyung; Lim, Seong Yong; Yoo, Kwang Ha; Jung, Ki-Suck; Kim, Young Kyoon; Rhee, Chin Kook

2017-01-01

A low body mass index (BMI) is associated with increased mortality and low health-related quality of life in patients with COPD. The Asia-Pacific classification of BMI has a lower cutoff for overweight and obese categories compared to the World Health Organization (WHO) classification. The present study assessed patients with COPD among different BMI categories according to two BMI classification systems: WHO and Asia-Pacific. Patients with COPD aged 40 years or older from the Korean COPD Subtype Study cohort were selected for evaluation. We enrolled 1,462 patients. Medical history including age, sex, St George's Respiratory Questionnaire (SGRQ-C), the modified Medical Research Council (mMRC) dyspnea scale, and post-bronchodilator forced expiratory volume in 1 second (FEV 1 ) were evaluated. Patients were categorized into different BMI groups according to the two BMI classification systems. FEV 1 and the diffusing capacity of the lung for carbon monoxide (DLCO) percentage revealed an inverse "U"-shaped pattern as the BMI groups changed from underweight to obese when WHO cutoffs were applied. When Asia-Pacific cutoffs were applied, FEV 1 and DLCO (%) exhibited a linearly ascending relationship as the BMI increased, and the percentage of patients in the overweight and obese groups linearly decreased with increasing severity of the Global Initiative for Chronic Obstructive Lung Disease criteria. From the underweight to the overweight groups, SGRQ-C and mMRC had a decreasing relationship in both the WHO and Asia-Pacific classifications. The prevalence of comorbidities in the different BMI groups showed similar trends in both BMI classifications systems. The present study demonstrated that patients with COPD who have a high BMI have better pulmonary function and health-related quality of life and reduced dyspnea symptoms. Furthermore, the Asia-Pacific BMI classification more appropriately reflects the correlation of obesity and disease manifestation in Asian COPD patients than the WHO classification.

Seizure classification in EEG signals utilizing Hilbert-Huang transform

PubMed Central

2011-01-01

Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Method Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. Results The t-test results in a P-value < 0.02 and the clustering leads to accurate (94%) and specific (96%) results. The proposed method is also contrasted against the Multivariate Empirical Mode Decomposition that reaches 80% accuracy. Comparison results strengthen the contribution of this paper not only from the accuracy point of view but also with respect to its fast response and ease to use. Conclusion An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool. PMID:21609459

Seizure classification in EEG signals utilizing Hilbert-Huang transform.

PubMed

Oweis, Rami J; Abdulhay, Enas W

2011-05-24

Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. The t-test results in a P-value < 0.02 and the clustering leads to accurate (94%) and specific (96%) results. The proposed method is also contrasted against the Multivariate Empirical Mode Decomposition that reaches 80% accuracy. Comparison results strengthen the contribution of this paper not only from the accuracy point of view but also with respect to its fast response and ease to use. An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool.

"Interactive Classification Technology"

NASA Technical Reports Server (NTRS)

deBessonet, Cary

1999-01-01

The investigators are upgrading a knowledge representation language called SL (Symbolic Language) and an automated reasoning system called SMS (Symbolic Manipulation System) to enable the technologies to be used in automated reasoning and interactive classification systems. The overall goals of the project are: a) the enhancement of the representation language SL to accommodate multiple perspectives and a wider range of meaning; b) the development of a sufficient set of operators to enable the interpreter of SL to handle representations of basic cognitive acts; and c) the development of a default inference scheme to operate over SL notation as it is encoded. As to particular goals the first-year work plan focused on inferencing and.representation issues, including: 1) the development of higher level cognitive/ classification functions and conceptual models for use in inferencing and decision making; 2) the specification of a more detailed scheme of defaults and the enrichment of SL notation to accommodate the scheme; and 3) the adoption of additional perspectives for inferencing.

Low back related leg pain: an investigation of construct validity of a new classification system.

PubMed

Schäfer, Axel G M; Hall, Toby M; Rolke, Roman; Treede, Rolf-Detlef; Lüdtke, Kerstin; Mallwitz, Joachim; Briffa, Kathryn N

2014-01-01

Leg pain is associated with back pain in 25-65% of all cases and classified as somatic referred pain or radicular pain. However, distinction between the two may be difficult as different pathomechanisms may cause similar patterns of pain. Therefore a pathomechanism based classification system was proposed, with four distinct hierarchical and mutually exclusive categories: Neuropathic Sensitization (NS) comprising major features of neuropathic pain with sensory sensitization; Denervation (D) arising from significant axonal compromise; Peripheral Nerve Sensitization (PNS) with marked nerve trunk mechanosensitivity; and Musculoskeletal (M) with pain referred from musculoskeletal structures. To investigate construct validity of the classification system. Construct validity was investigated by determining the relationship of nerve functioning with subgroups of patients and asymptomatic controls. Thus somatosensory profiles of subgroups of patients with low back related leg pain (LBRLP) and healthy controls were determined by a comprehensive quantitative sensory test (QST) protocol. It was hypothesized that subgroups of patients and healthy controls would show differences in QST profiles relating to underlying pathomechanisms. 77 subjects with LBRLP were recruited and classified in one of the four groups. Additionally, 18 age and gender matched asymptomatic controls were measured. QST revealed signs of pain hypersensitivity in group NS and sensory deficits in group D whereas Groups PNS and M showed no significant differences when compared to the asymptomatic group. These findings support construct validity for two of the categories of the new classification system, however further research is warranted to achieve construct validation of the classification system as a whole.

Physical therapy for facial paralysis: a tailored treatment approach.

PubMed

Brach, J S; VanSwearingen, J M

1999-04-01

Bell palsy is an acute facial paralysis of unknown etiology. Although recovery from Bell palsy is expected without intervention, clinical experience suggests that recovery is often incomplete. This case report describes a classification system used to guide treatment and to monitor recovery of an individual with facial paralysis. The patient was a 71-year-old woman with complete left facial paralysis secondary to Bell palsy. Signs and symptoms were assessed using a standardized measure of facial impairment (Facial Grading System [FGS]) and questions regarding functional limitations. A treatment-based category was assigned based on signs and symptoms. Rehabilitation involved muscle re-education exercises tailored to the treatment-based category. In 14 physical therapy sessions over 13 months, the patient had improved facial impairments (initial FGS score= 17/100, final FGS score= 68/100) and no reported functional limitations. Recovery from Bell palsy can be a complicated and lengthy process. The use of a classification system may help simplify the rehabilitation process.

Naïve Bayes classification in R.

PubMed

Zhang, Zhongheng

2016-06-01

Naïve Bayes classification is a kind of simple probabilistic classification methods based on Bayes' theorem with the assumption of independence between features. The model is trained on training dataset to make predictions by predict() function. This article introduces two functions naiveBayes() and train() for the performance of Naïve Bayes classification.

[The establishment, development and application of classification approach of freshwater phytoplankton based on the functional group: a review].

PubMed

Yang, Wen; Zhu, Jin-Yong; Lu, Kai-Hong; Wan, Li; Mao, Xiao-Hua

2014-06-01

Appropriate schemes for classification of freshwater phytoplankton are prerequisites and important tools for revealing phytoplanktonic succession and studying freshwater ecosystems. An alternative approach, functional group of freshwater phytoplankton, has been proposed and developed due to the deficiencies of Linnaean and molecular identification in ecological applications. The functional group of phytoplankton is a classification scheme based on autoecology. In this study, the theoretical basis and classification criterion of functional group (FG), morpho-functional group (MFG) and morphology-based functional group (MBFG) were summarized, as well as their merits and demerits. FG was considered as the optimal classification approach for the aquatic ecology research and aquatic environment evaluation. The application status of FG was introduced, with the evaluation standards and problems of two approaches to assess water quality on the basis of FG, index methods of Q and QR, being briefly discussed.

Experimental approaches to investigate effector translocation into host cells in the Ustilago maydis/maize pathosystem.

PubMed

Tanaka, Shigeyuki; Djamei, Armin; Presti, Libera Lo; Schipper, Kerstin; Winterberg, Sarah; Amati, Simone; Becker, Dirk; Büchner, Heike; Kumlehn, Jochen; Reissmann, Stefanie; Kahmann, Regine

2015-01-01

The fungus Ustilago maydis is a pathogen that establishes a biotrophic interaction with Zea mays. The interaction with the plant host is largely governed by more than 300 novel, secreted protein effectors, of which only four have been functionally characterized. Prerequisite to examine effector function is to know where effectors reside after secretion. Effectors can remain in the extracellular space, i.e. the plant apoplast (apoplastic effectors), or can cross the plant plasma membrane and exert their function inside the host cell (cytoplasmic effectors). The U. maydis effectors lack conserved motifs in their primary sequences that could allow a classification of the effectome into apoplastic/cytoplasmic effectors. This represents a significant obstacle in functional effector characterization. Here we describe our attempts to establish a system for effector classification into apoplastic and cytoplasmic members, using U. maydis for effector delivery. Copyright © 2015 Elsevier GmbH. All rights reserved.

Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922

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

NASA Astrophysics Data System (ADS)

Delbecque, Nele; Verdoodt, Ann

2017-04-01

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

Caracterization of adults with cerebral palsy.

PubMed

Margre, Anna L M; Reis, Maria G L; Morais, Rosane L S

2010-01-01

cerebral Palsy (CP) is a group of permanent disorders of the development of movement and posture that cause functional limitation and are attributed to non-progressive disorders which occur in the fetal or infant brain. In recent years, with the increase in life expectancy of individuals with CP, several studies have described the impact of musculoskeletal disabilities and functional limitations over the life cycle. to characterize adults with CP through sociodemographic information, classifications, general health, associated conditions, physical complications and locomotion. twenty-two adults with CP recruited from local rehabilitation centers in an inner town of Brazil participated in this study. A questionnaire was used to collect data on sociodemographic characteristics, comorbities, and physical complications. A brief physical therapy evaluation was carried out, and the Gross Motor Function Classification System (GMFCS) and the Manual Ability Classification System (MACS) were applied. Data were analyzed through descriptive statistics. the mean age was 28.7 (SD 10.6) years, 86.4% of participants lived with parents, and 4.5% were employed. Most of the sample consisted of spastic quadriplegic subjects, corresponding to levels IV and V of the GMFCS and MACS. Different comorbidities and important physical complications such as scoliosis and muscle contractures were present. More than half of the participants were unable to walk. Most participants demonstrated important restrictions in social participation and lower educational level. Adults with CP can be affected by several physical complications and progressive limitations in gait.

Comparing the predictive value of the pelvic ring injury classification systems by Tile and by Young and Burgess.

PubMed

Osterhoff, Georg; Scheyerer, Max J; Fritz, Yannick; Bouaicha, Samy; Wanner, Guido A; Simmen, Hans-Peter; Werner, Clément M L

2014-04-01

Radiology-based classifications of pelvic ring injuries and their relevance for the prognosis of morbidity and mortality are disputed in the literature. The purpose of this study was to evaluate potential differences between the pelvic ring injury classification systems by Tile and by Young and Burgess with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Two-hundred-and-eighty-five consecutive patients with pelvic ring fractures were analyzed for mortality within 30 days after admission, number of blood units and total volume of fluid infused during the first 24h after trauma, the Abbreviated Injury Severity (AIS) scores for head, chest, spine, abdomen and extremities as a function of the Tile and the Young-Burgess classifications. There was no significant relationship between occurrence of death and fracture pattern but a significant relationship between fracture pattern and need for blood units/total fluid volume for Tile (p<.001/p<.001) and Young-Burgess (p<.001/p<.001). In both classifications, open book fractures were associated with more fluid requirement and more severe injuries of the abdomen, spine and extremities (p<.05). When divided into the larger subgroups "partially stable" and "unstable", unstable fractures were associated with a higher mortality rate in the Young-Burgess system (p=.036). In both classifications, patients with unstable fractures required significantly more blood transfusions (p<.001) and total fluid infusion (p<.001) and higher AIS scores. In this first direct comparison of both classifications, we found no clinical relevant differences with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

Zariffa, José; Steeves, John D

2011-01-01

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

Brief Report: Symptom Onset Patterns and Functional Outcomes in Young Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Shumway, Stacy; Thurm, Audrey; Swedo, Susan E.; Deprey, Lesley; Barnett, Lou Ann; Amaral, David G.; Rogers, Sally J.; Ozonoff, Sally

2011-01-01

This study examined the relationship between onset status and current functioning using a recently proposed onset classification system in 272 young children with autism spectrum disorder (ASD). Participants were classified into one of the following groups, based on parent report using the Autism Diagnostic Interview-Revised: Early Onset (symptoms…

U.S. Fish and Wildlife Service 1979 wetland classification: a review

USGS Publications Warehouse

Cowardin, L.M.; Golet, F.C.

1995-01-01

In 1979 the US Fish and Wildlife Service published and adopted a classification of wetlands and deepwater habitats of the United States. The system was designed for use in a national inventory of wetlands. It was intended to be ecologically based, to furnish the mapping units needed for the inventory, and to provide national consistency in terminology and definition. We review the performance of the classification after 13 years of use. The definition of wetland is based on national lists of hydric soils and plants that occur in wetlands. Our experience suggests that wetland classifications must facilitate mapping and inventory because these data gathering functions are essential to management and preservation of the wetland resource, but the definitions and taxa must have ecological basis. The most serious problem faced in construction of the classification was lack of data for many of the diverse wetland types. Review of the performance of the classification suggests that, for the most part, it was successful in accomplishing its objectives, but that problem areas should be corrected and modification could strengthen its utility. The classification, at least in concept, could be applied outside the United States. Experience gained in use of the classification can furnish guidance as to pitfalls to be avoided in the wetland classification process.

AUTOMOTIVE DIESEL MAINTENANCE 1. UNIT XXVI, I--CATERPILLAR LUBRICATION SYSTEMS AND COMPONENTS, II--LEARNING ABOUT BRAKES (PART I).

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul. Div. of Vocational and Technical Education.

THIS MODULE OF A 30-MODULE COURSE IS DESIGNED TO DEVELOP AN UNDERSTANDING OF THE FUNCTIONS OF DIESEL ENGINE LUBRICATION SYSTEMS AND COMPONENTS AND THE PRINCIPLES OF OPERATION OF BRAKE SYSTEMS USED ON DIESEL POWERED VEHICLES. TOPICS ARE (1) THE NEED FOR OIL, (2) SERVICE CLASSIFICATION OF OILS, (3) CATERPILLAR LUBRICATION SYSTEM COMPONENTS (4)…

Brain-computer interface design using alpha wave

NASA Astrophysics Data System (ADS)

Zhao, Hai-bin; Wang, Hong; Liu, Chong; Li, Chun-sheng

2010-01-01

A brain-computer interface (BCI) is a novel communication system that translates brain activity into commands for a computer or other electronic devices. BCI system based on non-invasive scalp electroencephalogram (EEG) has become a hot research area in recent years. BCI technology can help improve the quality of life and restore function for people with severe motor disabilities. In this study, we design a real-time asynchronous BCI system using Alpha wave. The basic theory of this BCI system is alpha wave-block phenomenon. Alpha wave is the most prominent wave in the whole realm of brain activity. This system includes data acquisition, feature selection and classification. The subject can use this system easily and freely choose anyone of four commands with only short-time training. The results of the experiment show that this BCI system has high classification accuracy, and has potential application for clinical engineering and is valuable for further research.

Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.

PubMed

Vigano, Antonio A L; Morais, José A; Ciutto, Lorella; Rosenthall, Leonard; di Tomasso, Jonathan; Khan, Sarah; Olders, Henry; Borod, Manuel; Kilgour, Robert D

2017-10-01

Cachexia is a highly prevalent syndrome in cancer and chronic diseases. However, due to the heterogeneous features of cancer cachexia, its identification and classification challenge clinical practitioners. To determine the clinical relevance of a cancer cachexia classification system in advanced cancer patients. Beginning with the four-stage classification system proposed for cachexia [non-cachexia (NCa), pre-cachexia (PCa), cachexia (Ca) and refractory cachexia (RCa)], we assigned patients to these cachexia stages according to five classification criteria available in clinical practice: 1) biochemistry (high C-reactive protein or leukocytes, or hypoalbuminemia, or anemia), 2) food intake (normal/decreased), weight loss: 3) moderate (≤5%) or 4) significant (>5%/past six months) and 5) performance status (Eastern Cooperative Oncology Group Performance Status ≥ 3). We then determined if symptom severity, body composition changes, functional levels, hospitalizations and survival rates varied significantly across cachexia stages. Two-hundred and ninety-seven advanced cancer patients with primary gastrointestinal and lung tumors were included. Patients were classified into Ca (36%), PCa and RCa (21%, respectively) and NCa (15%). Significant (p < 0.05) differences were observed among cachexia stages for most of the outcome measures (symptoms, body composition, handgrip strength, emergency room visits and length of hospital stays) according to cachexia severity. Survival also differed between cachexia stages (except between PCa and Ca). Five clinical criteria can be used to stage cancer cachexia patients and predict important clinical, nutritional and functional outcomes. The lack of statistical difference between PCa and Ca in almost all clinical outcomes examined suggests either that the PCa group includes patients already affected by early cachexia or that more precise criteria are needed to differentiate PCa from Ca patients. More studies are required to validate these findings. Copyright © 2016. Published by Elsevier Ltd.

Digital processing of satellite imagery application to jungle areas of Peru

NASA Technical Reports Server (NTRS)

Pomalaza, J. C. (Principal Investigator); Pomalaza, C. A.; Espinoza, J.

1976-01-01

The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

Railroad Classification Yard Technology : An Introductory Analysis of Functions and Operations

DOT National Transportation Integrated Search

1975-05-01

A review of the basic operating characteristics and functions of railroad classification yards is presented. Introductory descriptions of terms, concepts, and problems of railroad operations involving classification yards are included in an attempt t...

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

DTIC Science & Technology

2008-11-01

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

Anaerobic Digestion II. Sludge Treatment and Disposal Course #166. Instructor's Guide [and] Student Workbook.

ERIC Educational Resources Information Center

Arasmith, E. E.

This lesson is the second of a two-part series on anaerobic digestion. Topics discussed include classification of digester by function, roof design, and temperature range, mixing systems, gas system components, operational control basics, and general safety considerations. The lesson includes an instructor's guide and student workbook. The…

Sex differences in cerebral palsy incidence and functional ability: a total population study.

PubMed

Chounti, A; Hägglund, G; Wagner, P; Westbom, L

2013-07-01

To describe gender difference in a total population of children with cerebral palsy (CP), related to subtype, gross and fine motor function, and to compare CP incidence trends in girls and boys. All 590 children with CP born in southern Sweden 1990-2005 were included. CP subtype was classified according to the Surveillance of Cerebral Palsy in Europe, gross motor function according to Gross Motor Function Classification System (GMFCS) and manual ability according to Manual Ability Classification System (MACS). Trends in CP incidence by birth year were analysed using Poisson regression modelling. There was a male predominance in all levels of GMFCS except level II, in all levels of MACS and in all CP subtypes except ataxic CP. There was no statistically significant difference between males and females regarding gross motor function or manual ability. The CP incidence trends in boys compared with girls did not change during the period 1990-2005. No equalization was detected in the incidence of CP between girls and boys during recent years in this total population. We could not confirm any consistent sex difference in motor function levels. Male sex is a risk factor for CP. ©2013 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

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.

Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas

NASA Astrophysics Data System (ADS)

Chestek, Cynthia A.; Gilja, Vikash; Blabe, Christine H.; Foster, Brett L.; Shenoy, Krishna V.; Parvizi, Josef; Henderson, Jaimie M.

2013-04-01

Objective. Brain-machine interface systems translate recorded neural signals into command signals for assistive technology. In individuals with upper limb amputation or cervical spinal cord injury, the restoration of a useful hand grasp could significantly improve daily function. We sought to determine if electrocorticographic (ECoG) signals contain sufficient information to select among multiple hand postures for a prosthetic hand, orthotic, or functional electrical stimulation system.Approach. We recorded ECoG signals from subdural macro- and microelectrodes implanted in motor areas of three participants who were undergoing inpatient monitoring for diagnosis and treatment of intractable epilepsy. Participants performed five distinct isometric hand postures, as well as four distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with two participants. Main results. Classification rates were 68%, 84% and 81% for correct identification of 5 isometric hand postures offline. Using 3 potential controls for removing sensory signals, error rates were approximately doubled on average (2.1×). A similar increase in errors (2.6×) was noted when the participant was asked to make simultaneous wrist movements along with the hand postures. In online experiments, fist versus rest was successfully classified on 97% of trials; the classification output drove a prosthetic hand. Online classification performance for a larger number of hand postures remained above chance, but substantially below offline performance. In addition, the long integration windows used would preclude the use of decoded signals for control of a BCI system. Significance. These results suggest that ECoG is a plausible source of command signals for prosthetic grasp selection. Overall, avenues remain for improvement through better electrode designs and placement, better participant training, and characterization of non-stationarities such that ECoG could be a viable signal source for grasp control for amputees or individuals with paralysis.

The multiscale classification system and grid encoding mode of ecological land in China

NASA Astrophysics Data System (ADS)

Wang, Jing; Liu, Aixia; Lin, Yifan

2017-10-01

Ecological land provides goods and services that have direct or indirect benefic to eco-environment and human welfare. In recent years, researches on ecological land have become important in the field of land changes and ecosystem management. In the study, a multi-scale classification scheme of ecological land was developed for land management based on combination of the land-use classification and the ecological function zoning in China, including eco-zone, eco-region, eco-district, land ecosystem, and ecological land-use type. The geographical spatial unit leads toward greater homogeneity from macro to micro scale. The term "ecological land-use type" is the smallest one, being important to maintain the key ecological processes in land ecosystem. Ecological land-use type was categorized into main-functional and multi-functional ecological land-use type according to its ecological function attributes and production function attributes. Main-functional type was defined as one kind of land-use type mainly providing ecological goods and function attributes, such as river, lake, swampland, shoaly land, glacier and snow, while multi-functional type not only providing ecological goods and function attributes but also productive goods and function attributes, such as arable land, forestry land, and grassland. Furthermore, a six-level grid encoding mode was proposed for modern management of ecological land and data update under cadastral encoding. The six-level irregular grid encoding from macro to micro scale included eco-zone, eco-region, eco-district, cadastral area, land ecosystem, land ownership type, ecological land-use type, and parcel. Besides, the methodologies on ecosystem management were discussed for integrated management of natural resources in China.

Mapping the rehabilitation interventions of a community stroke team to the extended International Classification of Functioning, Disability and Health Core Set for Stroke.

PubMed

Evans, Melissa; Hocking, Clare; Kersten, Paula

2017-12-01

This study aim was to evaluate whether the Extended International Classification of Functioning, Disability and Health Core Set for Stroke captured the interventions of a community stroke rehabilitation team situated in a large city in New Zealand. It was proposed that the results would identify the contribution of each discipline, and the gaps and differences in service provision to Māori and non-Māori. Applying the Extended International Classification of Functioning, Disability and Health Core Set for Stroke in this way would also inform whether this core set should be adopted in New Zealand. Interventions were retrospectively extracted from 18 medical records and linked to the International Classification of Functioning, Disability and Health and the Extended International Classification of Functioning, Disability and Health Core Set for Stroke. The frequencies of linked interventions and the health discipline providing the intervention were calculated. Analysis revealed that 98.8% of interventions provided by the rehabilitation team could be linked to the Extended International Classification of Functioning, Disability and Health Core Set for Stroke, with more interventions for body function and structure than for activities and participation; no interventions for emotional concerns; and limited interventions for community, social and civic life. Results support previous recommendations for additions to the EICSS. The results support the use of the Extended International Classification of Functioning, Disability and Health Core Set for Stroke in New Zealand and demonstrates its use as a quality assurance tool that can evaluate the scope and practice of a rehabilitation service. Implications for Rehabilitation The Extended International Classification of Functioning Disability and Health Core Set for Stroke appears to represent the stroke interventions of a community stroke rehabilitation team in New Zealand. As a result, researchers and clinicians may have increased confidence to use this core set in research and clinical practice. The Extended International Classification of Functioning Disability and Health Core Set for Stroke can be used as a quality assurance tool to establish whether a community stroke rehabilitation team is meeting the functional needs of its stroke population.

Cerebral palsy in Victoria: motor types, topography and gross motor function.

PubMed

Howard, Jason; Soo, Brendan; Graham, H Kerr; Boyd, Roslyn N; Reid, Sue; Lanigan, Anna; Wolfe, Rory; Reddihough, Dinah S

2005-01-01

To study the relationships between motor type, topographical distribution and gross motor function in a large, population-based cohort of children with cerebral palsy (CP), from the State of Victoria, and compare this cohort to similar cohorts from other countries. An inception cohort was generated from the Victorian Cerebral Palsy Register (VCPR) for the birth years 1990-1992. Demographic information, motor types and topographical distribution were obtained from the register and supplemented by grading gross motor function according to the Gross Motor Function Classification System (GMFCS). Complete data were obtained on 323 (86%) of 374 children in the cohort. Gross motor function varied from GMFCS level I (35%) to GMFCS level V (18%) and was similar in distribution to a contemporaneous Swedish cohort. There was a fairly even distribution across the topographical distributions of hemiplegia (35%), diplegia (28%) and quadriplegia (37%) with a large majority of young people having the spastic motor type (86%). The VCPR is ideal for population-based studies of gross motor function in children with CP. Gross motor function is similar in populations of children with CP in developed countries but the comparison of motor types and topographical distribution is difficult because of lack of consensus with classification systems. Use of the GMFCS provides a valid and reproducible method for clinicians to describe gross motor function in children with CP using a universal language.

Vulnerability of Oregon hydrologic landscapes and streamflow to climate change

EPA Science Inventory

Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors. Such assessments could be particularly useful in determining hydrologic vulnerability from climate change. ...

The Gross Motor Function Classification System Family Report Questionnaire: reliability between special-education teachers and caregivers.

PubMed

Ramrit, Sirinun; Yonglitthipagon, Ponlapat; Janyacharoen, Taweesak; Emasithi, Alongkot; Siritaratiwat, Wantana

2017-05-01

The aim of this study was to investigate the reliability of the Thai Gross Motor Function Classification System Family Report Questionnaire (GMFCS-FR) and the possibility of special-education teachers and caregivers in the community using this system in children with cerebral palsy (CP). The reliability was examined by two teachers and two caregivers who classified 21 children with CP aged 2 to 12 years. A GMFCS-FR workshop was organized for raters. The teachers and caregivers classified the mobility of 362 children. The rater reliability was analysed using the weighted kappa coefficient. The possibility of using the GMFCS-FR is reported. The reliability of using the GMFCS-FR in the community was analysed by the intraclass correlation coefficient. The intrarater reliability ranged from 0.91 to 1.00. The interrater reliability between teachers was 0.85 (95% confidence interval [CI] 0.69-0.97) and between caregivers was 0.84 (95% CI 0.70-0.97). Ninety-seven percent of raters used the Thai GMFCS-FR correctly. The overall intraclass correlation coefficient between raters was 0.90 (95% CI 0.88-0.92). The Thai GMFCS-FR is a reliable system for classifying the motor function of young children with CP by teachers and caregivers in the community. © 2016 Mac Keith Press.

How well do the rosgen classification and associated "natural channel design" methods integrate and quantify fluvial processes and channel response?

USGS Publications Warehouse

Simon, A.; Doyle, M.; Kondolf, M.; Shields, F.D.; Rhoads, B.; Grant, G.; Fitzpatrick, F.; Juracek, K.; McPhillips, M.; MacBroom, J.

2005-01-01

Over the past 10 years the Rosgen classification system and its associated methods of "natural channel design" have become synonymous (to many without prior knowledge of the field) with the term "stream restoration" and the science of fluvial geomorphology. Since the mid 1990s, this classification approach has become widely, and perhaps dominantly adopted by governmental agencies, particularly those funding restoration projects. For example, in a request for proposals for the restoration of Trout Creek in Montana, the Natural Resources Conservation Service required "experience in the use and application of a stream classification system and its implementation." Similarly, classification systems have been used in evaluation guides for riparian areas and U.S. Forest Service management plans. Most notably, many highly trained geomorphologists and hydraulic engineers are often held suspect, or even thought incorrect, if their approach does not include reference to or application of a classification system. This, combined with the para-professional training provided by some involved in "natural channel design" empower individuals and groups with limited backgrounds in stream and watershed sciences to engineer wholesale re-patterning of stream reaches using 50-year old technology that was never intended for engineering design. At Level I, the Rosgen classification system consists of eight or nine major stream types, based on hydraulic-geometry relations and four other measures of channel shape to distinguish the dimensions of alluvial stream channels as a function of the bankfull stage. Six classes of the particle size of the boundary sediments are used to further sub-divide each of the major stream types, resulting in 48 or 54 stream types. Aside from the difficulty in identifying bankfull stage, particularly in incising channels, and the issue of sampling from two distinct populations (beds and banks) to classify the boundary sediments, the classification provides a consistent and reproducible means for practitioners to describe channel morphology although difficulties have been encountered in lower-gradient stream systems. Use of the scheme to communicate between users or as a conceptual model, however, has not justified its use for engineering design or for predicting river behavior; its use for designing mitigation projects, therefore, seems beyond its technical scope. Copyright ASCE 2005.

Reliability and cross-cultural validation of the Turkish version of Manual Ability Classification System (MACS) for children with cerebral palsy.

PubMed

Akpinar, Pinar; Tezel, Canan G; Eliasson, Ann-Christin; Icagasioglu, Afitap

2010-01-01

To determine the reliability and cross-cultural validation of the Turkish translation of the Manual Ability Classification System (MACS) for children with cerebral palsy (CP) and to investigate the relation to gross motor function and other comorbidities. After the forward and backward translation procedures, inter-rater and test-retest reliability was assessed between parents, physiotherapists and physicians using the intra-class correlation coefficient (ICC). Children (N = 118, 4 to 18 years, mean age 9 years 4 months; 68 boys, 50 girls) with various types of CP were classified. Additional data on the Gross Motor Function Classification System (GMFCS), intellectual delay, visual acuity, and epilepsy were collected. The inter-rater reliability was high; the ICC ranged from 0.89 to 0.96 among different professionals and parents. Between two persons of the same profession it ranged from 0.97 to 0.98. For the test-retest reliability it ranged from 0.91 to 0.98. Total agreement between the GMFCS and the MACS occurred in only 45% of the children. The level of the MACS was found to correlate with the accompanying comorbidities, namely intellectual delay and epilepsy. The Turkish version of the MACS is found to be valid and reliable, and is suggested to be appropriate for the assessment of manual ability within the Turkish population.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

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

PubMed

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

2018-01-01

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

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.

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.

Towards automated human gait disease classification using phase space representation of intrinsic mode functions

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Patra, Sayantani; Pratiher, Souvik

2017-06-01

A novel analytical methodology for segregating healthy and neurological disorders from gait patterns is proposed by employing a set of oscillating components called intrinsic mode functions (IMF's). These IMF's are generated by the Empirical Mode Decomposition of the gait time series and the Hilbert transformed analytic signal representation forms the complex plane trace of the elliptical shaped analytic IMFs. The area measure and the relative change in the centroid position of the polygon formed by the Convex Hull of these analytic IMF's are taken as the discriminative features. Classification accuracy of 79.31% with Ensemble learning based Adaboost classifier validates the adequacy of the proposed methodology for a computer aided diagnostic (CAD) system for gait pattern identification. Also, the efficacy of several potential biomarkers like Bandwidth of Amplitude Modulation and Frequency Modulation IMF's and it's Mean Frequency from the Fourier-Bessel expansion from each of these analytic IMF's has been discussed for its potency in diagnosis of gait pattern identification and classification.

Less-Complex Method of Classifying MPSK

NASA Technical Reports Server (NTRS)

Hamkins, Jon

2006-01-01

An alternative to an optimal method of automated classification of signals modulated with M-ary phase-shift-keying (M-ary PSK or MPSK) has been derived. The alternative method is approximate, but it offers nearly optimal performance and entails much less complexity, which translates to much less computation time. Modulation classification is becoming increasingly important in radio-communication systems that utilize multiple data modulation schemes and include software-defined or software-controlled receivers. Such a receiver may "know" little a priori about an incoming signal but may be required to correctly classify its data rate, modulation type, and forward error-correction code before properly configuring itself to acquire and track the symbol timing, carrier frequency, and phase, and ultimately produce decoded bits. Modulation classification has long been an important component of military interception of initially unknown radio signals transmitted by adversaries. Modulation classification may also be useful for enabling cellular telephones to automatically recognize different signal types and configure themselves accordingly. The concept of modulation classification as outlined in the preceding paragraph is quite general. However, at the present early stage of development, and for the purpose of describing the present alternative method, the term "modulation classification" or simply "classification" signifies, more specifically, a distinction between M-ary and M'-ary PSK, where M and M' represent two different integer multiples of 2. Both the prior optimal method and the present alternative method require the acquisition of magnitude and phase values of a number (N) of consecutive baseband samples of the incoming signal + noise. The prior optimal method is based on a maximum- likelihood (ML) classification rule that requires a calculation of likelihood functions for the M and M' hypotheses: Each likelihood function is an integral, over a full cycle of carrier phase, of a complicated sum of functions of the baseband sample values, the carrier phase, the carrier-signal and noise magnitudes, and M or M'. Then the likelihood ratio, defined as the ratio between the likelihood functions, is computed, leading to the choice of whichever hypothesis - M or M'- is more likely. In the alternative method, the integral in each likelihood function is approximated by a sum over values of the integrand sampled at a number, 1, of equally spaced values of carrier phase. Used in this way, 1 is a parameter that can be adjusted to trade computational complexity against the probability of misclassification. In the limit as 1 approaches infinity, one obtains the integral form of the likelihood function and thus recovers the ML classification. The present approximate method has been tested in comparison with the ML method by means of computational simulations. The results of the simulations have shown that the performance (as quantified by probability of misclassification) of the approximate method is nearly indistinguishable from that of the ML method (see figure).

Review Article: Mapping of children's health and development data on population level using the classification system ICF-CY.

PubMed

Ståhl, Ylva; Granlund, Mats; Gäre-Andersson, Boel; Enskär, Karin

2011-02-01

The aim of this study was to investigate if essential health and development data of all children in Sweden in the Child Health Service (CHS) and School Health Service (SHS) can be linked to the classification system International Classification of Functioning, Disability and Health--Children and Youth (ICF-CY). Lists of essential health terms, compiled by professionals from CHS and SHS, expected to be used in the national standardised records form the basis for the analysis in this study. The essential health terms have been linked to the codes of ICF-CY by using linking rules and a verification procedure. After exclusion of terms not directly describing children's health, a majority of the health terms could be linked into the ICF-CY with a high proportion of terms in body functions and a lower proportion in activity/participation and environment respectively. Some health terms had broad description and were linked to several ICF-CY codes. The precision of the health terms was at a medium level of detail. ICF-CY can be useful as a tool for documenting child health. It provides not only a code useful for statistical purposes but also a language useful for the CHS and SHS in their work on individual as well as population levels. It was noted that the health terms used by services mainly focused on health related to body function. This indicates that more focus is needed on health data related to child's functioning in everyday life situations.

Keratoconus: The ABCD Grading System.

PubMed

Belin, M W; Duncan, J K

2016-06-01

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

Integrability of the one dimensional Schrödinger equation

NASA Astrophysics Data System (ADS)

Combot, Thierry

2018-02-01

We present a definition of integrability for the one-dimensional Schrödinger equation, which encompasses all known integrable systems, i.e., systems for which the spectrum can be explicitly computed. For this, we introduce the class of rigid functions, built as Liouvillian functions, but containing all solutions of rigid differential operators in the sense of Katz, and a notion of natural of boundary conditions. We then make a complete classification of rational integrable potentials. Many new integrable cases are found, some of them physically interesting.

Changing Perspectives for Practice in Stuttering: Echoes from a Celtic Past, when Wordlessness Was Entitled to Time

ERIC Educational Resources Information Center

Leahy, Margaret M.

2005-01-01

Changing perspectives for practice in stuttering therapy are informed by the changes in knowledge, social values, and belief systems of a society. The International Classification of Functioning, Disability and Health (ICF; World Health Organization, 2001) has a sociological emphasis with a focus on the ability and functioning of the person, and…

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

The Eating and Drinking Ability Classification System: concurrent validity and reliability in children with cerebral palsy.

PubMed

Tschirren, Lea; Bauer, Susanne; Hanser, Chiara; Marsico, Petra; Sellers, Diane; van Hedel, Hubertus J A

2018-06-01

As there is little evidence for concurrent validity of the Eating and Drinking Ability Classification System (EDACS), this study aimed to determine its concurrent validity and reliability in children and adolescents with cerebral palsy (CP). After an extensive translation procedure, we applied the German language version to 52 participants with CP (30 males, 22 females, mean age 9y 7mo [SD 4y 2mo]). We correlated (Kendall's tau or K τ ) the EDACS levels with the Bogenhausener Dysphagiescore (BODS), and the EDACS level of assistance with the Manual Ability Classification System (MACS) and the item 'eating' of the Functional Independence Measure for Children (WeeFIM). We further quantified the interrater reliability between speech and language therapists (SaLTs) and between SaLTs and parents with Kappa (κ). The EDACS levels correlated highly with the BODS (K τ =0.79), and the EDACS level of assistance correlated highly with the MACS (K τ =0.73) and WeeFIM eating item (K τ =-0.80). Interrater reliability proved almost perfect between SaLTs (EDACS: κ=0.94; EDACS level of assistance: κ=0.89) and SaLTs and parents (EDACS: κ=0.82; EDACS level of assistance: κ=0.89). The EDACS levels and level of assistance seem valid and showed almost perfect interrater reliability when classifying eating and drinking problems in children and adolescents with CP. The Eating and Drinking Ability Classification System (EDACS) correlates well with a dysphagia score. The EDACS level of assistance proves valid. The German version of EDACS is highly reliable. EDACS correlates moderately to highly with other classification systems. © 2018 Mac Keith Press.

Rapid assessment of urban wetlands: Do hydrogeomorpic classification and reference criteria work?

EPA Science Inventory

The Hydrogeomorphic (HGM) functional assessment method is predicated on the ability of a wetland classification method based on hydrology (HGM classification) and a visual assessment of disturbance and alteration to provide reference standards against which functions in individua...

The family needs of parents of preschool children with cerebral palsy: the impact of child's gross motor and communications functions.

PubMed

Bertule, Dace; Vetra, Anita

2014-01-01

An understanding of the needs of families of preschool children with cerebral palsy (CP) is of essential importance if efficient and cost-effective services are to be provided to them. The aims of this study were to identify the most frequently expressed needs of families with preschool children with CP; differences in the amount and types of family needs based on the child's gross motor function and communication function level; and the impact of the child's gross motor function and communication function level on the type and amount of family needs. A total of 227 parents of preschool children with CP completed a modified version of the Family Needs Survey and a demographic questionnaire. Children's gross motor function level and communication function level was classified using the Gross Motor Function Classification System (GMFCS) and the Communication Function Classification System (CFCS), respectively. The total number of family needs differed based on GMFCS and CFCS levels. Children's GMFCS and CFCS level were not significant predictors of overall family needs (adjusted R(2)=0.163). In this model the GMFCS level of children did not account for the total number of family needs, while the CFCS level did. Child's limitations in terms of communication and gross motor functions must be taken into consideration when planning services for families with preschool children with CP. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

NASA Technical Reports Server (NTRS)

Lure, Y. M. Fleming; Grody, Norman C.; Chiou, Y. S. Peter; Yeh, H. Y. Michael

1993-01-01

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

In search of a consumer-focused food classification system. An experimental heuristic approach to differentiate degrees of quality.

PubMed

Torres-Ruiz, Francisco J; Marano-Marcolini, Carla; Lopez-Zafra, Esther

2018-06-01

The present paper focuses on the problems that arise in food classification systems (FCSs), especially when the food product type has different levels or grades of quality. Despite the principal function of these systems being to assist the consumer (to inform, clarify and facilitate choice and purchase), they frequently have the opposite effect. Thus, the main aim of the present research involves providing orientations for the design of effective food classification systems. To address this objective, considering the context of food product consumption (related to heuristic processing), we conducted an experimental study with 720 participants. We analysed the usefulness of heuristic elements by a factorial 2 (category length: short and long) × 3 (visual signs: colours, numbers and images) design in relation to recall and recognition activities. The results showed that the elements used to make the classification more effective for consumers vary depending on whether the user seeks to prioritize the recall or the recognition of product categories. Thus, long categories with images significantly improve recognition, and short categories with colours improve recall. A series of recommendations are provided that can help to enhance FCSs and to make them more intuitive and easier to understand for consumers. Implications with regard to theory and practice are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Systematic technology transfer from biology to engineering.

PubMed

Vincent, Julian F V; Mann, Darrell L

2002-02-15

Solutions to problems move only very slowly between different disciplines. Transfer can be greatly speeded up with suitable abstraction and classification of problems. Russian researchers working on the TRIZ (Teoriya Resheniya Izobretatelskikh Zadatch) method for inventive problem solving have identified systematic means of transferring knowledge between different scientific and engineering disciplines. With over 1500 person years of effort behind it, TRIZ represents the biggest study of human creativity ever conducted, whose aim has been to establish a system into which all known solutions can be placed, classified in terms of function. At present, the functional classification structure covers nearly 3 000 000 of the world's successful patents and large proportions of the known physical, chemical and mathematical knowledge-base. Additional tools are the identification of factors which prevent the attainment of new technology, leading directly to a system of inventive principles which will resolve the impasse, a series of evolutionary trends of development, and to a system of methods for effecting change in a system (Su-fields). As yet, the database contains little biological knowledge despite early recognition by the instigator of TRIZ (Genrich Altshuller) that one day it should. This is illustrated by natural systems evolved for thermal stability and the maintenance of cleanliness.

Aging, Counterfeiting Configuration Control (AC3)

DTIC Science & Technology

2010-01-31

SARA continuously polls contributing data sources on a data specific refresh cycle. SARA supports a continuous risk topology assessment by the program...function was demonstrated at the bread -board level based on comparison of North American Industrialization Classification System (NAICS) codes. Other

Effects of a Static Bicycling Programme on the Functional Ability of Young People with Cerebral Palsy Who Are Non-Ambulant

ERIC Educational Resources Information Center

Williams, Heather; Pountney, Teresa

2007-01-01

This study investigated the effects of exercise on the motor function of 11 young people (10 females, one male; age range 11-15y; mean age 12y 7mo [SD 1y 4mo]) with cerebral palsy (CP) who were non-ambulant (Gross Motor Function Classification System Levels IV or V), using an adapted static bicycle. Three participants had dyskinetic quadriplegia,…

Visualization of usability and functionality of a professional website through web-mining.

PubMed

Jones, Josette F; Mahoui, Malika; Gopa, Venkata Devi Pragna

2007-10-11

Functional interface design requires understanding of the information system structure and the user. Web logs record user interactions with the interface, and thus provide some insight into user search behavior and efficiency of the search process. The present study uses a data-mining approach with techniques such as association rules, clustering and classification, to visualize the usability and functionality of a digital library through in depth analyses of web logs.

Refined 4-group classification of left ventricular hypertrophy based on ventricular concentricity and volume dilatation outlines distinct noninvasive hemodynamic profiles in a large contemporary echocardiographic population.

PubMed

Barbieri, Andrea; Rossi, Andrea; Gaibazzi, Nicola; Erlicher, Andrea; Mureddu, Gian Francesco; Frattini, Silvia; Faden, Giacomo; Manicardi, Marcella; Beraldi, Monica; Agostini, Francesco; Lazzarini, Valentina; Moreo, Antonella; Temporelli, Pier Luigi; Faggiano, Pompilio

2018-05-23

Left ventricular hypertrophy (LVH) may reflect a wide variety of physiologic and pathologic conditions. Thus, it can be misleading to consider all LVH to be homogenous or similar. Refined 4-group classification of LVH based on ventricular concentricity and dilatation may be identified. To determine whether the 4-group classification of LVH identified distinct phenotypes, we compared their association with various noninvasive markers of cardiac stress. Cohort of unselected adult outpatients referred to a seven tertiary care echocardiographic laboratory for any indication in a 2-week period. We evaluated the LV geometric patterns using validated echocardiographic indexation methods and partition values. Standard echocardiography was performed in 1137 consecutive subjects, and LVH was found in 42%. The newly proposed 4-group classification of LVH was applicable in 88% of patients. The most common pattern resulted in concentric LVH (19%). The worst functional and hemodynamic profile was associated with eccentric LVH and those with mixed LVH had a higher prevalence of reduced EF than those with concentric LVH (P < .001 for all). The new 4-group classification of LVH system showed distinct differences in cardiac function and noninvasive hemodynamics allowing clinicians to distinguish different LV hemodynamic stress adaptations in patients with LVH. © 2018 Wiley Periodicals, Inc.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

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.

Classification of Magneto-Optic Images using Neural Networks

NASA Technical Reports Server (NTRS)

Nath, Shridhar; Wincheski, Buzz; Fulton, Jim; Namkung, Min

1994-01-01

A real time imaging system with a neural network classifier has been incorporated on a Macintosh computer in conjunction with an MOI system. This system images rivets on aircraft aluminium structures using eddy currents and magnetic imaging. Moment invariant functions from the image of a rivet is used to train a multilayer perceptron neural network to classify the rivets as good or bad (rivets with cracks).

Repertoire and classification of non-song calls in Southeast Alaskan humpback whales (Megaptera novaeangliae).

PubMed

Fournet, Michelle E; Szabo, Andy; Mellinger, David K

2015-01-01

On low-latitude breeding grounds, humpback whales produce complex and highly stereotyped songs as well as a range of non-song sounds associated with breeding behaviors. While on their Southeast Alaskan foraging grounds, humpback whales produce a range of previously unclassified non-song vocalizations. This study investigates the vocal repertoire of Southeast Alaskan humpback whales from a sample of 299 non-song vocalizations collected over a 3-month period on foraging grounds in Frederick Sound, Southeast Alaska. Three classification systems were used, including aural spectrogram analysis, statistical cluster analysis, and discriminant function analysis, to describe and classify vocalizations. A hierarchical acoustic structure was identified; vocalizations were classified into 16 individual call types nested within four vocal classes. The combined classification method shows promise for identifying variability in call stereotypy between vocal groupings and is recommended for future classification of broad vocal repertoires.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

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

Medical and surgical management of esophageal and gastric motor dysfunction.

PubMed

Awad, R A

2012-09-01

he occurrence of esophageal and gastric motor dysfunctions happens, when the software of the esophagus and the stomach is injured. This is really a program previously established in the enteric nervous system as a constituent of the newly called neurogastroenterology. The enteric nervous system is composed of small aggregations of nerve cells, enteric ganglia, the neural connections between these ganglia, and nerve fibers that supply effectors tissues, including the muscle of the gut wall. The wide range of enteric neuropathies that includes esophageal achalasia and gastroparesis highlights the importance of the enteric nervous system. A classification of functional gastrointestinal disorders based on symptoms has received attention. However, a classification based solely in symptoms and consensus may lack an integral approach of disease. As an alternative to the Rome classification, an international working team in Bangkok presented a classification of motility disorders as a physiology-based diagnosis. Besides, the Chicago Classification of esophageal motility was developed to facilitate the interpretation of clinical high-resolution esophageal pressure topography studies. This review covers exclusively the medical and surgical management of the esophageal and gastric motor dysfunction using evidence from well-designed studies. Motor control of the esophagus and the stomach, motor esophageal and gastric alterations, treatment failure, side effects of PPIs, overlap of gastrointestinal symptoms, predictors of treatment, burden of GERD medical management, data related to conservative treatment vs. antireflux surgery, and postsurgical esophagus and gastric motor dysfunction are also taken into account.

Cost-effectiveness of a classification-based system for sub-acute and chronic low back pain.

PubMed

Apeldoorn, Adri T; Bosmans, Judith E; Ostelo, Raymond W; de Vet, Henrica C W; van Tulder, Maurits W

2012-07-01

Identifying relevant subgroups in patients with low back pain (LBP) is considered important to guide physical therapy practice and to improve outcomes. The aim of the present study was to assess the cost-effectiveness of a modified version of Delitto's classification-based treatment approach compared with usual physical therapy care in patients with sub-acute and chronic LBP with 1 year follow-up. All patients were classified using the modified version of Delitto's classification-based system and then randomly assigned to receive either classification-based treatment or usual physical therapy care. The main clinical outcomes measured were; global perceived effect, intensity of pain, functional disability and quality of life. Costs were measured from a societal perspective. Multiple imputations were used for missing data. Uncertainty surrounding cost differences and incremental cost-effectiveness ratios was estimated using bootstrapping. Cost-effectiveness planes and cost-effectiveness acceptability curves were estimated. In total, 156 patients were included. The outcome analyses showed a significantly better outcome on global perceived effect favoring the classification-based approach, and no differences between the groups on pain, disability and quality-adjusted life-years. Mean total societal costs for the classification-based group were 2,287, and for the usual physical therapy care group 2,020. The difference was 266 (95% CI -720 to 1,612) and not statistically significant. Cost-effectiveness analyses showed that the classification-based approach was not cost-effective in comparison with usual physical therapy care for any clinical outcome measure. The classification-based treatment approach as used in this study was not cost-effective in comparison with usual physical therapy care in a population of patients with sub-acute and chronic LBP.

The Australian National Sub-acute and Non-acute Patient Casemix Classification (AN-SNAP): its application and value in a stroke rehabilitation programme.

PubMed

Lowthian, P; Disler, P; Ma, S; Eagar, K; Green, J; de Graaff, S

2000-10-01

To investigate whether the Australian National Sub-acute and Non-acute Patient Casemix Classification (SNAP) and Functional Independence Measure and Functional Related Group (Version 2) (FIM-FRG2) casemix systems can be used to predict functional outcome, and reduce the variance of length of stay (LOS) of patients undergoing rehabilitation after strokes. The study comprised a retrospective analysis of the records of patients admitted to the Cedar Court Healthsouth Rehabilitation Hospital for rehabilitation after stroke. The sample included 547 patients (83.3% of those admitted with stroke during this period). Patient data were stratified for analysis into the five SNAP or nine FIM-FRG2 groups, on the basis of the admission FIM scores and age. The AN-SNAP classification accounted for a 30.7% reduction of the variance of LOS, and 44.2% of motor FIM, and the FIM-FRG2 accounts for 33.5% and 56.4% reduction respectively. Comparison of the Cedar Court with the national AN-SNAP data showed differences in the LOS and functional outcomes of older, severely disabled patients. Intensive rehabilitation in selected patients of this type appears to have positive effects, albeit with a slightly longer period of inpatient rehabilitation. Casemix classifications can be powerful management tools. Although FIM-FRG2 accounts for more reduction in variance than SNAP, division into nine groups meant that some contained few subjects. This paper supports the introduction of AN-SNAP as the standard casemix tool for rehabilitation in Australia, which will hopefully lead to rational, adequate funding of the rehabilitation phase of care.

Motor function domains in alternating hemiplegia of childhood.

PubMed

Masoud, Melanie; Gordon, Kelly; Hall, Amanda; Jasien, Joan; Lardinois, Kara; Uchitel, Julie; Mclean, Melissa; Prange, Lyndsey; Wuchich, Jeffrey; Mikati, Mohamad A

2017-08-01

To characterize motor function profiles in alternating hemiplegia of childhood, and to investigate interrelationships between these domains and with age. We studied a cohort of 23 patients (9 males, 14 females; mean age 9y 4mo, range 4mo-43y) who underwent standardized tests to assess gross motor, upper extremity motor control, motor speech, and dysphagia functions. Gross Motor Function Classification System (GMFCS), Gross Motor Function Measure-88 (GMFM-88), Manual Ability Classification System (MACS), and Revised Melbourne Assessment (MA2) scales manifested predominantly mild impairments; motor speech, moderate to severe; Modified Dysphagia Outcome and Severity Scale (M-DOSS), mild-to moderate deficits. GMFCS correlated with GMFM-88 scores (Pearson's correlation, p=0.002), MACS (p=0.038), and MA2 fluency (p=0.005) and accuracy (p=0.038) scores. GMFCS did not correlate with motor speech (p=0.399), MA2 dexterity (p=0.247), range of motion (p=0.063), or M-DOSS (p=0.856). Motor speech was more severely impaired than the GMFCS (p<0.013). There was no correlation between any of the assessment tools and age (p=0.210-0.798). Our data establish a detailed profile of motor function in alternating hemiplegia of childhood, argue against the presence of worse motor function in older patients, identify tools helpful in evaluating this population, and identify oropharyngeal function as the more severely affected domain, suggesting that brain areas controlling this function are more affected than others. © 2017 Mac Keith Press.

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

European validation of The Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis from the perspective of patients with osteoarthritis of the knee or hip.

PubMed

Weigl, Martin; Wild, Heike

2017-09-15

To validate the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis from the patient perspective in Europe. This multicenter cross-sectional study involved 375 patients with knee or hip osteoarthritis. Trained health professionals completed the Comprehensive Core Set, and patients completed the Short-Form 36 questionnaire. Content validity was evaluated by calculating prevalences of impairments in body function and structures, limitations in activities and participation and environmental factors, which were either barriers or facilitators. Convergent construct validity was evaluated by correlating the International Classification of Functioning, Disability and Health categories with the Short-Form 36 Physical Component Score and the SF-36 Mental Component Score in a subgroup of 259 patients. The prevalences of all body function, body structure and activities and participation categories were >40%, >32% and >20%, respectively, and all environmental factors were relevant for >16% of patients. Few categories showed relevant differences between knee and hip osteoarthritis. All body function categories and all but two activities and participation categories showed significant correlations with the Physical Component Score. Body functions from the ICF chapter Mental Functions showed higher correlations with the Mental Component Score than with the Physical Component Score. This study supports the validity of the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis. Implications for Rehabilitation Comprehensive International Classification of Functioning, Disability and Health Core Sets were developed as practical tools for application in multidisciplinary assessments. The validity of the Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis in this study supports its application in European patients with osteoarthritis. The differences in results between this Europe validation study and a previous Singaporean validation study underscore the need to validate the International Classification of Functioning, Disability and Health Core Sets in different regions of the world.

Impairments, activity limitations, and participation restrictions of the international classification of functioning, disability, and health model in children with ambulatory cerebral palsy

PubMed Central

Mutlu, Akmer; Büğüsan, Sema; Kara, Özgün K.

2017-01-01

Objectives: To examine the impairments, activity limitations, and participation restrictions in children with spastic unilateral and bilateral cerebral palsy (CP). We investigated the relationship between these factors according to the international classification of functioning, disability, and health (ICF) model. Methods: This prospective cross sectional study included 60 children aged between 4-18 years with spastic CP (30 unilateral, 30 bilateral involvement) classified as Levels I and II on the gross motor function classification system. Children had been referred to the Pediatric Rehabilitation Unit in the Department of Physiotherapy and Rehabilitation, Hacettepe University, Ankara, Turkey between March 2014 and March 2015. The Physician Rating scale was used to assess body functions and structures. The Gillette Functional Assessment Questionnaire 22-item skill set, Pediatric Functional Independence Measure, and Pediatric Outcomes Data Collection Instrument were used to assess activity and participation levels. Results: There was a significant positive correlation between impairments and activity limitations (r=0.558; p=0.000), as well as between activity limitations and participation restrictions (r=0.354, p=0.005). Conclusion: These results show that activity limitations in children with unilateral and bilateral ambulatory CP may be related to their impairments and participation restrictions, although the sample size of our study is not large enough for generalizations. Overall, our study highlights the need for up-to-date, practical evaluation methods according to the ICF model. PMID:28133691

Creation of a Digital Aquifer Permeability Map for the Pacific Northwest

EPA Science Inventory

Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors such as climate change. One of the greatest challenges to this effort is obtaining consistent aquifer permea...

Vulnerability of Oregon Hydrologic Landscapes and Streamflow to Climate Change - 5/20/2014

EPA Science Inventory

Hydrologic classification systems can provide a basis for broadscale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors. Such assessments could be particularly useful in determining hydrologic vulnerability from climate change. A...

Promising personalized therapeutic options for diffuse large B-cell Lymphoma Subtypes with oncogene addictions.

PubMed

Steinhardt, James J; Gartenhaus, Ronald B

2012-09-01

Currently, two major classification systems segregate diffuse large B-cell lymphoma (DLBCL) into subtypes based on gene expression profiles and provide great insights about the oncogenic mechanisms that may be crucial for lymphomagenesis as well as prognostic information regarding response to current therapies. However, these current classification systems primarily look at expression and not dependency and are thus limited to inductive or probabilistic reasoning when evaluating alternative therapeutic options. The development of a deductive classification system that identifies subtypes in which all patients with a given phenotype require the same oncogenic drivers, and would therefore have a similar response to a rational therapy targeting the essential drivers, would significantly advance the treatment of DLBCL. This review highlights the putative drivers identified as well as the work done to identify potentially dependent populations. These studies integrated genomic analysis and functional screens to provide a rationale for targeted therapies within defined populations. Personalizing treatments by identifying patients with oncogenic dependencies via genotyping and specifically targeting the responsible drivers may constitute a novel approach for the treatment of DLBCL. ©2012 AACR.

Realizing parameterless automatic classification of remote sensing imagery using ontology engineering and cyberinfrastructure techniques

NASA Astrophysics Data System (ADS)

Sun, Ziheng; Fang, Hui; Di, Liping; Yue, Peng

2016-09-01

It was an untouchable dream for remote sensing experts to realize total automatic image classification without inputting any parameter values. Experts usually spend hours and hours on tuning the input parameters of classification algorithms in order to obtain the best results. With the rapid development of knowledge engineering and cyberinfrastructure, a lot of data processing and knowledge reasoning capabilities become online accessible, shareable and interoperable. Based on these recent improvements, this paper presents an idea of parameterless automatic classification which only requires an image and automatically outputs a labeled vector. No parameters and operations are needed from endpoint consumers. An approach is proposed to realize the idea. It adopts an ontology database to store the experiences of tuning values for classifiers. A sample database is used to record training samples of image segments. Geoprocessing Web services are used as functionality blocks to finish basic classification steps. Workflow technology is involved to turn the overall image classification into a total automatic process. A Web-based prototypical system named PACS (Parameterless Automatic Classification System) is implemented. A number of images are fed into the system for evaluation purposes. The results show that the approach could automatically classify remote sensing images and have a fairly good average accuracy. It is indicated that the classified results will be more accurate if the two databases have higher quality. Once the experiences and samples in the databases are accumulated as many as an expert has, the approach should be able to get the results with similar quality to that a human expert can get. Since the approach is total automatic and parameterless, it can not only relieve remote sensing workers from the heavy and time-consuming parameter tuning work, but also significantly shorten the waiting time for consumers and facilitate them to engage in image classification activities. Currently, the approach is used only on high resolution optical three-band remote sensing imagery. The feasibility using the approach on other kinds of remote sensing images or involving additional bands in classification will be studied in future.

Multi-dimensionality and variability in folk classification of stingless bees (Apidae: Meliponini).

PubMed

Zamudio, Fernando; Hilgert, Norma I

2015-05-23

Not long ago Eugene Hunn suggested using a combination of cognitive, linguistic, ecological and evolutionary theories in order to account for the dynamic character of ethnoecology in the study of folk classification systems. In this way he intended to question certain homogeneity in folk classifications models and deepen in the analysis and interpretation of variability in folk classifications. This paper studies how a rural culturally mixed population of the Atlantic Forest of Misiones (Argentina) classified honey-producing stingless bees according to the linguistic, cognitive and ecological dimensions of folk classification. We also analyze the socio-ecological meaning of binomialization in naming and the meaning of general local variability in the appointment of stingless bees. We used three different approaches: the classical approach developed by Brent Berlin which relies heavily on linguistic criteria, the approach developed by Eleonor Rosch which relies on psychological (cognitive) principles of categorization and finally we have captured the ecological dimension of folk classification in local narratives. For the second approximation, we developed ways of measuring the degree of prototypicality based on a total of 107 comparisons of the type "X is similar to Y" identified in personal narratives. Various logical and grouping strategies coexist and were identified as: graded of lateral linkage, hierarchical and functional. Similarity judgments among folk taxa resulted in an implicit logic of classification graded according to taxa's prototypicality. While there is a high agreement on naming stingless bees with monomial names, a considerable number of underrepresented binomial names and lack of names were observed. Two possible explanations about reported local naming variability are presented. We support the multidimensionality of folk classification systems. This confirms the specificity of local classification systems but also reflects the use of grouping strategies and mechanisms commonly observed in other cultural groups, such as the use of similarity judgments between more or less prototypical organisms. Also we support the idea that alternative naming results from a process of fragmentation of knowledge or incomplete transmission of knowledge. These processes lean on the facts that culturally based knowledge, on the one hand, and biologic knowledge of nature on the other, can be acquired through different learning pathways.

A trait-based framework to understand life history of mycorrhizal fungi.

PubMed

Chagnon, Pierre-Luc; Bradley, Robert L; Maherali, Hafiz; Klironomos, John N

2013-09-01

Despite the growing appreciation for the functional diversity of arbuscular mycorrhizal (AM) fungi, our understanding of the causes and consequences of this diversity is still poor. In this opinion article, we review published data on AM fungal functional traits and attempt to identify major axes of life history variation. We propose that a life history classification system based on the grouping of functional traits, such as Grime's C-S-R (competitor, stress tolerator, ruderal) framework, can help to explain life history diversification in AM fungi, successional dynamics, and the spatial structure of AM fungal assemblages. Using a common life history classification framework for both plants and AM fungi could also help in predicting probable species associations in natural communities and increase our fundamental understanding of the interaction between land plants and AM fungi. Copyright © 2013 Elsevier Ltd. 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.

Neural architecture underlying classification of face perception paradigms.

PubMed

Laird, Angela R; Riedel, Michael C; Sutherland, Matthew T; Eickhoff, Simon B; Ray, Kimberly L; Uecker, Angela M; Fox, P Mickle; Turner, Jessica A; Fox, Peter T

2015-10-01

We present a novel strategy for deriving a classification system of functional neuroimaging paradigms that relies on hierarchical clustering of experiments archived in the BrainMap database. The goal of our proof-of-concept application was to examine the underlying neural architecture of the face perception literature from a meta-analytic perspective, as these studies include a wide range of tasks. Task-based results exhibiting similar activation patterns were grouped as similar, while tasks activating different brain networks were classified as functionally distinct. We identified four sub-classes of face tasks: (1) Visuospatial Attention and Visuomotor Coordination to Faces, (2) Perception and Recognition of Faces, (3) Social Processing and Episodic Recall of Faces, and (4) Face Naming and Lexical Retrieval. Interpretation of these sub-classes supports an extension of a well-known model of face perception to include a core system for visual analysis and extended systems for personal information, emotion, and salience processing. Overall, these results demonstrate that a large-scale data mining approach can inform the evolution of theoretical cognitive models by probing the range of behavioral manipulations across experimental tasks. Copyright © 2015 Elsevier Inc. All rights reserved.

The biopsychosocial domains and the functions of the medical interview in primary care: construct validity of the Verona Medical Interview Classification System.

PubMed

Del Piccolo, Lidia; Putnam, Samuel M; Mazzi, Maria Angela; Zimmermann, Christa

2004-04-01

Factor analysis (FA) is a powerful method of testing the construct validity of coding systems of the medical interview. The study uses FA to test the underlying assumptions of the Verona Medical Interview Classification System (VR-MICS). The relationship between factor scores and patient characteristics was also examined. The VR-MICS coding categories consider the three domains of the biopsychosocial model and the main functions of the medical interview-data gathering, relationship building and patient education. FA was performed on the frequencies of the VR-MICS categories based on 238 medical interviews. Seven factors (62.5% of variance explained) distinguished different strategies patients and physicians use to exchange information, build a relationship and negotiate treatment within the domains of the biopsychosocial model. Three factors, Psychological, Social Inquiry and Management of Patient Agenda, were related to patient data: sociodemographic (female gender, age and employment), social (stressful events), clinical (GHQ-12 score), personality (chance external health locus of control) and clinical characteristics (psychiatric history, chronic illness, attributed presence of emotional distress).

Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease.

PubMed

Schouten, Tijn M; Koini, Marisa; de Vos, Frank; Seiler, Stephan; van der Grond, Jeroen; Lechner, Anita; Hafkemeijer, Anne; Möller, Christiane; Schmidt, Reinhold; de Rooij, Mark; Rombouts, Serge A R B

2016-01-01

Magnetic resonance imaging (MRI) is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD), and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N = 77) from the prospective registry on dementia study and controls (N = 173) from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC) of 0.760 (full correlations between functional networks) to 0.909 (grey matter density). When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.

Spectral feature design in high dimensional multispectral data

NASA Technical Reports Server (NTRS)

Chen, Chih-Chien Thomas; Landgrebe, David A.

1988-01-01

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Carotenoid Antenna Binding and Function in Retinal Proteins

DTIC Science & Technology

2012-08-13

REPORT Carotenoid antenna binding and function in retinal proteins 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Xanthorhodopsin, a proton pump from the...eubacterium Salinibacter ruber, is a unique dual chromophore system that contains, in addition to retinal, the carotenoid salinixanthin as a light... carotenoid ring near the retinal ring. Substitution of the small glycine with bulky tryptophan in this site eliminates binding. The second factor is the 4

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.

A Classification of Remote Sensing Image Based on Improved Compound Kernels of Svm

NASA Astrophysics Data System (ADS)

Zhao, Jianing; Gao, Wanlin; Liu, Zili; Mou, Guifen; Lu, Lin; Yu, Lina

The accuracy of RS classification based on SVM which is developed from statistical learning theory is high under small number of train samples, which results in satisfaction of classification on RS using SVM methods. The traditional RS classification method combines visual interpretation with computer classification. The accuracy of the RS classification, however, is improved a lot based on SVM method, because it saves much labor and time which is used to interpret images and collect training samples. Kernel functions play an important part in the SVM algorithm. It uses improved compound kernel function and therefore has a higher accuracy of classification on RS images. Moreover, compound kernel improves the generalization and learning ability of the kernel.

Information Systems Security Management: A Review and a Classification of the ISO Standards

NASA Astrophysics Data System (ADS)

Tsohou, Aggeliki; Kokolakis, Spyros; Lambrinoudakis, Costas; Gritzalis, Stefanos

The need for common understanding and agreement of functional and non-functional requirements is well known and understood by information system designers. This is necessary for both: designing the "correct" system and achieving interoperability with other systems. Security is maybe the best example of this need. If the understanding of the security requirements is not the same for all involved parties and the security mechanisms that will be implemented do not comply with some globally accepted rules and practices, then the system that will be designed will not necessarily achieve the desired security level and it will be very difficult to securely interoperate with other systems. It is therefore clear that the role and contribution of international standards to the design and implementation of security mechanisms is dominant. In this paper we provide a state of the art review on information security management standards published by the International Organization for Standardization and the International Electrotechnical Commission. Such an analysis is meaningful to security practitioners for an efficient management of information security. Moreover, the classification of the standards in the clauses of ISO/IEC 27001:2005 that results from our analysis is expected to provide assistance in dealing with the plethora of security standards.

Mathematical methods to analysis of topology, functional variability and evolution of metabolic systems based on different decomposition concepts.

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

Complexity of metabolic systems can be undertaken at different scales (metabolites, metabolic pathways, metabolic network map, biological population) and under different aspects (structural, functional, evolutive). To analyse such a complexity, metabolic systems need to be decomposed into different components according to different concepts. Four concepts are presented here consisting in considering metabolic systems as sets of metabolites, chemical reactions, metabolic pathways or successive processes. From a metabolomic dataset, such decompositions are performed using different mathematical methods including correlation, stiochiometric, ordination, classification, combinatorial and kinetic analyses. Correlation analysis detects and quantifies affinities/oppositions between metabolites. Stoichiometric analysis aims to identify the organisation of a metabolic network into different metabolic pathways on the hand, and to quantify/optimize the metabolic flux distribution through the different chemical reactions of the system. Ordination and classification analyses help to identify different metabolic trends and their associated metabolites in order to highlight chemical polymorphism representing different variability poles of the metabolic system. Then, metabolic processes/correlations responsible for such a polymorphism can be extracted in silico by combining metabolic profiles representative of different metabolic trends according to a weighting bootstrap approach. Finally evolution of metabolic processes in time can be analysed by different kinetic/dynamic modelling approaches.

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...

Validation of Resource Utilization Groups version III for Home Care (RUG-III/HC): evidence from a Canadian home care jurisdiction.

PubMed

Poss, Jeffrey W; Hirdes, John P; Fries, Brant E; McKillop, Ian; Chase, Mary

2008-04-01

The case-mix system Resource Utilization Groups version III for Home Care (RUG-III/HC) was derived using a modest data sample from Michigan, but to date no comprehensive large scale validation has been done. This work examines the performance of the RUG-III/HC classification using a large sample from Ontario, Canada. Cost episodes over a 13-week period were aggregated from individual level client billing records and matched to assessment information collected using the Resident Assessment Instrument for Home Care, from which classification rules for RUG-III/HC are drawn. The dependent variable, service cost, was constructed using formal services plus informal care valued at approximately one-half that of a replacement worker. An analytic dataset of 29,921 episodes showed a skewed distribution with over 56% of cases falling into the lowest hierarchical level, reduced physical functions. Case-mix index values for formal and informal cost showed very close similarities to those found in the Michigan derivation. Explained variance for a function of combined formal and informal cost was 37.3% (20.5% for formal cost alone), with personal support services as well as informal care showing the strongest fit to the RUG-III/HC classification. RUG-III/HC validates well compared with the Michigan derivation work. Potential enhancements to the present classification should consider the large numbers of undifferentiated cases in the reduced physical function group, and the low explained variance for professional disciplines.

Density Functional Theory (DFT) study of β-Hairpins in Antiparallel β-Sheets, A New Classification Based upon H-bond Topology

PubMed Central

Roy, Dipankar; Pohl, Gabor; Ali-Torres, Jorge; Marianski, Mateusz; Dannenberg, J. J.

2012-01-01

We present a new classification of β-turns specific to antiparallel β-sheets based upon the topology of H-bond formation. This classification results from ONIOM calculations using B3LYP/D95** DFT and AM1 semiempirical calculations as the high and low levels respectively. We chose acetyl(Ala)6NH2 as a model system as it is the simplest all alanine system that can form all the H-bonds required for a β-turn in a sheet. Of the ten different conformation we have found, the most stable structures have C7 cyclic H-bonds in place of the C10 interactions specified in the classic definition. Also, the chiralities specified for the i+1st and i+2nd residues in the classic definition disappear when the structures are optimized using our techniques, as the energetic differences between the four diastereomers of each structure are not substantial for eight of the ten conformations. PMID:22731966

The role of identity in the DSM-5 classification of personality disorders

PubMed Central

2013-01-01

In the revised Diagnostic and Statistical Manual DSM-5 the definition of personality disorder diagnoses has not been changed from that in the DSM-IV-TR. However, an alternative model for diagnosing personality disorders where the construct “identity” has been integrated as a central diagnostic criterion for personality disorders has been placed in section III of the manual. The alternative model’s hybrid nature leads to the simultaneous use of diagnoses and the newly developed “Level of Personality Functioning-Scale” (a dimensional tool to define the severity of the disorder). Pathological personality traits are assessed in five broad domains which are divided into 25 trait facets. With this dimensional approach, the new classification system gives, both clinicians and researchers, the opportunity to describe the patient in much more detail than previously possible. The relevance of identity problems in assessing and understanding personality pathology is illustrated using the new classification system applied in two case examples of adolescents with a severe personality disorder. PMID:23902698

The role of identity in the DSM-5 classification of personality disorders.

PubMed

Schmeck, Klaus; Schlüter-Müller, Susanne; Foelsch, Pamela A; Doering, Stephan

2013-07-31

In the revised Diagnostic and Statistical Manual DSM-5 the definition of personality disorder diagnoses has not been changed from that in the DSM-IV-TR. However, an alternative model for diagnosing personality disorders where the construct "identity" has been integrated as a central diagnostic criterion for personality disorders has been placed in section III of the manual. The alternative model's hybrid nature leads to the simultaneous use of diagnoses and the newly developed "Level of Personality Functioning-Scale" (a dimensional tool to define the severity of the disorder). Pathological personality traits are assessed in five broad domains which are divided into 25 trait facets. With this dimensional approach, the new classification system gives, both clinicians and researchers, the opportunity to describe the patient in much more detail than previously possible. The relevance of identity problems in assessing and understanding personality pathology is illustrated using the new classification system applied in two case examples of adolescents with a severe personality disorder.

Rename the family Ophioviridae and its constituent species

USDA-ARS?s Scientific Manuscript database

A transparent and functional system for virus classification is essential to allow scientists to correctly identify and report on viruses detected in different hosts or locations without ambiguity. This is a taxonomic proposal from the Ophioviridae Study Group of the International Committee on Viral...

14 CFR Section 8 - General

Code of Federal Regulations, 2011 CFR

2011-01-01

... UNIFORM SYSTEM OF ACCOUNTS AND REPORTS FOR LARGE CERTIFICATED AIR CARRIERS Profit and Loss Classification Section 8 General (a) The profit and loss accounts are designed to reflect, through natural groupings, the... the dual subdivision of profit and loss elements in terms of both natural objectives and functional...

23 CFR 970.212 - Federal lands safety management system (SMS).

Code of Federal Regulations, 2011 CFR

2011-04-01

...) An inventory of safety appurtenances such as signs, delineators, and guardrails (including terminals... upgrading safety appurtenances including highway-rail crossing warning devices, signs, highway elements, and... standards) for low volume roads may be tailored to be consistent with the functional classification of the...

23 CFR 970.212 - Federal lands safety management system (SMS).

Code of Federal Regulations, 2012 CFR

2012-04-01

...) An inventory of safety appurtenances such as signs, delineators, and guardrails (including terminals... upgrading safety appurtenances including highway-rail crossing warning devices, signs, highway elements, and... standards) for low volume roads may be tailored to be consistent with the functional classification of the...

23 CFR 970.212 - Federal lands safety management system (SMS).

Code of Federal Regulations, 2013 CFR

2013-04-01

...) An inventory of safety appurtenances such as signs, delineators, and guardrails (including terminals... upgrading safety appurtenances including highway-rail crossing warning devices, signs, highway elements, and... standards) for low volume roads may be tailored to be consistent with the functional classification of the...

23 CFR 970.212 - Federal lands safety management system (SMS).

Code of Federal Regulations, 2014 CFR

2014-04-01

...) An inventory of safety appurtenances such as signs, delineators, and guardrails (including terminals... upgrading safety appurtenances including highway-rail crossing warning devices, signs, highway elements, and... standards) for low volume roads may be tailored to be consistent with the functional classification of the...

MRS proof-of-concept on atmospheric corrections. Atmospheric corrections using an orbital pointable imaging system

NASA Technical Reports Server (NTRS)

Slater, P. N. (Principal Investigator)

1980-01-01

The feasibility of using a pointable imager to determine atmospheric parameters was studied. In particular the determination of the atmospheric extinction coefficient and the path radiance, the two quantities that have to be known in order to correct spectral signatures for atmospheric effects, was simulated. The study included the consideration of the geometry of ground irradiance and observation conditions for a pointable imager in a LANDSAT orbit as a function of time of year. A simulation study was conducted on the sensitivity of scene classification accuracy to changes in atmospheric condition. A two wavelength and a nonlinear regression method for determining the required atmospheric parameters were investigated. The results indicate the feasibility of using a pointable imaging system (1) for the determination of the atmospheric parameters required to improve classification accuracies in urban-rural transition zones and to apply in studies of bi-directional reflectance distribution function data and polarization effects; and (2) for the determination of the spectral reflectances of ground features.

Reliability of a novel, semi-quantitative scale for classification of structural brain magnetic resonance imaging in children with cerebral palsy.

PubMed

Fiori, Simona; Cioni, Giovanni; Klingels, Katrjin; Ortibus, Els; Van Gestel, Leen; Rose, Stephen; Boyd, Roslyn N; Feys, Hilde; Guzzetta, Andrea

2014-09-01

To describe the development of a novel rating scale for classification of brain structural magnetic resonance imaging (MRI) in children with cerebral palsy (CP) and to assess its interrater and intrarater reliability. The scale consists of three sections. Section 1 contains descriptive information about the patient and MRI. Section 2 contains the graphical template of brain hemispheres onto which the lesion is transposed. Section 3 contains the scoring system for the quantitative analysis of the lesion characteristics, grouped into different global scores and subscores that assess separately side, regions, and depth. A larger interrater and intrarater reliability study was performed in 34 children with CP (22 males, 12 females; mean age at scan of 9 y 5 mo [SD 3 y 3 mo], range 4 y-16 y 11 mo; Gross Motor Function Classification System level I, [n=22], II [n=10], and level III [n=2]). Very high interrater and intrarater reliability of the total score was found with indices above 0.87. Reliability coefficients of the lobar and hemispheric subscores ranged between 0.53 and 0.95. Global scores for hemispheres, basal ganglia, brain stem, and corpus callosum showed reliability coefficients above 0.65. This study presents the first visual, semi-quantitative scale for classification of brain structural MRI in children with CP. The high degree of reliability of the scale supports its potential application for investigating the relationship between brain structure and function and examining treatment response according to brain lesion severity in children with CP. © 2014 Mac Keith Press.

Age group estimation in free-ranging African elephants based on acoustic cues of low-frequency rumbles

PubMed Central

Stoeger, Angela S.; Zeppelzauer, Matthias; Baotic, Anton

2015-01-01

Animal vocal signals are increasingly used to monitor wildlife populations and to obtain estimates of species occurrence and abundance. In the future, acoustic monitoring should function not only to detect animals, but also to extract detailed information about populations by discriminating sexes, age groups, social or kin groups, and potentially individuals. Here we show that it is possible to estimate age groups of African elephants (Loxodonta africana) based on acoustic parameters extracted from rumbles recorded under field conditions in a National Park in South Africa. Statistical models reached up to 70 % correct classification to four age groups (infants, calves, juveniles, adults) and 95 % correct classification when categorising into two groups (infants/calves lumped into one group versus adults). The models revealed that parameters representing absolute frequency values have the most discriminative power. Comparable classification results were obtained by fully automated classification of rumbles by high-dimensional features that represent the entire spectral envelope, such as MFCC (75 % correct classification) and GFCC (74 % correct classification). The reported results and methods provide the scientific foundation for a future system that could potentially automatically estimate the demography of an acoustically monitored elephant group or population. PMID:25821348

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

2016-08-01

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

The cost-effectiveness of a treatment-based classification system for low back pain: design of a randomised controlled trial and economic evaluation

PubMed Central

2010-01-01

Background Systematic reviews have shown that exercise therapy and spinal manipulation are both more effective for low back pain (LBP) than no treatment at all. However, the effects are at best modest. To enhance the clinical outcomes, recommendations are to improve the patient selection process, and to identify relevant subgroups to guide clinical decision-making. One of the systems that has potentials to improve clinical decision-making is a treatment-based classification system that is intended to identify those patients who are most likely to respond to direction-specific exercises, manipulation, or stabilisation exercises. Methods/Design The primary aim of this randomised controlled trial will be to assess the effectiveness of a classification-based system. A sample of 150 patients with subacute and chronic LBP who attend a private physical therapy clinic for treatment will be recruited. At baseline, all participants will undergo a standard evaluation by trained research physical therapists and will be classified into one of the following subgroups: direction-specific exercises, manipulation, or stabilisation. The patient will not be informed about the results of the examination. Patients will be randomly assigned to classification-based treatment or usual care according to the Dutch LBP guidelines, and will complete questionnaires at baseline, and 8, 26, and 52 weeks after the start of the treatment. The primary outcomes will be general perceived recovery, functional status, and pain intensity. Alongside this trial, an economic evaluation of cost-effectiveness and cost-utility will be conducted from a societal perspective. Discussion The present study will contribute to our knowledge about the effectiveness and cost-effectiveness of classification-based treatment in patients with LBP. Trial registration Trial registration number: NTR1176 PMID:20346133

Digital ultrasonics signal processing: Flaw data post processing use and description

NASA Technical Reports Server (NTRS)

Buel, V. E.

1981-01-01

A modular system composed of two sets of tasks which interprets the flaw data and allows compensation of the data due to transducer characteristics is described. The hardware configuration consists of two main units. A DEC LSI-11 processor running under the RT-11 sngle job, version 2C-02 operating system, controls the scanner hardware and the ultrasonic unit. A DEC PDP-11/45 processor also running under the RT-11, version 2C-02, operating system, stores, processes and displays the flaw data. The software developed the Ultrasonics Evaluation System, is divided into two catagories; transducer characterization and flaw classification. Each category is divided further into two functional tasks: a data acquisition and a postprocessor ask. The flaw characterization collects data, compresses its, and writes it to a disk file. The data is then processed by the flaw classification postprocessing task. The use and operation of a flaw data postprocessor is described.

An experimental evaluation of the incidence of fitness-function/search-algorithm combinations on the classification performance of myoelectric control systems with iPCA tuning

PubMed Central

2013-01-01

Background The information of electromyographic signals can be used by Myoelectric Control Systems (MCSs) to actuate prostheses. These devices allow the performing of movements that cannot be carried out by persons with amputated limbs. The state of the art in the development of MCSs is based on the use of individual principal component analysis (iPCA) as a stage of pre-processing of the classifiers. The iPCA pre-processing implies an optimization stage which has not yet been deeply explored. Methods The present study considers two factors in the iPCA stage: namely A (the fitness function), and B (the search algorithm). The A factor comprises two levels, namely A1 (the classification error) and A2 (the correlation factor). Otherwise, the B factor has four levels, specifically B1 (the Sequential Forward Selection, SFS), B2 (the Sequential Floating Forward Selection, SFFS), B3 (Artificial Bee Colony, ABC), and B4 (Particle Swarm Optimization, PSO). This work evaluates the incidence of each one of the eight possible combinations between A and B factors over the classification error of the MCS. Results A two factor ANOVA was performed on the computed classification errors and determined that: (1) the interactive effects over the classification error are not significative (F0.01,3,72 = 4.0659 > f AB  = 0.09), (2) the levels of factor A have significative effects on the classification error (F0.02,1,72 = 5.0162 < f A  = 6.56), and (3) the levels of factor B over the classification error are not significative (F0.01,3,72 = 4.0659 > f B  = 0.08). Conclusions Considering the classification performance we found a superiority of using the factor A2 in combination with any of the levels of factor B. With respect to the time performance the analysis suggests that the PSO algorithm is at least 14 percent better than its best competitor. The latter behavior has been observed for a particular configuration set of parameters in the search algorithms. Future works will investigate the effect of these parameters in the classification performance, such as length of the reduced size vector, number of particles and bees used during optimal search, the cognitive parameters in the PSO algorithm as well as the limit of cycles to improve a solution in the ABC algorithm. PMID:24369728

Terminology and classification of muscle injuries in sport: The Munich consensus statement

PubMed Central

Mueller-Wohlfahrt, Hans-Wilhelm; Haensel, Lutz; Mithoefer, Kai; Ekstrand, Jan; English, Bryan; McNally, Steven; Orchard, John; van Dijk, C Niek; Kerkhoffs, Gino M; Schamasch, Patrick; Blottner, Dieter; Swaerd, Leif; Goedhart, Edwin; Ueblacker, Peter

2013-01-01

Objective To provide a clear terminology and classification of muscle injuries in order to facilitate effective communication among medical practitioners and development of systematic treatment strategies. Methods Thirty native English-speaking scientists and team doctors of national and first division professional sports teams were asked to complete a questionnaire on muscle injuries to evaluate the currently used terminology of athletic muscle injury. In addition, a consensus meeting of international sports medicine experts was established to develop practical and scientific definitions of muscle injuries as well as a new and comprehensive classification system. Results The response rate of the survey was 63%. The responses confirmed the marked variability in the use of the terminology relating to muscle injury, with the most obvious inconsistencies for the term strain. In the consensus meeting, practical and systematic terms were defined and established. In addition, a new comprehensive classification system was developed, which differentiates between four types: functional muscle disorders (type 1: overexertion-related and type 2: neuromuscular muscle disorders) describing disorders without macroscopic evidence of fibre tear and structural muscle injuries (type 3: partial tears and type 4: (sub)total tears/tendinous avulsions) with macroscopic evidence of fibre tear, that is, structural damage. Subclassifications are presented for each type. Conclusions A consistent English terminology as well as a comprehensive classification system for athletic muscle injuries which is proven in the daily practice are presented. This will help to improve clarity of communication for diagnostic and therapeutic purposes and can serve as the basis for future comparative studies to address the continued lack of systematic information on muscle injuries in the literature. What are the new things Consensus definitions of the terminology which is used in the field of muscle injuries as well as a new comprehensive classification system which clearly defines types of athletic muscle injuries. Level of evidence Expert opinion, Level V. PMID:23080315

A discrimlnant function approach to ecological site classification in northern New England

Treesearch

James M. Fincher; Marie-Louise Smith

1994-01-01

Describes one approach to ecologically based classification of upland forest community types of the White and Green Mountain physiographic regions. The classification approach is based on an intensive statistical analysis of the relationship between the communities and soil-site factors. Discriminant functions useful in distinguishing between types based on soil-site...

Pathohistological classification systems in gastric cancer: Diagnostic relevance and prognostic value

PubMed Central

Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

2014-01-01

Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer. PMID:24914328

A parametric multiclass Bayes error estimator for the multispectral scanner spatial model performance evaluation

NASA Technical Reports Server (NTRS)

Mobasseri, B. G.; Mcgillem, C. D.; Anuta, P. E. (Principal Investigator)

1978-01-01

The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.

A bayesian hierarchical model for classification with selection of functional predictors.

PubMed

Zhu, Hongxiao; Vannucci, Marina; Cox, Dennis D

2010-06-01

In functional data classification, functional observations are often contaminated by various systematic effects, such as random batch effects caused by device artifacts, or fixed effects caused by sample-related factors. These effects may lead to classification bias and thus should not be neglected. Another issue of concern is the selection of functions when predictors consist of multiple functions, some of which may be redundant. The above issues arise in a real data application where we use fluorescence spectroscopy to detect cervical precancer. In this article, we propose a Bayesian hierarchical model that takes into account random batch effects and selects effective functions among multiple functional predictors. Fixed effects or predictors in nonfunctional form are also included in the model. The dimension of the functional data is reduced through orthonormal basis expansion or functional principal components. For posterior sampling, we use a hybrid Metropolis-Hastings/Gibbs sampler, which suffers slow mixing. An evolutionary Monte Carlo algorithm is applied to improve the mixing. Simulation and real data application show that the proposed model provides accurate selection of functional predictors as well as good classification.

Use of a New International Classification of Health Interventions for Capturing Information on Health Interventions Relevant to People with Disabilities.

PubMed

Fortune, Nicola; Madden, Richard; Almborg, Ann-Helene

2018-01-17

Development of the World Health Organization's International Classification of Health Interventions (ICHI) is currently underway. Once finalised, ICHI will provide a standard basis for collecting, aggregating, analysing, and comparing data on health interventions across all sectors of the health system. In this paper, we introduce the classification, describing its underlying tri-axial structure, organisation and content. We then discuss the potential value of ICHI for capturing information on met and unmet need for health interventions relevant to people with a disability, with a particular focus on interventions to support functioning and health promotion interventions. Early experiences of use of the Swedish National Classification of Social Care Interventions and Activities, which is based closely on ICHI, illustrate the value of a standard classification to support practice and collect statistical data. Testing of the ICHI beta version in a wide range of countries and contexts is now needed so that improvements can be made before it is finalised. Input from those with an interest in the health of people with disabilities and health promotion more broadly is welcomed.

The future of transposable element annotation and their classification in the light of functional genomics - what we can learn from the fables of Jean de la Fontaine?

PubMed

Arensburger, Peter; Piégu, Benoît; Bigot, Yves

2016-01-01

Transposable element (TE) science has been significantly influenced by the pioneering ideas of David Finnegan near the end of the last century, as well as by the classification systems that were subsequently developed. Today, whole genome TE annotation is mostly done using tools that were developed to aid gene annotation rather than to specifically study TEs. We argue that further progress in the TE field is impeded both by current TE classification schemes and by a failure to recognize that TE biology is fundamentally different from that of multicellular organisms. Novel genome wide TE annotation methods are helping to redefine our understanding of TE sequence origins and evolution. We briefly discuss some of these new methods as well as ideas for possible alternative classification schemes. Our hope is to encourage the formation of a society to organize a larger debate on these questions and to promote the adoption of standards for annotation and an improved TE classification.

Chemometric and multivariate statistical analysis of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulfides.

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2012-03-20

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) spectra of mineral samples are complex, comprised of large mass ranges and many peaks. Consequently, characterization and classification analysis of these systems is challenging. In this study, different chemometric and statistical data evaluation methods, based on monolayer sensitive TOF-SIMS data, have been tested for the characterization and classification of copper-iron sulfide minerals (chalcopyrite, chalcocite, bornite, and pyrite) at different flotation pulp conditions (feed, conditioned feed, and Eh modified). The complex mass spectral data sets were analyzed using the following chemometric and statistical techniques: principal component analysis (PCA); principal component-discriminant functional analysis (PC-DFA); soft independent modeling of class analogy (SIMCA); and k-Nearest Neighbor (k-NN) classification. PCA was found to be an important first step in multivariate analysis, providing insight into both the relative grouping of samples and the elemental/molecular basis for those groupings. For samples exposed to oxidative conditions (at Eh ~430 mV), each technique (PCA, PC-DFA, SIMCA, and k-NN) was found to produce excellent classification. For samples at reductive conditions (at Eh ~ -200 mV SHE), k-NN and SIMCA produced the most accurate classification. Phase identification of particles that contain the same elements but a different crystal structure in a mixed multimetal mineral system has been achieved.

Vector analysis of postcardiotomy behavioral phenomena.

PubMed

Caston, J C; Miller, W C; Felber, W J

1975-04-01

The classification of postcardiotomy behavioral phenomena in Figure 1 is proposed for use as a clinical instrument to analyze etiological determinants. The utilization of a vector analysis analogy inherently denies absolutism. Classifications A-P are presented as prototypes of certain ratio imbalances of the metabolic, hemodynamic, environmental, and psychic vectors. Such a system allows for change from one type to another according to the individuality of the patient and the highly specific changes in his clinical presentation. A vector analysis also allows for infinite intermediary ratio imbalances between classification types as a function of time. Thus, postcardiotomy behavioral phenomena could be viewed as the vector summation of hemodynamic, metabolic, environmental, and psychic processes at a given point in time. Elaboration of unknown determinants in this complex syndrome appears to be task for the future.

Multispectral scanner system parameter study and analysis software system description, volume 2

NASA Technical Reports Server (NTRS)

Landgrebe, D. A. (Principal Investigator); Mobasseri, B. G.; Wiersma, D. J.; Wiswell, E. R.; Mcgillem, C. D.; Anuta, P. E.

1978-01-01

The author has identified the following significant results. The integration of the available methods provided the analyst with the unified scanner analysis package (USAP), the flexibility and versatility of which was superior to many previous integrated techniques. The USAP consisted of three main subsystems; (1) a spatial path, (2) a spectral path, and (3) a set of analytic classification accuracy estimators which evaluated the system performance. The spatial path consisted of satellite and/or aircraft data, data correlation analyzer, scanner IFOV, and random noise model. The output of the spatial path was fed into the analytic classification and accuracy predictor. The spectral path consisted of laboratory and/or field spectral data, EXOSYS data retrieval, optimum spectral function calculation, data transformation, and statistics calculation. The output of the spectral path was fended into the stratified posterior performance estimator.

Feature extraction via KPCA for classification of gait patterns.

PubMed

Wu, Jianning; Wang, Jue; Liu, Li

2007-06-01

Automated recognition of gait pattern change is important in medical diagnostics as well as in the early identification of at-risk gait in the elderly. We evaluated the use of Kernel-based Principal Component Analysis (KPCA) to extract more gait features (i.e., to obtain more significant amounts of information about human movement) and thus to improve the classification of gait patterns. 3D gait data of 24 young and 24 elderly participants were acquired using an OPTOTRAK 3020 motion analysis system during normal walking, and a total of 36 gait spatio-temporal and kinematic variables were extracted from the recorded data. KPCA was used first for nonlinear feature extraction to then evaluate its effect on a subsequent classification in combination with learning algorithms such as support vector machines (SVMs). Cross-validation test results indicated that the proposed technique could allow spreading the information about the gait's kinematic structure into more nonlinear principal components, thus providing additional discriminatory information for the improvement of gait classification performance. The feature extraction ability of KPCA was affected slightly with different kernel functions as polynomial and radial basis function. The combination of KPCA and SVM could identify young-elderly gait patterns with 91% accuracy, resulting in a markedly improved performance compared to the combination of PCA and SVM. These results suggest that nonlinear feature extraction by KPCA improves the classification of young-elderly gait patterns, and holds considerable potential for future applications in direct dimensionality reduction and interpretation of multiple gait signals.

How should children with speech sound disorders be classified? A review and critical evaluation of current classification systems.

PubMed

Waring, R; Knight, R

2013-01-01

Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of theoretically differing classification systems have been proposed based on either an aetiological (medical) approach, a descriptive-linguistic approach or a processing approach. To describe and review the supporting evidence, and to provide a critical evaluation of the current childhood SSD classification systems. Descriptions of the major specific approaches to classification are reviewed and research papers supporting the reliability and validity of the systems are evaluated. Three specific paediatric SSD classification systems; the aetiologic-based Speech Disorders Classification System, the descriptive-linguistic Differential Diagnosis system, and the processing-based Psycholinguistic Framework are identified as potentially useful in classifying children with SSD into homogeneous subgroups. The Differential Diagnosis system has a growing body of empirical support from clinical population studies, across language error pattern studies and treatment efficacy studies. The Speech Disorders Classification System is currently a research tool with eight proposed subgroups. The Psycholinguistic Framework is a potential bridge to linking cause and surface level speech errors. There is a need for a universally agreed-upon classification system that is useful to clinicians and researchers. The resulting classification system needs to be robust, reliable and valid. A universal classification system would allow for improved tailoring of treatments to subgroups of SSD which may, in turn, lead to improved treatment efficacy. © 2012 Royal College of Speech and Language Therapists.

Kyoto global consensus report on Helicobacter pylori gastritis

PubMed Central

Sugano, Kentaro; Tack, Jan; Kuipers, Ernst J; Graham, David Y; El-Omar, Emad M; Miura, Soichiro; Haruma, Ken; Asaka, Masahiro; Uemura, Naomi; Malfertheiner, Peter

2015-01-01

Objective To present results of the Kyoto Global Consensus Meeting, which was convened to develop global consensus on (1) classification of chronic gastritis and duodenitis, (2) clinical distinction of dyspepsia caused by Helicobacter pylori from functional dyspepsia, (3) appropriate diagnostic assessment of gastritis and (4) when, whom and how to treat H. pylori gastritis. Design Twenty-three clinical questions addressing the above-mentioned four domains were drafted for which expert panels were asked to formulate relevant statements. A Delphi method using an anonymous electronic system was adopted to develop the consensus, the level of which was predefined as ≥80%. Final modifications of clinical questions and consensus were achieved at the face-to-face meeting in Kyoto. Results All 24 statements for 22 clinical questions after extensive modifications and omission of one clinical question were achieved with a consensus level of >80%. To better organise classification of gastritis and duodenitis based on aetiology, a new classification of gastritis and duodenitis is recommended for the 11th international classification. A new category of H. pylori-associated dyspepsia together with a diagnostic algorithm was proposed. The adoption of grading systems for gastric cancer risk stratification, and modern image-enhancing endoscopy for the diagnosis of gastritis, were recommended. Treatment to eradicate H. pylori infection before preneoplastic changes develop, if feasible, was recommended to minimise the risk of more serious complications of the infection. Conclusions A global consensus for gastritis was developed for the first time, which will be the basis for an international classification system and for further research on the subject. PMID:26187502

Classification of oxidative stress based on its intensity

PubMed Central

Lushchak, Volodymyr I.

2014-01-01

In living organisms production of reactive oxygen species (ROS) is counterbalanced by their elimination and/or prevention of formation which in concert can typically maintain a steady-state (stationary) ROS level. However, this balance may be disturbed and lead to elevated ROS levels called oxidative stress. To our best knowledge, there is no broadly acceptable system of classification of oxidative stress based on its intensity due to which proposed here system may be helpful for interpretation of experimental data. Oxidative stress field is the hot topic in biology and, to date, many details related to ROS-induced damage to cellular components, ROS-based signaling, cellular responses and adaptation have been disclosed. However, it is common situation when researchers experience substantial difficulties in the correct interpretation of oxidative stress development especially when there is a need to characterize its intensity. Careful selection of specific biomarkers (ROS-modified targets) and some system may be helpful here. A classification of oxidative stress based on its intensity is proposed here. According to this classification there are four zones of function in the relationship between “Dose/concentration of inducer” and the measured “Endpoint”: I – basal oxidative stress (BOS); II – low intensity oxidative stress (LOS); III – intermediate intensity oxidative stress (IOS); IV – high intensity oxidative stress (HOS). The proposed classification will be helpful to describe experimental data where oxidative stress is induced and systematize it based on its intensity, but further studies will be in need to clear discriminate between stress of different intensity. PMID:26417312

5 CFR 9701.231 - Conversion of positions and employees to the DHS classification system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... the DHS classification system. 9701.231 Section 9701.231 Administrative Personnel DEPARTMENT OF... MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Transitional Provisions § 9701.231 Conversion of positions and employees to the DHS classification system. (a) This...

Integrating image processing and classification technology into automated polarizing film defect inspection

NASA Astrophysics Data System (ADS)

Kuo, Chung-Feng Jeffrey; Lai, Chun-Yu; Kao, Chih-Hsiang; Chiu, Chin-Hsun

2018-05-01

In order to improve the current manual inspection and classification process for polarizing film on production lines, this study proposes a high precision automated inspection and classification system for polarizing film, which is used for recognition and classification of four common defects: dent, foreign material, bright spot, and scratch. First, the median filter is used to remove the impulse noise in the defect image of polarizing film. The random noise in the background is smoothed by the improved anisotropic diffusion, while the edge detail of the defect region is sharpened. Next, the defect image is transformed by Fourier transform to the frequency domain, combined with a Butterworth high pass filter to sharpen the edge detail of the defect region, and brought back by inverse Fourier transform to the spatial domain to complete the image enhancement process. For image segmentation, the edge of the defect region is found by Canny edge detector, and then the complete defect region is obtained by two-stage morphology processing. For defect classification, the feature values, including maximum gray level, eccentricity, the contrast, and homogeneity of gray level co-occurrence matrix (GLCM) extracted from the images, are used as the input of the radial basis function neural network (RBFNN) and back-propagation neural network (BPNN) classifier, 96 defect images are then used as training samples, and 84 defect images are used as testing samples to validate the classification effect. The result shows that the classification accuracy by using RBFNN is 98.9%. Thus, our proposed system can be used by manufacturing companies for a higher yield rate and lower cost. The processing time of one single image is 2.57 seconds, thus meeting the practical application requirement of an industrial production line.

Probabilistic multiple sclerosis lesion classification based on modeling regional intensity variability and local neighborhood information.

PubMed

Harmouche, Rola; Subbanna, Nagesh K; Collins, D Louis; Arnold, Douglas L; Arbel, Tal

2015-05-01

In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. Statistically significant improvements in Dice values ( ), for voxel-based and lesion-based sensitivity values ( ), and positive predictive rates ( and respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1]. This holds particularly true in the posterior fossa, an area where classification is very challenging. The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

Group Treatment in Acquired Brain Injury Rehabilitation

ERIC Educational Resources Information Center

Bertisch, Hilary; Rath, Joseph F.; Langenbahn, Donna M.; Sherr, Rose Lynn; Diller, Leonard

2011-01-01

The current article describes critical issues in adapting traditional group-treatment methods for working with individuals with reduced cognitive capacity secondary to acquired brain injury. Using the classification system based on functional ability developed at the NYU Rusk Institute of Rehabilitation Medicine (RIRM), we delineate the cognitive…

75 FR 11620 - Agency Information Collection Activities: Notice of Request for Extension of Currently Approved...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-11

..., to the extent appropriate, safety, bridge, pavement, and congestion management systems for roads...; Pavement features such as number of lanes, length, width, surface type, functional classification, and shoulder information; and pavement condition information such as roughness, distress, rutting, and surface...

Examining transgender health through the International Classification of Functioning, Disability, and Health's (ICF) Contextual Factors.

PubMed

Jacob, Melissa; Cox, Steven R

2017-12-01

For many transgender individuals, medical intervention is necessary to live as their desired gender. However, little is known about Contextual Factors (i.e., Environmental and Personal) that may act as facilitators and barriers in the health of transgender individuals. Therefore, this paper sought to examine Contextual Factors of the World Health Organization's International Classification of Functioning, Disability, and Health that may facilitate or negatively impact the physical, psychological, and social functioning of transgender individuals. A literature review was conducted to identify Environmental and Personal Factors that may influence transgender individuals' physical, psychological, and social functioning. Seven electronic databases were searched. In total, 154 records were reviewed, and 41 articles and other records met inclusion criteria. Three general themes emerged for Environmental Factors: family and social networks, education, and health care. Three general themes also emerged for Personal Factors: socioeconomic status, race, and age. Transgender individuals benefit from gender-affirming services, improved family and social support systems, and competent provider care. Educational training programs, including medical curricula or workshops, might provide the greatest benefit in improving transgender health by increasing the knowledge and cultural competency of health professionals working with this population. Given the diversity of gender expression, differences in lived experiences, and potential for enduring persistent "double discrimination" due to the intersectional relationships between socioeconomic status, race, and/or age, health professionals must approach transgender health using a holistic lens such as the World Health Organization's International Classification of Functioning, Disability, and Health.

Disability and Profiles of Functioning of Patients with Parkinson's Disease Described with ICF Classification

ERIC Educational Resources Information Center

Raggi, Alberto; Leonardi, Matilde; Ajovalasit, Daniela; Carella, Francesco; Soliveri, Paola; Albanese, Alberto; Romito, Luigi

2011-01-01

The objective of this study was to describe the functional profiles of patients with Parkinson's disease (PD), and the relationships between impairment in body functions, limitations in activities, and environmental factors, using the World Health Organization's International Classification of Functioning, Disability, and Health (ICF). Patients…

Research on evaluating water resource resilience based on projection pursuit classification model

NASA Astrophysics Data System (ADS)

Liu, Dong; Zhao, Dan; Liang, Xu; Wu, Qiuchen

2016-03-01

Water is a fundamental natural resource while agriculture water guarantees the grain output, which shows that the utilization and management of water resource have a significant practical meaning. Regional agricultural water resource system features with unpredictable, self-organization, and non-linear which lays a certain difficulty on the evaluation of regional agriculture water resource resilience. The current research on water resource resilience remains to focus on qualitative analysis and the quantitative analysis is still in the primary stage, thus, according to the above issues, projection pursuit classification model is brought forward. With the help of artificial fish-swarm algorithm (AFSA), it optimizes the projection index function, seeks for the optimal projection direction, and improves AFSA with the application of self-adaptive artificial fish step and crowding factor. Taking Hongxinglong Administration of Heilongjiang as the research base and on the basis of improving AFSA, it established the evaluation of projection pursuit classification model to agriculture water resource system resilience besides the proceeding analysis of projection pursuit classification model on accelerating genetic algorithm. The research shows that the water resource resilience of Hongxinglong is the best than Raohe Farm, and the last 597 Farm. And the further analysis shows that the key driving factors influencing agricultural water resource resilience are precipitation and agriculture water consumption. The research result reveals the restoring situation of the local water resource system, providing foundation for agriculture water resource management.

Automated system function allocation and display format: Task information processing requirements

NASA Technical Reports Server (NTRS)

Czerwinski, Mary P.

1993-01-01

An important consideration when designing the interface to an intelligent system concerns function allocation between the system and the user. The display of information could be held constant, or 'fixed', leaving the user with the task of searching through all of the available information, integrating it, and classifying the data into a known system state. On the other hand, the system, based on its own intelligent diagnosis, could display only relevant information in order to reduce the user's search set. The user would still be left the task of perceiving and integrating the data and classifying it into the appropriate system state. Finally, the system could display the patterns of data. In this scenario, the task of integrating the data is carried out by the system, and the user's information processing load is reduced, leaving only the tasks of perception and classification of the patterns of data. Humans are especially adept at this form of display processing. Although others have examined the relative effectiveness of alphanumeric and graphical display formats, it is interesting to reexamine this issue together with the function allocation problem. Currently, Johnson Space Center is the test site for an intelligent Thermal Control System (TCS), TEXSYS, being tested for use with Space Station Freedom. Expert TCS engineers, as well as novices, were asked to classify several displays of TEXSYS data into various system states (including nominal and anomalous states). Three different display formats were used: fixed, subset, and graphical. The hypothesis tested was that the graphical displays would provide for fewer errors and faster classification times by both experts and novices, regardless of the kind of system state represented within the display. The subset displays were hypothesized to be the second most effective display format/function allocation condition, based on the fact that the search set is reduced in these displays. Both the subset and the graphic display conditions were hypothesized to be processed more efficiently than the fixed display conditions.

Aldehyde Recognition and Discrimination by Mammalian Odorant Receptors via Functional Group-Specific Hydration Chemistry

DTIC Science & Technology

2015-09-02

Agriculture, Food and Environment, The Hebrew University, Rehovot 76100, Israel ∥Department of Molecular Genetics and Microbiology , and Neurobiology, Duke...SECURITY CLASSIFICATION OF: The mammalian odorant receptors (ORs) form a chemical- detecting interface between the atmosphere and the nervous system...specificity for the aldehyde functional group, a significant percentage detect the aldehyde 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13

Using binary classification to prioritize and curate articles for the Comparative Toxicogenomics Database.

PubMed

Vishnyakova, Dina; Pasche, Emilie; Ruch, Patrick

2012-01-01

We report on the original integration of an automatic text categorization pipeline, so-called ToxiCat (Toxicogenomic Categorizer), that we developed to perform biomedical documents classification and prioritization in order to speed up the curation of the Comparative Toxicogenomics Database (CTD). The task can be basically described as a binary classification task, where a scoring function is used to rank a selected set of articles. Then components of a question-answering system are used to extract CTD-specific annotations from the ranked list of articles. The ranking function is generated using a Support Vector Machine, which combines three main modules: an information retrieval engine for MEDLINE (EAGLi), a gene normalization service (NormaGene) developed for a previous BioCreative campaign and finally, a set of answering components and entity recognizer for diseases and chemicals. The main components of the pipeline are publicly available both as web application and web services. The specific integration performed for the BioCreative competition is available via a web user interface at http://pingu.unige.ch:8080/Toxicat.

Perspectives on the International Classification of Functioning, Disability, and Health: Child and Youth Version (ICF-CY) and Occupational Therapy Practice

ERIC Educational Resources Information Center

Cramm, Heidi; Aiken, Alice B.; Stewart, Debra

2012-01-01

Classifying disability for children and youth has typically meant describing a diagnosis or developmental lag. The publication of the "International Classification of Functioning, Disability and Health: Child & Youth" version (ICF-CY) marks a global paradigm shift in the conceptualization and classification of childhood disability. Knowledge and…

Strengthening Rehabilitation in Health Systems Worldwide by Integrating Information on Functioning in National Health Information Systems.

PubMed

Stucki, Gerold; Bickenbach, Jerome; Melvin, John

2017-09-01

A complete understanding of the experience of health requires information relevant not merely to the health indicators of mortality and morbidity but also to functioning-that is, information about what it means to live in a health state, "the lived experience of health." Not only is functioning information relevant to healthcare and the overall objectives of person-centered healthcare but to the successful operation of all components of health systems.In light of population aging and major epidemiological trends, the health strategy of rehabilitation, whose aim has always been to optimize functioning and minimize disability, will become a key health strategy. The increasing prominence of the rehabilitative strategy within the health system drives the argument for the integration of functioning information as an essential component in national health information systems.Rehabilitation professionals and researchers have long recognized in WHO's International Classification of Functioning, Disability and Health the best prospect for an internationally recognized, sufficiently complete and powerful information reference for the documentation of functioning information. This paper opens the discussion of the promise of integrating the ICF as an essential component in national health systems to secure access to functioning information for rehabilitation, across health systems and countries.

Rough set soft computing cancer classification and network: one stone, two birds.

PubMed

Zhang, Yue

2010-07-15

Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

Predicting equipment needs of children with cerebral palsy using the Gross Motor Function Classification System: a cross-sectional study.

PubMed

Novak, Iona; Smithers-Sheedy, Hayley; Morgan, Cathy

2012-01-01

Children with cerebral palsy (CP) routinely use assistive equipment to improve their independence. Specialist equipment is expensive and therefore not always available to the child when needed. The aim of this study was to determine whether the assistive equipment needs of children with CP and the associated costs could be predicted. A cross-sectional study using a chart audit was completed. Two hundred forty-two children met eligibility criteria and were included in the study. Data abstracted from files pertained to the child's CP, associated impairments and assistive equipment prescribed. The findings were generated using linear regression modelling. Gross Motor Function Classification System (GMFCS) level [B = 3.01 (95% CI, 2.36-3.57), p = 0.000] and the presence of epilepsy [B = 2.35 (95% CI, 0.64-4.06), p = 0.008] predicted the prescription of assistive equipment. The more severely affected the gross motor function impairment, the more equipment that was required and the more the equipment cost. The equipment needs of children with CP can be predicted for the duration of childhood. This information may be useful for families and for budget and service planning.

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

NASA Technical Reports Server (NTRS)

Yakimovsky, Y.

1974-01-01

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Cognitive functioning in dyskinetic cerebral palsy: Its relation to motor function, communication and epilepsy.

PubMed

Ballester-Plané, Júlia; Laporta-Hoyos, Olga; Macaya, Alfons; Póo, Pilar; Meléndez-Plumed, Mar; Toro-Tamargo, Esther; Gimeno, Francisca; Narberhaus, Ana; Segarra, Dolors; Pueyo, Roser

2018-01-01

Cerebral palsy (CP) is a disorder of motor function often accompanied by cognitive impairment. There is a paucity of research focused on cognition in dyskinetic CP and on the potential effect of related factors. To describe the cognitive profile in dyskinetic CP and to assess its relationship with motor function and associated impairments. Fifty-two subjects with dyskinetic CP (28 males, mean age 24 y 10 mo, SD 13 y) and 52 typically-developing controls (age- and gender-matched) completed a comprehensive neuropsychological assessment. Gross Motor Function Classification System (GMFCS), Communication Function Classification System (CFCS) and epilepsy were recorded. Cognitive performance was compared between control and CP groups, also according different levels of GMFCS. The relationship between cognition, CFCS and epilepsy was examined through partial correlation coefficients, controlling for GMFCS. Dyskinetic CP participants performed worse than controls on all cognitive functions except for verbal memory. Milder cases (GMFCS I) only showed impairment in attention, visuoperception and visual memory. Participants with GMFCS II-III also showed impairment in language-related functions. Severe cases (GMFCS IV-V) showed impairment in intelligence and all specific cognitive functions but verbal memory. CFCS was associated with performance in receptive language functions. Epilepsy was related to performance in intelligence, visuospatial abilities, visual memory, grammar comprehension and learning. Cognitive performance in dyskinetic CP varies with the different levels of motor impairment, with more cognitive functions impaired as motor severity increases. This study also demonstrates the relationship between communication and epilepsy and cognitive functioning, even controlling for the effect of motor severity. Copyright © 2017 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

PubMed Central

Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

PubMed

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

Alignment of classification paradigms for communication abilities in children with cerebral palsy.

PubMed

Hustad, Katherine C; Oakes, Ashley; McFadd, Emily; Allison, Kristen M

2016-06-01

We examined three communication ability classification paradigms for children with cerebral palsy (CP): the Communication Function Classification System (CFCS), the Viking Speech Scale (VSS), and the Speech Language Profile Groups (SLPG). Questions addressed interjudge reliability, whether the VSS and the CFCS captured impairments in speech and language, and whether there were differences in speech intelligibility among levels within each classification paradigm. Eighty children (42 males, 38 females) with a range of types and severity levels of CP participated (mean age 60mo, range 50-72mo [SD 5mo]). Two speech-language pathologists classified each child via parent-child interaction samples and previous experience with the children for the CFCS and VSS, and using quantitative speech and language assessment data for the SLPG. Intelligibility scores were obtained using standard clinical intelligibility measurement. Kappa values were 0.67 (95% confidence interval [CI] 0.55-0.79) for the CFCS, 0.82 (95% CI 0.72-0.92) for the VSS, and 0.95 (95% CI 0.72-0.92) for the SLPG. Descriptively, reliability within levels of each paradigm varied, with the lowest agreement occurring within the CFCS at levels II (42%), III (40%), and IV (61%). Neither the CFCS nor the VSS were sensitive to language impairments captured by the SLPG. Significant differences in speech intelligibility were found among levels for all classification paradigms. Multiple tools are necessary to understand speech, language, and communication profiles in children with CP. Characterization of abilities at all levels of the International Classification of Functioning, Disability and Health will advance our understanding of the ways that speech, language, and communication abilities present in children with CP. © 2015 Mac Keith Press.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

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

PubMed

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

2015-01-01

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

23 CFR 970.212 - Federal lands safety management system (SMS).

Code of Federal Regulations, 2010 CFR

2010-04-01

... planning, design, construction, maintenance, and operations. (c) The SMS shall be designed to fit the NPS... for the collection, maintenance and reporting of a data base that includes: (i) Accident records with... standards) for low volume roads may be tailored to be consistent with the functional classification of the...

Comorbidity in "DSM" Childhood Mental Disorders: A Functional Perspective

ERIC Educational Resources Information Center

Cipani, Ennio

2014-01-01

In this article, I address the issue of comorbidity and its prevalence in the prior "Diagnostic and Statistical Manual of Mental Disorders" ("DSM") classification systems. The focus on the topography or form of presenting problems as the venue for determining mental disorders is scrutinized as the possible cause. Addressing the…

23 CFR 972.212 - Federal lands safety management system (SMS).

Code of Federal Regulations, 2010 CFR

2010-04-01

... functional classification to provide adequate information for use in making safety decisions in the RR... NHTSA, May 1996, may be obtained at the FHWA, Office of Safety, 1200 New Jersey Avenue, SE., Washington..., design, construction, maintenance, and operations. (d) The SMS may be utilized at various levels of...

On Teaching Brains To Think: A Conversation with Robert Sylwester.

ERIC Educational Resources Information Center

Brandt, Ron

2000-01-01

Sylwester says education must begin relying more on biology than social and behavioral science. All brain systems move from a slow, awkward functional level to a fast, efficient level. Contributions of metacognition, self-regulation, emotions, reflective and reflexive responses, comparison, and classification to cognitive development are…

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

USDA-ARS?s Scientific Manuscript database

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

3 new species in a proposed new genus Deltaflexivirus and new family Deltaflexiviridae in the order Tymovirales

USDA-ARS?s Scientific Manuscript database

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

Landscape object-based analysis of wetland plant functional types: the effects of spatial scale, vegetation classes and classifier methods

NASA Astrophysics Data System (ADS)

Dronova, I.; Gong, P.; Wang, L.; Clinton, N.; Fu, W.; Qi, S.

2011-12-01

Remote sensing-based vegetation classifications representing plant function such as photosynthesis and productivity are challenging in wetlands with complex cover and difficult field access. Recent advances in object-based image analysis (OBIA) and machine-learning algorithms offer new classification tools; however, few comparisons of different algorithms and spatial scales have been discussed to date. We applied OBIA to delineate wetland plant functional types (PFTs) for Poyang Lake, the largest freshwater lake in China and Ramsar wetland conservation site, from 30-m Landsat TM scene at the peak of spring growing season. We targeted major PFTs (C3 grasses, C3 forbs and different types of C4 grasses and aquatic vegetation) that are both key players in system's biogeochemical cycles and critical providers of waterbird habitat. Classification results were compared among: a) several object segmentation scales (with average object sizes 900-9000 m2); b) several families of statistical classifiers (including Bayesian, Logistic, Neural Network, Decision Trees and Support Vector Machines) and c) two hierarchical levels of vegetation classification, a generalized 3-class set and more detailed 6-class set. We found that classification benefited from object-based approach which allowed including object shape, texture and context descriptors in classification. While a number of classifiers achieved high accuracy at the finest pixel-equivalent segmentation scale, the highest accuracies and best agreement among algorithms occurred at coarser object scales. No single classifier was consistently superior across all scales, although selected algorithms of Neural Network, Logistic and K-Nearest Neighbors families frequently provided the best discrimination of classes at different scales. The choice of vegetation categories also affected classification accuracy. The 6-class set allowed for higher individual class accuracies but lower overall accuracies than the 3-class set because individual classes differed in scales at which they were best discriminated from others. Main classification challenges included a) presence of C3 grasses in C4-grass areas, particularly following harvesting of C4 reeds and b) mixtures of emergent, floating and submerged aquatic plants at sub-object and sub-pixel scales. We conclude that OBIA with advanced statistical classifiers offers useful instruments for landscape vegetation analyses, and that spatial scale considerations are critical in mapping PFTs, while multi-scale comparisons can be used to guide class selection. Future work will further apply fuzzy classification and field-collected spectral data for PFT analysis and compare results with MODIS PFT products.

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

PubMed

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

2015-12-01

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

LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches

PubMed Central

2014-01-01

Background Laccases (E.C. 1.10.3.2) are multi-copper oxidases that have gained importance in many industries such as biofuels, pulp production, textile dye bleaching, bioremediation, and food production. Their usefulness stems from the ability to act on a diverse range of phenolic compounds such as o-/p-quinols, aminophenols, polyphenols, polyamines, aryl diamines, and aromatic thiols. Despite acting on a wide range of compounds as a family, individual Laccases often exhibit distinctive and varied substrate ranges. This is likely due to Laccases involvement in many metabolic roles across diverse taxa. Classification systems for multi-copper oxidases have been developed using multiple sequence alignments, however, these systems seem to largely follow species taxonomy rather than substrate ranges, enzyme properties, or specific function. It has been suggested that the roles and substrates of various Laccases are related to their optimal pH. This is consistent with the observation that fungal Laccases usually prefer acidic conditions, whereas plant and bacterial Laccases prefer basic conditions. Based on these observations, we hypothesize that a descriptor-based unsupervised learning system could generate homology independent classification system for better describing the functional properties of Laccases. Results In this study, we first utilized unsupervised learning approach to develop a novel homology independent Laccase classification system. From the descriptors considered, physicochemical properties showed the best performance. Physicochemical properties divided the Laccases into twelve subtypes. Analysis of the clusters using a t-test revealed that the majority of the physicochemical descriptors had statistically significant differences between the classes. Feature selection identified the most important features as negatively charges residues, the peptide isoelectric point, and acidic or amidic residues. Secondly, to allow for classification of new Laccases, a supervised learning system was developed from the clusters. The models showed high performance with an overall accuracy of 99.03%, error of 0.49%, MCC of 0.9367, precision of 94.20%, sensitivity of 94.20%, and specificity of 99.47% in a 5-fold cross-validation test. In an independent test, our models still provide a high accuracy of 97.98%, error rate of 1.02%, MCC of 0.8678, precision of 87.88%, sensitivity of 87.88% and specificity of 98.90%. Conclusion This study provides a useful classification system for better understanding of Laccases from their physicochemical properties perspective. We also developed a publically available web tool for the characterization of Laccase protein sequences (http://lacsubpred.bioinfo.ucr.edu/). Finally, the programs used in the study are made available for researchers interested in applying the system to other enzyme classes (https://github.com/tweirick/SubClPred). PMID:25350584

Data Applicability of Heritage and New Hardware for Launch Vehicle System Reliability Models

NASA Technical Reports Server (NTRS)

Al Hassan Mohammad; Novack, Steven

2015-01-01

Many launch vehicle systems are designed and developed using heritage and new hardware. In most cases, the heritage hardware undergoes modifications to fit new functional system requirements, impacting the failure rates and, ultimately, the reliability data. New hardware, which lacks historical data, is often compared to like systems when estimating failure rates. Some qualification of applicability for the data source to the current system should be made. Accurately characterizing the reliability data applicability and quality under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This presentation will demonstrate a data-source classification method that ranks reliability data according to applicability and quality criteria to a new launch vehicle. This method accounts for similarities/dissimilarities in source and applicability, as well as operating environments like vibrations, acoustic regime, and shock. This classification approach will be followed by uncertainty-importance routines to assess the need for additional data to reduce uncertainty.

The neuron classification problem

PubMed Central

Bota, Mihail; Swanson, Larry W.

2007-01-01

A systematic account of neuron cell types is a basic prerequisite for determining the vertebrate nervous system global wiring diagram. With comprehensive lineage and phylogenetic information unavailable, a general ontology based on structure-function taxonomy is proposed and implemented in a knowledge management system, and a prototype analysis of select regions (including retina, cerebellum, and hypothalamus) presented. The supporting Brain Architecture Knowledge Management System (BAMS) Neuron ontology is online and its user interface allows queries about terms and their definitions, classification criteria based on the original literature and “Petilla Convention” guidelines, hierarchies, and relations—with annotations documenting each ontology entry. Combined with three BAMS modules for neural regions, connections between regions and neuron types, and molecules, the Neuron ontology provides a general framework for physical descriptions and computational modeling of neural systems. The knowledge management system interacts with other web resources, is accessible in both XML and RDF/OWL, is extendible to the whole body, and awaits large-scale data population requiring community participation for timely implementation. PMID:17582506

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

PubMed

Siddiqui, Muhammad Faisal; Reza, Ahmed Wasif; Kanesan, Jeevan

2015-01-01

A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.

n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation

PubMed Central

Palma Orozco, Rosaura

2018-01-01

Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe the signal behavior. Thus, great importance should be taken to feature extraction which is complicated for the Parameter Estimation (PE)–System Identification (SI) process. When based on an average approximation, nonstationary characteristics are presented. For PE the comparison of three forms of iterative-recursive uses of the Exponential Forgetting Factor (EFF) combined with a linear function to identify a synthetic stochastic signal is presented. The one with best results seen through the functional error is applied to approximate an EEG signal for a simple classification example, showing the effectiveness of our proposal. PMID:29568310

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Changes in the DRG classification system. 412.10... § 412.10 Changes in the DRG classification system. (a) General rule. CMS issues changes in the DRG classification system in a Federal Register notice at least annually. Except as specified in paragraphs (c) and...

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Changes in the DRG classification system. 412.10... § 412.10 Changes in the DRG classification system. (a) General rule. CMS issues changes in the DRG classification system in a Federal Register notice at least annually. Except as specified in paragraphs (c) and...

Evaluation of a wetland classification system devised for ...

EPA Pesticide Factsheets

The manuscript is part of an FY14 RAP product: "Functional Assessment of Alaska Peatlands in Cook Inlet Basin: A report to Region 10". This report included this technical information product which is a manuscript that has now been fully revised, reviewed and published in a scientific peer-reviewed publication with open access (doi:10.1007/s11273-016-9504-0). The journal article scientific abstract is as follows: "Several wetland classification schemes are now commonly used to describe wetlands in the contiguous United States to meet local, regional, and national regulatory requirements. However, these established systems have proven to be insufficient to meet the needs of land managers in Alaska. The wetlands of this northern region are predominantly peatlands, which are not adequately treated by the nationally-used systems, which have few, if any, peatland classes. A new system was therefore devised to classify wetlands in the rapidly urbanizing Cook Inlet Basin of southcentral Alaska, USA. The Cook Inlet Classification (CIC) is based on seven geomorphic and six hydrologic components that incorporate the environmental gradients responsible for the primary sources of variation in peatland ecosystems. The geomorphic and hydrologic components have the added advantage of being detectable on remote sensing imagery, which facilitates regional mapping across large tracts of inaccessible terrain. Three different quantitative measures were used to evaluate the robu

Correlation of the Rock Mass Rating (RMR) System with the Unified Soil Classification System (USCS): Introduction of the Weak Rock Mass Rating System (W-RMR)

NASA Astrophysics Data System (ADS)

Warren, Sean N.; Kallu, Raj R.; Barnard, Chase K.

2016-11-01

Underground gold mines in Nevada are exploiting increasingly deeper ore bodies comprised of weak to very weak rock masses. The Rock Mass Rating (RMR) classification system is widely used at underground gold mines in Nevada and is applicable in fair to good-quality rock masses, but is difficult to apply and loses reliability in very weak rock mass to soil-like material. Because very weak rock masses are transition materials that border engineering rock mass and soil classification systems, soil classification may sometimes be easier and more appropriate to provide insight into material behavior and properties. The Unified Soil Classification System (USCS) is the most likely choice for the classification of very weak rock mass to soil-like material because of its accepted use in tunnel engineering projects and its ability to predict soil-like material behavior underground. A correlation between the RMR and USCS systems was developed by comparing underground geotechnical RMR mapping to laboratory testing of bulk samples from the same locations, thereby assigning a numeric RMR value to the USCS classification that can be used in spreadsheet calculations and geostatistical analyses. The geotechnical classification system presented in this paper including a USCS-RMR correlation, RMR rating equations, and the Geo-Pick Strike Index is collectively introduced as the Weak Rock Mass Rating System (W-RMR). It is the authors' hope that this system will aid in the classification of weak rock masses and more usable design tools based on the RMR system. More broadly, the RMR-USCS correlation and the W-RMR system help define the transition between engineering soil and rock mass classification systems and may provide insight for geotechnical design in very weak rock masses.

Overweight and Obesity Prevalence Among School-Aged Nunavik Inuit Children According to Three Body Mass Index Classification Systems.

PubMed

Medehouenou, Thierry Comlan Marc; Ayotte, Pierre; St-Jean, Audray; Meziou, Salma; Roy, Cynthia; Muckle, Gina; Lucas, Michel

2015-07-01

Little is known about the suitability of three commonly used body mass index (BMI) classification system for Indigenous children. This study aims to estimate overweight and obesity prevalence among school-aged Nunavik Inuit children according to International Obesity Task Force (IOTF), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO) BMI classification systems, to measure agreement between those classification systems, and to investigate whether BMI status as defined by these classification systems is associated with levels of metabolic and inflammatory biomarkers. Data were collected on 290 school-aged children (aged 8-14 years; 50.7% girls) from the Nunavik Child Development Study with data collected in 2005-2010. Anthropometric parameters were measured and blood sampled. Participants were classified as normal weight, overweight, and obese according to BMI classification systems. Weighted kappa (κw) statistics assessed agreement between different BMI classification systems, and multivariate analysis of variance ascertained their relationship with metabolic and inflammatory biomarkers. The combined prevalence rate of overweight/obesity was 26.9% (with 6.6% obesity) with IOTF, 24.1% (11.0%) with CDC, and 40.4% (12.8%) with WHO classification systems. Agreement was the highest between IOTF and CDC (κw = .87) classifications, and substantial for IOTF and WHO (κw = .69) and for CDC and WHO (κw = .73). Insulin and high-sensitivity C-reactive protein plasma levels were significantly higher from normal weight to obesity, regardless of classification system. Among obese subjects, higher insulin level was observed with IOTF. Compared with other systems, IOTF classification appears to be more specific to identify overweight and obesity in Inuit children. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Typology of person-environment fit constellations: a platform addressing accessibility problems in the built environment for people with functional limitations.

PubMed

Slaug, Björn; Schilling, Oliver; Iwarsson, Susanne; Carlsson, Gunilla

2015-09-02

Making the built environment accessible for all regardless of functional capacity is an important goal for public health efforts. Considerable impediments to achieving this goal suggest the need for valid measurements of acccessibility and for greater attention to the complexity of person-environment fit issues. To address these needs, this study aimed to provide a methodological platform, useful for further research and instrument development within accessibility research. This was accomplished by the construction of a typology of problematic person-environment fit constellations, utilizing an existing methodology developed to assess and analyze accessibility problems in the built environment. By means of qualitative review and statistical methods we classified the person-environment fit components covered by an existing application which targets housing accessibility: the Housing Enabler (HE) instrument. The International Classification of Functioning, Disability and Health (ICF) was used as a conceptual framework. Qualitative classification principles were based on conceptual similarities and for quantitative analysis of similarities, Principal Component Analysis was carried out. We present a typology of problematic person-environment fit constellations classified along three dimensions: 1) accessibility problem range and severity 2) aspects of functioning 3) environmental context. As a result of the classification of the HE components, 48 typical person-environment fit constellations were recognised. The main contribution of this study is the proposed typology of person-environment fit constellations. The typology provides a methodological platform for the identification and quantification of problematic person-environment fit constellations. Its link to the globally accepted ICF classification system facilitates communication within the scientific and health care practice communities. The typology also highlights how relations between aspects of functioning and physical environmental barriers generate typical accessibility problems, and thereby furnishes a reference point for research oriented to how the built environment may be designed to be supportive for activity, participation and health.

Classification of Aircraft Maneuvers for Fault Detection

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.; Clancy, Daniel (Technical Monitor)

2002-01-01

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data is a reasonable match to known examples of proper operation. In our domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. We explain where this subsystem fits into our envisioned fault detection system as well its experiments showing the promise of this classification subsystem.

Acute kidney injury: not just acute renal failure anymore?

PubMed

Dirkes, Susan

2011-02-01

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

Skin problems in individuals with lower-limb loss: literature review and proposed classification system.

PubMed

Bui, Kelly M; Raugi, Gregory J; Nguyen, Viet Q; Reiber, Gayle E

2009-01-01

Problems with skin integrity can disrupt daily prosthesis use and lead to decreased mobility and function in individuals with lower-limb loss. This study reviewed the literature to examine how skin problems are defined and diagnosed and to identify the prevalence and types of skin problems in individuals with lower-limb loss. We searched the literature for terms related to amputation and skin problems. We identified 777 articles. Of the articles, 90 met criteria for review of research methodology. Four clinical studies met our selection criteria. The prevalence rate of skin problems was 15% to 41%. The most commonly reported skin problems were wounds, abscesses, and blisters. Given the lack of standardized definitions of skin problems on residual limbs, we conclude this article with a system for classification.

Functional Basis of Microorganism Classification.

PubMed

Zhu, Chengsheng; Delmont, Tom O; Vogel, Timothy M; Bromberg, Yana

2015-08-01

Correctly identifying nearest "neighbors" of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with phylogenetic descent.

Functional Basis of Microorganism Classification

PubMed Central

Zhu, Chengsheng; Delmont, Tom O.; Vogel, Timothy M.; Bromberg, Yana

2015-01-01

Correctly identifying nearest “neighbors” of a given microorganism is important in industrial and clinical applications where close relationships imply similar treatment. Microbial classification based on similarity of physiological and genetic organism traits (polyphasic similarity) is experimentally difficult and, arguably, subjective. Evolutionary relatedness, inferred from phylogenetic markers, facilitates classification but does not guarantee functional identity between members of the same taxon or lack of similarity between different taxa. Using over thirteen hundred sequenced bacterial genomes, we built a novel function-based microorganism classification scheme, functional-repertoire similarity-based organism network (FuSiON; flattened to fusion). Our scheme is phenetic, based on a network of quantitatively defined organism relationships across the known prokaryotic space. It correlates significantly with the current taxonomy, but the observed discrepancies reveal both (1) the inconsistency of functional diversity levels among different taxa and (2) an (unsurprising) bias towards prioritizing, for classification purposes, relatively minor traits of particular interest to humans. Our dynamic network-based organism classification is independent of the arbitrary pairwise organism similarity cut-offs traditionally applied to establish taxonomic identity. Instead, it reveals natural, functionally defined organism groupings and is thus robust in handling organism diversity. Additionally, fusion can use organism meta-data to highlight the specific environmental factors that drive microbial diversification. Our approach provides a complementary view to cladistic assignments and holds important clues for further exploration of microbial lifestyles. Fusion is a more practical fit for biomedical, industrial, and ecological applications, as many of these rely on understanding the functional capabilities of the microbes in their environment and are less concerned with phylogenetic descent. PMID:26317871

Functions in Biological Kind Classification

ERIC Educational Resources Information Center

Lombrozo, Tania; Rehder, Bob

2012-01-01

Biological traits that serve functions, such as a zebra's coloration (for camouflage) or a kangaroo's tail (for balance), seem to have a special role in conceptual representations for biological kinds. In five experiments, we investigate whether and why functional features are privileged in biological kind classification. Experiment 1…

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

Code of Federal Regulations, 2011 CFR

2011-10-01

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

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

Code of Federal Regulations, 2010 CFR

2010-10-01

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

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

PubMed

Lanfranconi, Silvia; Markus, Hugh S

2013-12-01

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

Maneuver Classification for Aircraft Fault Detection

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.

2003-01-01

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, identifying all possible faulty and proper operating modes is clearly impossible. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Classification of Aircraft Maneuvers for Fault Detection

NASA Technical Reports Server (NTRS)

Oza, Nikunj; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.; Koga, Dennis (Technical Monitor)

2002-01-01

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

PubMed

Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

2015-08-01

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

Developing applications of the ICF in education systems: addressing issues of knowledge creation, management and transfer.

PubMed

Hollenweger, Judith

2013-06-01

Since its endorsement, the International Classification of Functioning, Disability and Health (ICF) has been applied in many policy contexts, including education. While so far the focus has been on showing ways in which it can be used to describe functioning and disability, this article seeks to focus on its value to represent knowledge. Two applications of the ICF and ICF-CY in the context of the Swiss education system highlight ways in which the classification can be used to assist multidisciplinary teams in acquiring and mapping existing knowledge, in creating new knowledge and in applying it for specific purposes. The conceptual analysis illustrates that "disability in education" is a hybrid conceptual world that needs to bridge disability-related information with information relevant for learning and education. The ICF can be used to adequately map such knowledge in complex social settings. More attention needs to be paid to the ICF as an information system to help negotiate between different views on reality and different areas of expertise. The selection of content and ways of representing it need to be considered in the light of the specific purposes during collaborative knowledge creation processes.

Acoustic detection of biosonar activity of deep diving odontocetes at Josephine Seamount High Seas Marine Protected Area.

PubMed

Giorli, Giacomo; Au, Whitlow W L; Ou, Hui; Jarvis, Susan; Morrissey, Ronald; Moretti, David

2015-05-01

The temporal occurrence of deep diving cetaceans in the Josephine Seamount High Seas Marine Protected Area (JSHSMPA), south-west Portugal, was monitored using a passive acoustic recorder. The recorder was deployed on 13 May 2010 at a depth of 814 m during the North Atlantic Treaty Organization Centre for Maritime Research and Experimentation cruise "Sirena10" and recovered on 6 June 2010. The recorder was programmed to record 40 s of data every 2 min. Acoustic data analysis, for the detection and classification of echolocation clicks, was performed using automatic detector/classification systems: M3R (Marine Mammal Monitoring on Navy Ranges), a custom matlab program, and an operator-supervised custom matlab program to assess the classification performance of the detector/classification systems. M3R CS-SVM algorithm contains templates to detect beaked whales, sperm whales, blackfish (pilot and false killer whales), and Risso's dolphins. The detections of each group of odontocetes was monitored as a function of time. Blackfish and Risso's dolphins were detected every day, while beaked whales and sperm whales were detected almost every day. The hourly distribution of detections reveals that blackfish and Risso's dolphins were more active at night, while beaked whales and sperm whales were more active during daylight hours.

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

PubMed

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

2014-10-01

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

A subject-independent pattern-based Brain-Computer Interface

PubMed Central

Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos, Cristián; Zamorano, Francisco; Aboitiz, Francisco; Birbaumer, Niels; Ruiz, Sergio

2015-01-01

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders. PMID:26539089

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

A multi-label learning based kernel automatic recommendation method for support vector machine.

PubMed

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

PubMed Central

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

[Distal clavicle fractures. Classifications and management].

PubMed

Ockert, Ben; Wiedemann, E; Haasters, F

2015-05-01

Fractures of the distal third of the clavicle represent 10-30% of all clavicle fractures . Frequently, these fractures result in instability due to a combination of bony and ligamentous injury. Thus, assessment of the stability is essential for adequate treatment of these fractures. This article presents a review of the different classification systems for distal clavicle fractures with respect to anatomical and functional factors to allow for comprehensive assessment of stability. Furthermore, the different treatment options for each fracture type are analyzed. Fractures to the distal third of the clavicle without instability can be treated conservatively with satisfactory outcome. In contrast, instability may result in symptomatic non-union under conservative treatment; therefore, distal clavicle fractures with instability should be treated operatively with respect to the functional demands of the patient. Operative treatment with locked plating in combination with coracoclavicular fixation results in excellent functional results. Arthroscopically assisted fracture fixation may be beneficial in terms of a minimally invasive approach as well as assessment and treatment of associated glenohumeral lesions.

[Erectile function and ablative surgery of penile tumors].

PubMed

Pisani, E; Austoni, E; Trinchieri, A; Ceresoli, A; Mantovani, F; Colombo, F; Mastromarino, G; Vecchio, D; Canclini, L; Fenice, O

1994-02-01

The Authors try to show the possibility to combine radical excision with minimal invasiveness in the surgery of penile cancer. The focal point of every therapeutic decision is correct clinical staging. Unfortunately there's some confusion in the two international staging systems (TNM and Jackson's classification). In fact it's not clear the anatomical difference between epithelioma of the glans infiltrating corpus spongiosum and subcoronary epithelioma of the shaft infiltrating the corpora cavernosa. It's obvious that the infiltration of the corpora cavernosa is a far more aggressive oncological manifestation than that of tumour infiltrating the corpus spongiosum. So we consider Jackson's classification more congenial. In terms of surgery this anatomical independence makes it easy to consider the corpora cavernosa as a distinct entity, so they remain perfectly functional when separated from the glandulo-spongio-urethral unit with its vasculo-nervous bundle. This makes conservation of the erectile function, when clinical staging show us that the tumour is not infiltrating the corpora cavernosa. The Authors show their results, which seem to be rather good.

A clinicopathological approach to the diagnosis of dementia

PubMed Central

Elahi, Fanny M.; Miller, Bruce L.

2018-01-01

The most definitive classification systems for dementia are based on the underlying pathology which, in turn, is categorized largely according to the observed accumulation of abnormal protein aggregates in neurons and glia. These aggregates perturb molecular processes, cellular functions and, ultimately, cell survival, with ensuing disruption of large-scale neural networks subserving cognitive, behavioural and sensorimotor functions. The functional domains affected and the evolution of deficits in these domains over time serve as footprints that the clinician can trace back with various levels of certainty to the underlying neuropathology. The process of phenotyping and syndromic classification has substantially improved over decades of careful clinicopathological correlation, and through the discovery of in vivo biomarkers of disease. Here, we present an overview of the salient features of the most common dementia subtypes — Alzheimer disease, vascular dementia, frontotemporal dementia and related syndromes, Lewy body dementias, and prion diseases — with an emphasis on neuropathology, relevant epidemiology, risk factors, and signature signs and symptoms. PMID:28708131

Extensions to the Speech Disorders Classification System (SDCS)

ERIC Educational Resources Information Center

Shriberg, Lawrence D.; Fourakis, Marios; Hall, Sheryl D.; Karlsson, Heather B.; Lohmeier, Heather L.; McSweeny, Jane L.; Potter, Nancy L.; Scheer-Cohen, Alison R.; Strand, Edythe A.; Tilkens, Christie M.; Wilson, David L.

2010-01-01

This report describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). Part I describes a classification extension to the SDCS to differentiate motor speech disorders from speech delay and to differentiate among three sub-types of motor speech disorders.…

Feeding and gastrointestinal problems in children with cerebral palsy.

PubMed

Erkin, Gulten; Culha, Canan; Ozel, Sumru; Kirbiyik, Eylem Gulsen

2010-09-01

The aim of our study was to identify feeding and gastrointestinal system (GIS) problems in children with cerebral palsy (CP), and to evaluate the relationship between these problems and the severity of CP. A total of 120 children with CP were enrolled consecutively into the study (67 males, 53 females; mean age: 6.0±2.4 years; range: 2-12 years). The children were classified according to the Swedish classification as diplegic, hemiplegic, or quadriplegic. Severity of CP was classified based on the Gross Motor Function Classification System. The amount of time that the caregiver allocated to mealtimes, modifications of the food, as well as feeding and GIS problems was evaluated. Feeding dysfunction was classified as mild, moderate, or severe. Comparisons of GIS and feeding disorders and the severity of CP were carried out using χ test. The results indicated lack of appetite in 46 of the 120 children (38.3%), sialorrhea in 37 (30.8%), constipation in 30 (25%), difficulty in swallowing in 23 (19.2%), and feeding dysfunction in 26 (21.7%). On the basis of the Gross Motor Function Classification System (GMFCS), the incidence of GIS problems and feeding dysfunction was found to be significantly higher in the children classified in the severe group. The time taken to consume meals was significantly longer among children with feeding dysfunction. Feeding and GIS problems are frequent in children with CP, and more marked in those with severe CP. Approximately one fourth of children with CP suffer from feeding dysfunction, and more time has to be allocated to consume meals.

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.

Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

NASA Astrophysics Data System (ADS)

Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

2014-03-01

A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

The application of wavelet denoising in material discrimination system

NASA Astrophysics Data System (ADS)

Fu, Kenneth; Ranta, Dale; Guest, Clark; Das, Pankaj

2010-01-01

Recently, the need for cargo inspection imaging systems to provide a material discrimination function has become desirable. This is done by scanning the cargo container with x-rays at two different energy levels. The ratio of attenuations of the two energy scans can provide information on the composition of the material. However, with the statistical error from noise, the accuracy of such systems can be low. Because the moving source emits two energies of x-rays alternately, images from the two scans will not be identical. That means edges of objects in the two images are not perfectly aligned. Moreover, digitization creates blurry-edge artifacts. Different energy x-rays produce different edge spread functions. Those combined effects contribute to a source of false classification namely, the "edge effect." Other types of false classification are caused by noise, mainly Poisson noise associated with photons. The Poisson noise in xray images can be dealt with using either a Wiener filter or a wavelet shrinkage denoising approach. In this paper, we propose a method that uses the wavelet shrinkage denoising approach to enhance the performance of the material identification system. Test results show that this wavelet-based approach has improved performance in object detection and eliminating false positives due to the edge effects.

Disability and Functional Profiles of Patients with Migraine Measured with ICF Classification

ERIC Educational Resources Information Center

Raggi, Alberto

2010-01-01

To describe the functional profiles of patients with migraine, and the relationships between symptoms, activities and environmental factors, using WHO's International Classification of Functioning (ICF). Patients were consecutively enrolled at the Besta Institute of Milan. The ICF checklist was administered and two count-based indexes developed:…

Biological attachment devices: exploring nature's diversity for biomimetics.

PubMed

Gorb, Stanislav N

2008-05-13

Many species of animals and plants are supplied with diverse attachment devices, in which morphology depends on the species biology and the particular function in which the attachment device is involved. Many functional solutions have evolved independently in different lineages of animals and plants. Since the diversity of such biological structures is huge, there is a need for their classification. This paper, based on the original and literature data, proposes ordering of biological attachment systems according to several principles: (i) fundamental physical mechanism, according to which the system operates, (ii) biological function of the attachment device, and (iii) duration of the contact. Finally, we show a biomimetic potential of studies on biological attachment devices.

Verification of the Robin and Graham classification system of hip disease in cerebral palsy using three-dimensional computed tomography.

PubMed

Gose, Shinichi; Sakai, Takashi; Shibata, Toru; Akiyama, Keisuke; Yoshikawa, Hideki; Sugamoto, Kazuomi

2011-12-01

We evaluated the validity of the Robin and Graham classification system of hip disease in cerebral palsy (CP) using three-dimensional computed tomography in young people with CP. A total of 91 hips in 91 consecutive children with bilateral spastic CP (57 males, 34 females; nine classified at Gross Motor Function Classification System level II, 42 at level III, 32 at level IV, and eight at level V; mean age 5 y 2 mo, SD 11 mo; range 2-6 y) were investigated retrospectively using anteroposterior plain radiographs and three-dimensional computed tomography (3D-CT) of the hip. The migration percentage was calculated on plain radiographs and all participants were classified into four groups according to migration percentage: grade II, migration percentage ≥ 10% but ≤ 15%, (four hips), grade III, migration percentage >15% but ≤ 30%, (20 hips); grade IV, migration percentage >30% but <100%, (63 hips); and grade V, migration percentage ≥ 100%, (four hips). The lateral opening angle and the sagittal inclination angle of the acetabulum, the neck-shaft angle, and the femoral anteversion of the femur were measured on 3D-CT. The three-dimensional quantitative evaluation indicated that there were significant differences in the lateral opening angle and the neck-shaft angle between the four groups (Kruskal-Wallis test, p ≤ 0.001). This three-dimensional evaluation supports the validation of the Robin and Graham classification system for hip disease in 2- to 7-year-olds with CP. © The Authors. Developmental Medicine & Child Neurology © 2011 Mac Keith Press.

Kyoto global consensus report on Helicobacter pylori gastritis.

PubMed

Sugano, Kentaro; Tack, Jan; Kuipers, Ernst J; Graham, David Y; El-Omar, Emad M; Miura, Soichiro; Haruma, Ken; Asaka, Masahiro; Uemura, Naomi; Malfertheiner, Peter

2015-09-01

To present results of the Kyoto Global Consensus Meeting, which was convened to develop global consensus on (1) classification of chronic gastritis and duodenitis, (2) clinical distinction of dyspepsia caused by Helicobacter pylori from functional dyspepsia, (3) appropriate diagnostic assessment of gastritis and (4) when, whom and how to treat H. pylori gastritis. Twenty-three clinical questions addressing the above-mentioned four domains were drafted for which expert panels were asked to formulate relevant statements. A Delphi method using an anonymous electronic system was adopted to develop the consensus, the level of which was predefined as ≥80%. Final modifications of clinical questions and consensus were achieved at the face-to-face meeting in Kyoto. All 24 statements for 22 clinical questions after extensive modifications and omission of one clinical question were achieved with a consensus level of >80%. To better organise classification of gastritis and duodenitis based on aetiology, a new classification of gastritis and duodenitis is recommended for the 11th international classification. A new category of H. pylori-associated dyspepsia together with a diagnostic algorithm was proposed. The adoption of grading systems for gastric cancer risk stratification, and modern image-enhancing endoscopy for the diagnosis of gastritis, were recommended. Treatment to eradicate H. pylori infection before preneoplastic changes develop, if feasible, was recommended to minimise the risk of more serious complications of the infection. A global consensus for gastritis was developed for the first time, which will be the basis for an international classification system and for further research on the subject. 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.

Automatically high accurate and efficient photomask defects management solution for advanced lithography manufacture

NASA Astrophysics Data System (ADS)

Zhu, Jun; Chen, Lijun; Ma, Lantao; Li, Dejian; Jiang, Wei; Pan, Lihong; Shen, Huiting; Jia, Hongmin; Hsiang, Chingyun; Cheng, Guojie; Ling, Li; Chen, Shijie; Wang, Jun; Liao, Wenkui; Zhang, Gary

2014-04-01

Defect review is a time consuming job. Human error makes result inconsistent. The defects located on don't care area would not hurt the yield and no need to review them such as defects on dark area. However, critical area defects can impact yield dramatically and need more attention to review them such as defects on clear area. With decrease in integrated circuit dimensions, mask defects are always thousands detected during inspection even more. Traditional manual or simple classification approaches are unable to meet efficient and accuracy requirement. This paper focuses on automatic defect management and classification solution using image output of Lasertec inspection equipment and Anchor pattern centric image process technology. The number of mask defect found during an inspection is always in the range of thousands or even more. This system can handle large number defects with quick and accurate defect classification result. Our experiment includes Die to Die and Single Die modes. The classification accuracy can reach 87.4% and 93.3%. No critical or printable defects are missing in our test cases. The missing classification defects are 0.25% and 0.24% in Die to Die mode and Single Die mode. This kind of missing rate is encouraging and acceptable to apply on production line. The result can be output and reloaded back to inspection machine to have further review. This step helps users to validate some unsure defects with clear and magnification images when captured images can't provide enough information to make judgment. This system effectively reduces expensive inline defect review time. As a fully inline automated defect management solution, the system could be compatible with current inspection approach and integrated with optical simulation even scoring function and guide wafer level defect inspection.

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

PubMed

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

2018-04-01

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

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,…

Distinguish self- and hetero-perceived stress through behavioral imaging and physiological features.

PubMed

Spodenkiewicz, Michel; Aigrain, Jonathan; Bourvis, Nadège; Dubuisson, Séverine; Chetouani, Mohamed; Cohen, David

2018-03-02

Stress reactivity is a complex phenomenon associated to multiple and multimodal expressions. Response to stressors has an obvious survival function and may be seen as an internal regulation to adapt to threat or danger. The intensity of this internal response can be assessed as the self-perception of the stress response. In species with social organization, this response also serves a communicative function, so-called hetero-perception. Our study presents multimodal stress detection assessment - a new methodology combining behavioral imaging and physiological monitoring for analyzing stress from these two perspectives. The system is based on automatic extraction of 39 behavioral (2D+3D video recording) and 62 physiological (Nexus-10 recording) features during a socially evaluated mental arithmetic test. The analysis with machine learning techniques for automatic classification using Support Vector Machine (SVM) show that self-perception and hetero-perception of social stress are both close but different phenomena: self-perception was significantly correlated with hetero-perception but significantly differed from it. Also, assessing stress with SVM through multimodality gave excellent classification results (F1 score values: 0.9±0.012 for hetero-perception and 0.87±0.021 for self-perception). In the best selected feature subsets, we found some common behavioral and physiological features that allow classification of both self- and hetero-perceived stress. However, we also found the contributing features for automatic classifications had opposite distributions: self-perception classification was mainly based on physiological features and hetero-perception was mainly based on behavioral features. Copyright © 2017. Published by Elsevier Inc.

5 CFR 9901.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9901.221 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

Distinct timing mechanisms produce discrete and continuous movements.

PubMed

Huys, Raoul; Studenka, Breanna E; Rheaume, Nicole L; Zelaznik, Howard N; Jirsa, Viktor K

2008-04-25

The differentiation of discrete and continuous movement is one of the pillars of motor behavior classification. Discrete movements have a definite beginning and end, whereas continuous movements do not have such discriminable end points. In the past decade there has been vigorous debate whether this classification implies different control processes. This debate up until the present has been empirically based. Here, we present an unambiguous non-empirical classification based on theorems in dynamical system theory that sets discrete and continuous movements apart. Through computational simulations of representative modes of each class and topological analysis of the flow in state space, we show that distinct control mechanisms underwrite discrete and fast rhythmic movements. In particular, we demonstrate that discrete movements require a time keeper while fast rhythmic movements do not. We validate our computational findings experimentally using a behavioral paradigm in which human participants performed finger flexion-extension movements at various movement paces and under different instructions. Our results demonstrate that the human motor system employs different timing control mechanisms (presumably via differential recruitment of neural subsystems) to accomplish varying behavioral functions such as speed constraints.

Functional gastroduodenal disorders

PubMed Central

Talley, N; Stanghellini, V; Heading, R; Koch, K; Malagelada, J; Tytgat, G

1999-01-01

While widely used in research, the 1991 Rome criteria for the gastroduodenal disorders, especially symptom subgroups in dyspepsia, remain contentious. After a comprehensive literature search, a consensus-based approach was applied, supplemented by input from international experts who reviewed the report. Three functional gastroduodenal disorders are defined. Functional dyspepsia is persistent or recurrent pain or discomfort centered in the upper abdomen; evidence of organic disease likely to explain the symptoms is absent, including at upper endoscopy. Discomfort refers to a subjective, negative feeling that may be characterized by or associated with a number of non-painful symptoms including upper abdominal fullness, early satiety, bloating, or nausea. A dyspepsia subgroup classification is proposed for research purposes, based on the predominant (most bothersome) symptom: (a) ulcer-like dyspepsia when pain (from mild to severe) is the predominant symptom, and (b) dysmotility-like dyspepsia when discomfort (not pain) is the predominant symptom. This classification is supported by recent evidence suggesting that predominant symptoms, but not symptom clusters, identify subgroups with distinct underlying pathophysiological disturbances and responses to treatment. Aerophagia is an unusual complaint characterized by air swallowing that is objectively observed and troublesome repetitive belching. Functional vomiting refers to frequent episodes of recurrent vomiting that is not self-induced nor medication induced, and occurs in the absence of eating disorders, major psychiatric diseases, abnormalities in the gut or central nervous system, or metabolic diseases that can explain the symptom. The current classification requires careful validation but the criteria should be of value in future research.


Keywords: dyspepsia; functional dyspepsia; aerophagia; psychogenic vomiting; Rome II PMID:10457043

Performance evaluation of MLP and RBF feed forward neural network for the recognition of off-line handwritten characters

NASA Astrophysics Data System (ADS)

Rishi, Rahul; Choudhary, Amit; Singh, Ravinder; Dhaka, Vijaypal Singh; Ahlawat, Savita; Rao, Mukta

2010-02-01

In this paper we propose a system for classification problem of handwritten text. The system is composed of preprocessing module, supervised learning module and recognition module on a very broad level. The preprocessing module digitizes the documents and extracts features (tangent values) for each character. The radial basis function network is used in the learning and recognition modules. The objective is to analyze and improve the performance of Multi Layer Perceptron (MLP) using RBF transfer functions over Logarithmic Sigmoid Function. The results of 35 experiments indicate that the Feed Forward MLP performs accurately and exhaustively with RBF. With the change in weight update mechanism and feature-drawn preprocessing module, the proposed system is competent with good recognition show.

Identification of International Classification of Functioning, Disability and Health categories for patients with peripheral arterial disease.

PubMed

Vyskocil, Erich; Gruther, Wolfgang; Steiner, Irene; Schuhfried, Othmar

2014-07-01

Disease-specific categories of the International Classification of Functioning, Disability and Health have not yet been described for patients with chronic peripheral arterial obstructive disease (PAD). The authors examined the relationship between the categories of the Brief Core Sets for ischemic heart diseases with the Peripheral Artery Questionnaire and the ankle-brachial index to determine which International Classification of Functioning, Disability and Health categories are most relevant for patients with PAD. This is a retrospective cohort study including 77 patients with verified PAD. Statistical analyses of the relationship between International Classification of Functioning, Disability and Health categories as independent variables and the endpoints Peripheral Artery Questionnaire or ankle-brachial index were carried out by simple and stepwise linear regression models adjusting for age, sex, and leg (left vs. right). The stepwise linear regression model with the ankle-brachial index as dependent variable revealed a significant effect of the variables blood vessel functions and muscle endurance functions. Calculating a stepwise linear regression model with the Peripheral Artery Questionnaire as dependent variable, a significant effect of age, emotional functions, energy and drive functions, carrying out daily routine, as well as walking could be observed. This study identifies International Classification of Functioning, Disability and Health categories in the Brief Core Sets for ischemic heart diseases that show a significant effect on the ankle-brachial index and the Peripheral Artery Questionnaire score in patients with PAD. These categories provide fundamental information on functioning of patients with PAD and patient-centered outcomes for rehabilitation interventions.

The Bellevue Classification System: nursing's voice upon the library shelves*†

PubMed Central

Mages, Keith C

2011-01-01

This article examines the inspiration, construction, and meaning of the Bellevue Classification System (BCS), created during the 1930s for use in the Bellevue School of Nursing Library. Nursing instructor Ann Doyle, with assistance from librarian Mary Casamajor, designed the BCS after consulting with library leaders and examining leading contemporary classification systems, including the Dewey Decimal Classification and Library of Congress, Ballard, and National Health Library classification systems. A close textual reading of the classes, subclasses, and subdivisions of these classification systems against those of the resulting BCS, reveals Doyle's belief that the BCS was created not only to organize the literature, but also to promote the burgeoning intellectualism and professionalism of early twentieth-century American nursing. PMID:21243054

Coordination of Local Road Classification with the State Highway System Classification: Impact and Clarification of Related Language in the LVR Manual

DOT National Transportation Integrated Search

1996-02-01

This study reviewed the low volume road (LVR) classifications in Kansas in conjunction with the State A, B, C, D, E road classification system and addressed alignment of these differences. As an extension to the State system, an F, G, H classificatio...

Multiclassifier system with hybrid learning applied to the control of bioprosthetic hand.

PubMed

Kurzynski, Marek; Krysmann, Maciej; Trajdos, Pawel; Wolczowski, Andrzej

2016-02-01

In this paper the problem of recognition of the intended hand movements for the control of bio-prosthetic hand is addressed. The proposed method is based on recognition of electromiographic (EMG) and mechanomiographic (MMG) biosignals using a multiclassifier system (MCS) working in a two-level structure with a dynamic ensemble selection (DES) scheme and original concepts of competence function. Additionally, feedback information coming from bioprosthesis sensors on the correct/incorrect classification is applied to the adjustment of the combining mechanism during MCS operation through adaptive tuning competences of base classifiers depending on their decisions. Three MCS systems operating in decision tree structure and with different tuning algorithms are developed. In the MCS1 system, competence is uniformly allocated to each class belonging to the group indicated by the feedback signal. In the MCS2 system, the modification of competence depends on the node of decision tree at which a correct/incorrect classification is made. In the MCS3 system, the randomized model of classifier and the concept of cross-competence are used in the tuning procedure. Experimental investigations on the real data and computer-simulated procedure of generating feedback signals are performed. In these investigations classification accuracy of the MCS systems developed is compared and furthermore, the MCS systems are evaluated with respect to the effectiveness of the procedure of tuning competence. The results obtained indicate that modification of competence of base classifiers during the working phase essentially improves performance of the MCS system and that this improvement depends on the MCS system and tuning method used. Copyright © 2015 Elsevier Ltd. All rights reserved.

OECD Handbook for Internationally Comparative Education Statistics: Concepts, Standards, Definitions and Classifications

ERIC Educational Resources Information Center

OECD Publishing, 2017

2017-01-01

For well over two decades, the OECD has developed and published a broad range of comparative indicators published yearly in the flagship publication "Education at a Glance." These provide insights into the functioning of education systems, such as the participation and progress through education, the human and financial resources…

Autistic Disorder Symptoms in Rett Syndrome

ERIC Educational Resources Information Center

Wulffaert, Josette; Van Berckelaer-Onnes, Ina A.; Scholte, Evert M.

2009-01-01

According to the major classification systems it is not possible to diagnose a comorbid autistic disorder in persons with Rett syndrome. However, this is a controversial issue, and given the level of functioning of persons with Rett syndrome, the autistic disorder is expected to be present in a comparable proportion as in people with the same…

Comparison of 2 Orthotic Approaches in Children With Cerebral Palsy.

PubMed

Wren, Tishya A L; Dryden, James W; Mueske, Nicole M; Dennis, Sandra W; Healy, Bitte S; Rethlefsen, Susan A

2015-01-01

To compare dynamic ankle-foot orthoses (DAFOs) and adjustable dynamic response (ADR) ankle-foot orthoses (AFOs) in children with cerebral palsy. A total of 10 children with cerebral palsy (4-12 years; 6 at Gross Motor Function Classification System level I, 4 at Gross Motor Function Classification System level III) and crouch and/or equinus gait wore DAFOs and ADR-AFOs, each for 4 weeks, in randomized order. Laboratory-based gait analysis, walking activity monitor, and parent-reported questionnaire outcomes were compared among braces and barefoot conditions. Children demonstrated better stride length (11-12 cm), hip extension (2°-4°), and swing-phase dorsiflexion (9°-17°) in both braces versus barefoot. Push-off power (0.3 W/kg) and knee extension (5°) were better in ADR-AFOs than in DAFOs. Parent satisfaction and walking activity (742 steps per day, 43 minutes per day) were higher for DAFOs. ADR-AFOs produce better knee extension and push-off power; DAFOs produce more normal ankle motion, greater parent satisfaction, and walking activity. Both braces provide improvements over barefoot.

Evaluation of cognitive and social functioning in patients requiring long-term inpatient psychiatric care using the International Classification of Functioning, Disability, and Health: a large-scale, multi-institutional observational study.

PubMed

Kawaguchi, Hideaki; Taguchi, Masamoto; Sukigara, Masune; Sakuragi, Shoji; Sugiyama, Naoya; Chiba, Hisomu; Kawasaki, Tatsuhito

2017-06-15

We comprehensively evaluated cognitive and social functioning in patients requiring long-term inpatient psychiatric care using the International Classification of Functioning, Disability, and Health. We surveyed 1967 patients receiving long-term inpatient psychiatric care. Patients were further categorized into an old long-stay group (n = 892, >5 years in hospitals) and a new long-stay group (n = 1075, 1-5 years in hospitals). We obtained responses for all the International Classification of Functioning, Disability, and Health items in domain b (Body Functions) and domain d (Activities and Participation). We estimated weighted means for each item using the propensity score to adjust for confounding factors. Responses were received from 307 hospitals (response rate of hospitals: 25.5%). Cognitive and social functioning in the old long-stay group was more severely impaired than in the new long-stay group. No statistically significant differences were observed regarding the International Classification of Functioning, Disability, and Health items associated with basic activities of daily living between the two groups. Combined therapy consisting of cognitive remediation and rehabilitation on social functioning for this patient population should be started from the early stage of hospitalization. Non-restrictive, independent environments may also be optimal for this patient population. Implications for rehabilitation Rehabilitation of cognitive and social functioning for patients requiring long-term inpatient psychiatric care should be started in the early stages of hospitalization. In psychiatric fields, the International Classification of Functioning, Disability, and Health checklist could facilitate individualized rehabilitation planning by allowing healthcare professionals to visually assess the comprehensive functioning of each patient using graphics such as radar charts.

New KF-PP-SVM classification method for EEG in brain-computer interfaces.

PubMed

Yang, Banghua; Han, Zhijun; Zan, Peng; Wang, Qian

2014-01-01

Classification methods are a crucial direction in the current study of brain-computer interfaces (BCIs). To improve the classification accuracy for electroencephalogram (EEG) signals, a novel KF-PP-SVM (kernel fisher, posterior probability, and support vector machine) classification method is developed. Its detailed process entails the use of common spatial patterns to obtain features, based on which the within-class scatter is calculated. Then the scatter is added into the kernel function of a radial basis function to construct a new kernel function. This new kernel is integrated into the SVM to obtain a new classification model. Finally, the output of SVM is calculated based on posterior probability and the final recognition result is obtained. To evaluate the effectiveness of the proposed KF-PP-SVM method, EEG data collected from laboratory are processed with four different classification schemes (KF-PP-SVM, KF-SVM, PP-SVM, and SVM). The results showed that the overall average improvements arising from the use of the KF-PP-SVM scheme as opposed to KF-SVM, PP-SVM and SVM schemes are 2.49%, 5.83 % and 6.49 % respectively.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Incorporating spatial context into statistical classification of multidimensional image data

NASA Technical Reports Server (NTRS)

Bauer, M. E. (Principal Investigator); Tilton, J. C.; Swain, P. H.

1981-01-01

Compound decision theory is employed to develop a general statistical model for classifying image data using spatial context. The classification algorithm developed from this model exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. A key input to this contextural classifier is a quantitative characterization of this tendency: the context function. Several methods for estimating the context function are explored, and two complementary methods are recommended. The contextural classifier is shown to produce substantial improvements in classification accuracy compared to the accuracy produced by a non-contextural uniform-priors maximum likelihood classifier when these methods of estimating the context function are used. An approximate algorithm, which cuts computational requirements by over one-half, is presented. The search for an optimal implementation is furthered by an exploration of the relative merits of using spectral classes or information classes for classification and/or context function estimation.

Rough Set Soft Computing Cancer Classification and Network: One Stone, Two Birds

PubMed Central

Zhang, Yue

2010-01-01

Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article. PMID:20706619

Bimanual Capacity of Children With Cerebral Palsy: Intra- and Interrater Reliability of a Revised Edition of the Bimanual Fine Motor Function Classification.

PubMed

Elvrum, Ann-Kristin G; Beckung, Eva; Sæther, Rannei; Lydersen, Stian; Vik, Torstein; Himmelmann, Kate

2017-08-01

To develop a revised edition of the Bimanual Fine Motor Function (BFMF 2), as a classification of fine motor capacity in children with cerebral palsy (CP), and establish intra- and interrater reliability of this edition. The content of the original BFMF was discussed by an expert panel, resulting in a revised edition comprising the original description of the classification levels, but in addition including figures with specific explanatory text. Four professionals classified fine motor function of 79 children (3-17 years; 45 boys) who represented all subtypes of CP and Manual Ability Classification levels (I-V). Intra- and inter-rater reliability was assessed using overall intra-class correlation coefficient (ICC), and Cohen's quadratic weighted kappa. The overall ICC was 0.86. Cohen's weighted kappa indicated high intra-rater (к w : >0.90) and inter-rater (к w : >0.85) reliability. The revised BFMF 2 had high intra- and interrater reliability. The classification levels could be determined from short video recordings (<5 minutes), using the figures and precise descriptions of the fine motor function levels included in the BFMF 2. Thus, the BFMF 2 may be a feasible and useful classification of fine motor capacity both in research and in clinical practice.

Juvenile idiopathic arthritis in adulthood: fulfilment of classification criteria for adult rheumatic diseases, long-term outcomes and predictors of inactive disease, functional status and damage.

PubMed

Oliveira-Ramos, Filipa; Eusébio, Mónica; M Martins, Fernando; Mourão, Ana Filipa; Furtado, Carolina; Campanilho-Marques, Raquel; Cordeiro, Inês; Ferreira, Joana; Cerqueira, Marcos; Figueira, Ricardo; Brito, Iva; Canhão, Helena; Santos, Maria José; Melo-Gomes, José A; Fonseca, João Eurico

2016-01-01

To determine how adult juvenile idiopathic arthritis (JIA) patients fulfil classification criteria for adult rheumatic diseases, evaluate their outcomes and determine clinical predictors of inactive disease, functional status and damage. Patients with JIA registered on the Rheumatic Diseases Portuguese Register (Reuma.pt) older than 18 years and with more than 5 years of disease duration were included. Data regarding sociodemographic features, fulfilment of adult classification criteria, Health Assessment Questionnaire, Juvenile Arthritis Damage Index-articular (JADI-A) and Juvenile Arthritis Damage Index-extra-articular (JADI-E) damage index and disease activity were analysed. 426 patients were included. Most of patients with systemic JIA fulfilled criteria for Adult Still's disease. 95.6% of the patients with rheumatoid factor (RF)-positive polyarthritis and 57.1% of the patients with RF-negative polyarthritis matched criteria for rheumatoid arthritis (RA). 38.9% of the patients with extended oligoarthritis were classified as RA while 34.8% of the patients with persistent oligoarthritis were classified as spondyloarthritis. Patients with enthesitis-related arthritis fulfilled criteria for spondyloarthritis in 94.7%. Patients with psoriatic arthritis maintained this classification. Patients with inactive disease had lower disease duration, lower diagnosis delay and corticosteroids exposure. Longer disease duration was associated with higher HAQ, JADI-A and JADI-E. Higher JADI-A was also associated with biological treatment and retirement due to JIA disability and higher JADI-E with corticosteroids exposure. Younger age at disease onset was predictive of higher HAQ, JADI-A and JADI-E and decreased the chance of inactive disease. Most of the included patients fulfilled classification criteria for adult rheumatic diseases, maintain active disease and have functional impairment. Younger age at disease onset was predictive of higher disability and decreased the chance of inactive disease.

A Regional Guidebook for Applying the Hydrogeomorphic Approach to the Functional Assessment of Forested Wetlands in Alluvial Valleys of East Texas

DTIC Science & Technology

2010-10-01

the reference domain has been variously affected by human activities. Each river basin contains at least one reservoir that influences the timing...Phillips 2003). Transportation corridors, utility rights-of-way, oil and gas exploration, and channelization also affect hydrology by altering runoff...also are regularly affected by stream flooding, and therefore have a riverine functional component. This is incorporated in the classification system

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Classification of close binary systems by Svechnikov

NASA Astrophysics Data System (ADS)

Dryomova, G. N.

The paper presents the historical overview of classification schemes of eclipsing variable stars with the foreground of advantages of the classification scheme by Svechnikov being widely appreciated for Close Binary Systems due to simplicity of classification criteria and brevity.

Disability and Functional Profiles of Patients with Myasthenia Gravis Measured with ICF Classification

ERIC Educational Resources Information Center

Leonardi, Matilde; Raggi, Alberto; Antozzi, Carlo; Confalonieri, Paolo; Maggi, Lorenzo; Cornelio, Ferdinando; Mantegazza, Renato

2009-01-01

The objective of this study is to describe functional profiles of patients with myasthenia gravis (MG), and the relationships among symptoms, activities and environmental factors (EF), by using WHO's International Classification of Functioning Disability and Health (ICF). Patients were consecutively enrolled at the Besta Institute of Milan, Italy.…

Aligning Physical Activity Measures with the International Classification of Functioning, Disability and Health Framework for Childhood Disability

ERIC Educational Resources Information Center

Ross, Samantha Mae; Case, Layne; Leung, Willie

2016-01-01

The introduction of the International Classification of Functioning, Disability and Health has placed emphasis on framing health behavior as a multidimensional construct. In relation to childhood physical activity, this encompasses dimensions of functional performance, activity attendance, and subjective perceptions of involvement and enjoyment…

Use of DAVID algorithms for gene functional classification in a non-model organism, rainbow trout

USDA-ARS?s Scientific Manuscript database

Gene functional clustering is essential in transcriptome data analysis but software programs are not always suitable for use with non-model species. The DAVID Gene Functional Classification Tool has been widely used for soft clustering in model species, but requires adaptations for use in non-model ...

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.

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

NASA Astrophysics Data System (ADS)

Jiang, Jifa; Niu, Lei

2017-12-01

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

Statistical fingerprinting for malware detection and classification

DOEpatents

Prowell, Stacy J.; Rathgeb, Christopher T.

2015-09-15

A system detects malware in a computing architecture with an unknown pedigree. The system includes a first computing device having a known pedigree and operating free of malware. The first computing device executes a series of instrumented functions that, when executed, provide a statistical baseline that is representative of the time it takes the software application to run on a computing device having a known pedigree. A second computing device executes a second series of instrumented functions that, when executed, provides an actual time that is representative of the time the known software application runs on the second computing device. The system detects malware when there is a difference in execution times between the first and the second computing devices.

Drug-induced sedation endoscopy (DISE) classification systems: a systematic review and meta-analysis.

PubMed

Dijemeni, Esuabom; D'Amone, Gabriele; Gbati, Israel

2017-12-01

Drug-induced sedation endoscopy (DISE) classification systems have been used to assess anatomical findings on upper airway obstruction, and decide and plan surgical treatments and act as a predictor for surgical treatment outcome for obstructive sleep apnoea management. The first objective is to identify if there is a universally accepted DISE grading and classification system for analysing DISE findings. The second objective is to identify if there is one DISE grading and classification treatment planning framework for deciding appropriate surgical treatment for obstructive sleep apnoea (OSA). The third objective is to identify if there is one DISE grading and classification treatment outcome framework for determining the likelihood of success for a given OSA surgical intervention. A systematic review was performed to identify new and significantly modified DISE classification systems: concept, advantages and disadvantages. Fourteen studies proposing a new DISE classification system and three studies proposing a significantly modified DISE classification were identified. None of the studies were based on randomised control trials. DISE is an objective method for visualising upper airway obstruction. The classification and assessment of clinical findings based on DISE is highly subjective due to the increasing number of DISE classification systems. Hence, this creates a growing divergence in surgical treatment planning and treatment outcome. Further research on a universally accepted objective DISE assessment is critically needed.

A New Tool for Climatic Analysis Using the Koppen Climate Classification

ERIC Educational Resources Information Center

Larson, Paul R.; Lohrengel, C. Frederick, II

2011-01-01

The purpose of climate classification is to help make order of the seemingly endless spatial distribution of climates. The Koppen classification system in a modified format is the most widely applied system in use today. This system may not be the best nor most complete climate classification that can be conceived, but it has gained widespread…

JOURNAL SCOPE GUIDELINES: Paper classification scheme

NASA Astrophysics Data System (ADS)

2005-06-01

This scheme is used to clarify the journal's scope and enable authors and readers to more easily locate the appropriate section for their work. For each of the sections listed in the scope statement we suggest some more detailed subject areas which help define that subject area. These lists are by no means exhaustive and are intended only as a guide to the type of papers we envisage appearing in each section. We acknowledge that no classification scheme can be perfect and that there are some papers which might be placed in more than one section. We are happy to provide further advice on paper classification to authors upon request (please email jphysa@iop.org). 1. Statistical physics numerical and computational methods statistical mechanics, phase transitions and critical phenomena quantum condensed matter theory Bose-Einstein condensation strongly correlated electron systems exactly solvable models in statistical mechanics lattice models, random walks and combinatorics field-theoretical models in statistical mechanics disordered systems, spin glasses and neural networks nonequilibrium systems network theory 2. Chaotic and complex systems nonlinear dynamics and classical chaos fractals and multifractals quantum chaos classical and quantum transport cellular automata granular systems and self-organization pattern formation biophysical models 3. Mathematical physics combinatorics algebraic structures and number theory matrix theory classical and quantum groups, symmetry and representation theory Lie algebras, special functions and orthogonal polynomials ordinary and partial differential equations difference and functional equations integrable systems soliton theory functional analysis and operator theory inverse problems geometry, differential geometry and topology numerical approximation and analysis geometric integration computational methods 4. Quantum mechanics and quantum information theory coherent states eigenvalue problems supersymmetric quantum mechanics scattering theory relativistic quantum mechanics semiclassical approximations foundations of quantum mechanics and measurement theory entanglement and quantum nonlocality geometric phases and quantum tomography quantum tunnelling decoherence and open systems quantum cryptography, communication and computation theoretical quantum optics 5. Classical and quantum field theory quantum field theory gauge and conformal field theory quantum electrodynamics and quantum chromodynamics Casimir effect integrable field theory random matrix theory applications in field theory string theory and its developments classical field theory and electromagnetism metamaterials 6. Fluid and plasma theory turbulence fundamental plasma physics kinetic theory magnetohydrodynamics and multifluid descriptions strongly coupled plasmas one-component plasmas non-neutral plasmas astrophysical and dusty plasmas

Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae

PubMed Central

Udatha, D. B. R. K. Gupta; Mapelli, Valeria; Panagiotou, Gianni; Olsson, Lisbeth

2012-01-01

Background Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. Methodology/Principal Findings The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Conclusions/Significance Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods. PMID:22745763

Common and distant structural characteristics of feruloyl esterase families from Aspergillus oryzae.

PubMed

Udatha, D B R K Gupta; Mapelli, Valeria; Panagiotou, Gianni; Olsson, Lisbeth

2012-01-01

Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods.

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

PubMed

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

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

Computer-aided classification of patients with dementia of Alzheimer's type based on cerebral blood flow determined with arterial spin labeling technique

NASA Astrophysics Data System (ADS)

Yamashita, Yasuo; Arimura, Hidetaka; Yoshiura, Takashi; Tokunaga, Chiaki; Magome, Taiki; Monji, Akira; Noguchi, Tomoyuki; Toyofuku, Fukai; Oki, Masafumi; Nakamura, Yasuhiko; Honda, Hiroshi

2010-03-01

Arterial spin labeling (ASL) is one of promising non-invasive magnetic resonance (MR) imaging techniques for diagnosis of Alzheimer's disease (AD) by measuring cerebral blood flow (CBF). The aim of this study was to develop a computer-aided classification system for AD patients based on CBFs measured by the ASL technique. The average CBFs in cortical regions were determined as functional image features based on the CBF map image, which was non-linearly transformed to a Talairach brain atlas by using a free-form deformation. An artificial neural network (ANN) was trained with the CBF functional features in 10 cortical regions, and was employed for distinguishing patients with AD from control subjects. For evaluation of the method, we applied the proposed method to 20 cases including ten AD patients and ten control subjects, who were scanned a 3.0-Tesla MR unit. As a result, the area under the receiver operating characteristic curve obtained by the proposed method was 0.893 based on a leave-one-out-by-case test in identification of AD cases among 20 cases. The proposed method would be feasible for classification of patients with AD.

Autonomous underwater vehicle adaptive path planning for target classification

NASA Astrophysics Data System (ADS)

Edwards, Joseph R.; Schmidt, Henrik

2002-11-01

Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.

The postoperative COFAS end-stage ankle arthritis classification system: interobserver and intraobserver reliability.

PubMed

Krause, Fabian G; Di Silvestro, Matthew; Penner, Murray J; Wing, Kevin J; Glazebrook, Mark A; Daniels, Timothy R; Lau, Johnny T C; Younger, Alastair S E

2012-02-01

End-stage ankle arthritis is operatively treated with numerous designs of total ankle replacement and different techniques for ankle fusion. For superior comparison of these procedures, outcome research requires a classification system to stratify patients appropriately. A postoperative 4-type classification system was designed by 6 fellowship-trained foot and ankle surgeons. Four surgeons reviewed blinded patient profiles and radiographs on 2 occasions to determine the interobserver and intraobserver reliability of the classification. Excellent interobserver reliability (κ = .89) and intraobserver reproducibility (κ = .87) were demonstrated for the postoperative classification system. In conclusion, the postoperative Canadian Orthopaedic Foot and Ankle Society (COFAS) end-stage ankle arthritis classification system appears to be a valid tool to evaluate the outcome of patients operated for end-stage ankle arthritis.

Feasibility of using the International Classification of Functioning, Disability and Health Core Set for evaluation of fall-related risk factors in acute rehabilitation settings.

PubMed

Huang, Shih W; Lin, Li F; Chou, Lin C; Wu, Mei J; Liao, Chun D; Liou, Tsan H

2016-04-01

Previously, we reported the use of an International Classification of Functioning (ICF) core set that can provide a holistic framework for evaluating the risk factors of falls; however, data on the feasibility of applying this core set are lacking. To investigate the feasibility of applying the fall-related ICF risk-factor core set in the case of patients in an acute-rehabilitation setting. A cross-sectional and descriptive correlational design. Acute-rehabilitation ward. A total of 273 patients who experienced fall at acute-rehabilitation ward. The data on falls were collected from the hospital's Nursing Information System (NIS) and the fall-reporting system (Adverse Event Reporting System, AERS) between 2010 and 2013. The relationship of both systems to the fall-related ICF core set was analyzed to assess the feasibility of their clinical application. We evaluated the feasibility of using the fall-related ICF risk-factor core set by using the frequency and the percentage of the fall patients in of the listed categories. The fall-related ICF risk-factor core set category b735 (muscle tone functions) exhibited a high feasibility (85.95%) for clinical application, and the category b730 (muscle power functions) covered 77.11% of the patients. The feasibility of application of the category d410 (change basic body position) was also high in the case of all fall patients (81.69%). In the acute-rehabilitation setting, the feasibility of application of the fall-related ICF risk-factor core set is high. The fall-related ICF risk-factor core set can help multidisciplinary teams develop fall-prevention strategies in acute rehabilitation wards.

Bidirectional reflectance distribution function based surface modeling of non-Lambertian using intensity data of light detection and ranging.

PubMed

Li, Xiaolu; Liang, Yu; Xu, Lijun

2014-09-01

To provide a credible model for light detection and ranging (LiDAR) target classification, the focus of this study is on the relationship between intensity data of LiDAR and the bidirectional reflectance distribution function (BRDF). An integration method based on the built-in-lab coaxial laser detection system was advanced. A kind of intermediary BRDF model advanced by Schlick was introduced into the integration method, considering diffuse and specular backscattering characteristics of the surface. A group of measurement campaigns were carried out to investigate the influence of the incident angle and detection range on the measured intensity data. Two extracted parameters r and S(λ) are influenced by different surface features, which illustrate the surface features of the distribution and magnitude of reflected energy, respectively. The combination of two parameters can be used to describe the surface characteristics for target classification in a more plausible way.

Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

PubMed

Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

2012-01-01

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

GDF v2.0, an enhanced version of GDF

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Gavrilis, Dimitris; Dermatas, Evangelos

2007-12-01

An improved version of the function estimation program GDF is presented. The main enhancements of the new version include: multi-output function estimation, capability of defining custom functions in the grammar and selection of the error function. The new version has been evaluated on a series of classification and regression datasets, that are widely used for the evaluation of such methods. It is compared to two known neural networks and outperforms them in 5 (out of 10) datasets. Program summaryTitle of program: GDF v2.0 Catalogue identifier: ADXC_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXC_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 98 147 No. of bytes in distributed program, including test data, etc.: 2 040 684 Distribution format: tar.gz Programming language: GNU C++ Computer: The program is designed to be portable in all systems running the GNU C++ compiler Operating system: Linux, Solaris, FreeBSD RAM: 200000 bytes Classification: 4.9 Does the new version supersede the previous version?: Yes Nature of problem: The technique of function estimation tries to discover from a series of input data a functional form that best describes them. This can be performed with the use of parametric models, whose parameters can adapt according to the input data. Solution method: Functional forms are being created by genetic programming which are approximations for the symbolic regression problem. Reasons for new version: The GDF package was extended in order to be more flexible and user customizable than the old package. The user can extend the package by defining his own error functions and he can extend the grammar of the package by adding new functions to the function repertoire. Also, the new version can perform function estimation of multi-output functions and it can be used for classification problems. Summary of revisions: The following features have been added to the package GDF: Multi-output function approximation. The package can now approximate any function f:R→R. This feature gives also to the package the capability of performing classification and not only regression. User defined function can be added to the repertoire of the grammar, extending the regression capabilities of the package. This feature is limited to 3 functions, but easily this number can be increased. Capability of selecting the error function. The package offers now to the user apart from the mean square error other error functions such as: mean absolute square error, maximum square error. Also, user defined error functions can be added to the set of error functions. More verbose output. The main program displays more information to the user as well as the default values for the parameters. Also, the package gives to the user the capability to define an output file, where the output of the gdf program for the testing set will be stored after the termination of the process. Additional comments: A technical report describing the revisions, experiments and test runs is packaged with the source code. Running time: Depending on the train data.

Cause of and factors associated with stillbirth: a systematic review of classification systems.

PubMed

Aminu, Mamuda; Bar-Zeev, Sarah; van den Broek, Nynke

2017-05-01

An estimated 2.6 million stillbirths occur worldwide each year. A standardized classification system setting out possible cause of death and contributing factors is useful to help obtain comparative data across different settings. We undertook a systematic review of stillbirth classification systems to highlight their strengths and weaknesses for practitioners and policymakers. We conducted a systematic search and review of the literature to identify the classification systems used to aggregate information for stillbirth and perinatal deaths. Narrative synthesis was used to compare the range and depth of information required to apply the systems, and the different categories provided for cause of and factors contributing to stillbirth. A total of 118 documents were screened; 31 classification systems were included, of which six were designed specifically for stillbirth, 14 for perinatal death, three systems included neonatal deaths and two included infant deaths. Most (27/31) were developed in and first tested using data obtained from high-income settings. All systems required information from clinical records. One-third of the classification systems (11/31) included information obtained from histology or autopsy. The percentage where cause of death remained unknown ranged from 0.39% using the Nordic-Baltic classification to 46.4% using the Keeling system. Over time, classification systems have become more complex. The success of application is dependent on the availability of detailed clinical information and laboratory investigations. Systems that adopt a layered approach allow for classification of cause of death to a broad as well as to a more detailed level. © 2017 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Towards quantitative classification of folded proteins in terms of elementary functions.

PubMed

Hu, Shuangwei; Krokhotin, Andrei; Niemi, Antti J; Peng, Xubiao

2011-04-01

A comparative classification scheme provides a good basis for several approaches to understand proteins, including prediction of relations between their structure and biological function. But it remains a challenge to combine a classification scheme that describes a protein starting from its well-organized secondary structures and often involves direct human involvement, with an atomary-level physics-based approach where a protein is fundamentally nothing more than an ensemble of mutually interacting carbon, hydrogen, oxygen, and nitrogen atoms. In order to bridge these two complementary approaches to proteins, conceptually novel tools need to be introduced. Here we explain how an approach toward geometric characterization of entire folded proteins can be based on a single explicit elementary function that is familiar from nonlinear physical systems where it is known as the kink soliton. Our approach enables the conversion of hierarchical structural information into a quantitative form that allows for a folded protein to be characterized in terms of a small number of global parameters that are in principle computable from atomary-level considerations. As an example we describe in detail how the native fold of the myoglobin 1M6C emerges from a combination of kink solitons with a very high atomary-level accuracy. We also verify that our approach describes longer loops and loops connecting α helices with β strands, with the same overall accuracy. ©2011 American Physical Society

Coastline complexity: A parameter for functional classification of coastal environments

USGS Publications Warehouse

Bartley, J.D.; Buddemeier, R.W.; Bennett, D.A.

2001-01-01

To understand the role of the world's coastal zone (CZ) in global biogeochemical fluxes (particularly those of carbon, nitrogen, phosphorus, and sediments) we must generalise from a limited number of observations associated with a few well-studied coastal systems to the global scale. Global generalisation must be based on globally available data and on robust techniques for classification and upscaling. These requirements impose severe constraints on the set of variables that can be used to extract information about local CZ functions such as advective and metabolic fluxes, and differences resulting from changes in biotic communities. Coastal complexity (plan-view tortuosity of the coastline) is a potentially useful parameter, since it interacts strongly with both marine and terrestrial forcing functions to determine coastal energy regimes and water residence times, and since 'open' vs. 'sheltered' categories are important components of most coastal habitat classification schemes. This study employs the World Vector Shoreline (WVS) dataset, originally developed at a scale of 1:250 000. Coastline complexity measures are generated using a modification of the Angle Measurement Technique (AMT), in which the basic measurement is the angle between two lines of specified length drawn from a selected point to the closest points of intersection with the coastline. Repetition of these measurements for different lengths at the same point yields a distribution of angles descriptive of the extent and scale of complexity in the vicinity of that point; repetition of the process at different points on the coast provides a basis for comparing both the extent and the characteristic scale of coastline variation along different reaches of the coast. The coast of northwestern Mexico (Baja California and the Gulf of California) was used as a case study for initial development and testing of the method. The characteristic angle distribution plots generated by the AMT analysis were clustered using LOICZVIEW, a high dimensionality clustering routine developed for large-scale coastal classification studies. The results show distinctive differences in coastal environments that have the potential for interpretation in terms of both biotic and hydrogeochemical environments, and that can be related to the resolution limits and uncertainties of the shoreline data used. These objective, quantitative measures of coastal complexity as a function of scale can be further developed and combined with other data sets to provide a key component of functional classification of coastal environments. ?? 2001 Elsevier Science B.V. All rights reserved.

Radiographic readings for asbestosis: misuse of science--validation of the ILO classification.

PubMed

Miller, Albert

2007-01-01

Radiographic readings for pneumoconiosis (both asbestosis and silicosis), even those using the International Labour Office (ILO) Classification, have received widespread negative coverage in the media and strong judicial rebuke. The medical literature over the past 90 years was reviewed for the relationships between radiographic severity (standardized as the ILO profusion score) and indices of exposure to silica or asbestos, tissue burden of silica particles or asbestos fibers, histologic fibrosis, various measurements of pulmonary function and mortality. Evidence from many different disciplines has demonstrated that the ILO profusion score correlates with occupational exposure, dust burden in the lung, histologic fibrosis and, more recently, with physiologic impairment and mortality. The ILO Classification has therefore been validated as a scientific tool. Its fraudulent misuse by "hired-gun" physicians, attorneys and elements of the compensation system to falsify claims of asbestosis and/or silicosis (often in the same claimant) must be condemned. (c) 2006 Wiley-Liss, Inc.

Blends and Nanocomposite Biomaterials for Articular Cartilage Tissue Engineering

PubMed Central

Doulabi, Azadehsadat Hashemi; Mequanint, Kibret; Mohammadi, Hadi

2014-01-01

This review provides a comprehensive assessment on polymer blends and nanocomposite systems for articular cartilage tissue engineering applications. Classification of various types of blends including natural/natural, synthetic/synthetic systems, their combination and nanocomposite biomaterials are studied. Additionally, an inclusive study on their characteristics, cell responses ability to mimic tissue and regenerate damaged articular cartilage with respect to have functionality and composition needed for native tissue, are also provided. PMID:28788131

Multifunctional energy landscape for a DNA G-quadruplex: An evolved molecular switch

NASA Astrophysics Data System (ADS)

Cragnolini, Tristan; Chakraborty, Debayan; Šponer, Jiří; Derreumaux, Philippe; Pasquali, Samuela; Wales, David J.

2017-10-01

We explore the energy landscape for a four-fold telomere repeat, obtaining interconversion pathways between six experimentally characterised G-quadruplex topologies. The results reveal a multi-funnel system, with a variety of intermediate configurations and misfolded states. This organisation is identified with the intrinsically multi-functional nature of the system, suggesting a new paradigm for the classification of such biomolecules and clarifying issues regarding apparently conflicting experimental results.

Effects of short-term active video game play on community adults: under International Classification of Functioning, Disability and Health consideration.

PubMed

Tseng, Wei-Che; Hsieh, Ru-Lan

2013-06-01

The effects of active video game play on healthy individuals remain uncertain. A person's functional health status constitutes a dynamic interaction between components identified in the International Classification of Functioning, Disability, and Health (ICF). The aim of this study was to investigate the short-term effects of active video game play on community adults using the ICF. Sixty community adults with an average age of 59.3 years and without physical disabilities were recruited. Over 2 weeks, each adult participated in six sessions of active video game play lasting 20 minutes each. Participants were assessed before and after the intervention. Variables were collected using sources related to the ICF components, including the Hospital Anxiety and Depression Scale, Multidimensional Fatigue Inventory, Biodex Stability System, chair- rising time, Frenchay Activity Index, Rivermead Mobility Index, Chronic Pain Grade Questionnaire, Work Ability Index, and World Health Organization Quality of Life-Brief Version. Compared to baseline data, significantly reduced risk of a fall measured by Biodex Stability System and improvements in disability scores measured by the Chronic Pain Grade Questionnaire were noted. There was no significant change in the other variables measured. Short-term, active video game play reduces fall risks and ameliorates disabilities in community adults.

[Complex surgical procedures in orthopedics and trauma surgery. A contribution to the proposal procedure for the DRG system in 2009].

PubMed

Flohé, S; Nabring, J; Luetkes, P; Nast-Kolb, D; Windolf, J

2008-10-01

Since the DRG system was introduced in 2003/2004 the system for remuneration has been continually modified in conjunction with input from specialized medical associations. As part of this development of the payment system, the criteria for classification of a diagnosis-related group were further expanded and new functions were added. This contribution addresses the importance of the complex surgical procedures as criteria for subdivision of the DRG case-based lump sums in orthopedics and trauma surgery.

Reliability of the Dutch-language version of the Communication Function Classification System and its association with language comprehension and method of communication.

PubMed

Vander Zwart, Karlijn E; Geytenbeek, Joke J; de Kleijn, Maaike; Oostrom, Kim J; Gorter, Jan Willem; Hidecker, Mary Jo Cooley; Vermeulen, R Jeroen

2016-02-01

The aims of this study were to determine the intra- and interrater reliability of the Dutch-language version of the Communication Function Classification System (CFCS-NL) and to investigate the association between the CFCS level and (1) spoken language comprehension and (2) preferred method of communication in children with cerebral palsy (CP). Participants were 93 children with CP (50 males, 43 females; mean age 7y, SD 2y 6mo, range 2y 9mo-12y 10mo; unilateral spastic [n=22], bilateral spastic [n=51], dyskinetic [n=15], ataxic [n=3], not specified [n=2]; Gross Motor Function Classification System level I [n=16], II [n=14], III, [n=7], IV [n=24], V [n=31], unknown [n=1]), recruited from rehabilitation centres throughout the Netherlands. Because some centres only contributed to part of the study, different numbers of participants are presented for different aspects of the study. Parents and speech and language therapists (SLTs) classified the communication level using the CFCS. Kappa was used to determine the intra- and interrater reliability. Spearman's correlation coefficient was used to determine the association between CFCS level and spoken language comprehension, and Fisher's exact test was used to examine the association between the CFCS level and method of communication. Interrater reliability of the CFCS-NL between parents and SLTs was fair (r=0.54), between SLTs good (r=0.78), and the intrarater (SLT) reliability very good (r=0.85). The association between the CFCS and spoken language comprehension was strong for SLTs (r=0.63) and moderate for parents (r=0.51). There was a statistically significant difference between the CFCS level and the preferred method of communication of the child (p<0.01). Also, CFCS level classification showed a statistically significant difference between parents and SLTs (p<0.01). These data suggest that the CFCS-NL is a valid and reliable clinical tool to classify everyday communication in children with CP. Preferably, professionals should classify the child's CFCS level in collaboration with the parents to acquire the most comprehensive information about the everyday communication of the child in various situations both with familiar and with unfamiliar partners. © 2015 Mac Keith Press.

Real-time and wearable functional electrical stimulation system for volitional hand motor function control using the electromyography bridge method

PubMed Central

Wang, Hai-peng; Bi, Zheng-yang; Zhou, Yang; Zhou, Yu-xuan; Wang, Zhi-gong; Lv, Xiao-ying

2017-01-01

Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy. A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method. Through a series of novel design concepts, including the integration of a detecting circuit and an analog-to-digital converter, a miniaturized functional electrical stimulation circuit technique, a low-power super-regeneration chip for wireless receiving, and two wearable armbands, a prototype system has been established with reduced size, power, and overall cost. Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects, the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy. Test results showed that wrist flexion/extension, hand grasp, and finger extension could be reproduced with high accuracy and low latency. This system can build a bridge of information transmission between healthy limbs and paralyzed limbs, effectively improve voluntary participation of hemiplegic patients, and elevate efficiency of rehabilitation training. PMID:28250759

Single-trial EEG RSVP classification using convolutional neural networks

NASA Astrophysics Data System (ADS)

Shamwell, Jared; Lee, Hyungtae; Kwon, Heesung; Marathe, Amar R.; Lawhern, Vernon; Nothwang, William

2016-05-01

Traditionally, Brain-Computer Interfaces (BCI) have been explored as a means to return function to paralyzed or otherwise debilitated individuals. An emerging use for BCIs is in human-autonomy sensor fusion where physiological data from healthy subjects is combined with machine-generated information to enhance the capabilities of artificial systems. While human-autonomy fusion of physiological data and computer vision have been shown to improve classification during visual search tasks, to date these approaches have relied on separately trained classification models for each modality. We aim to improve human-autonomy classification performance by developing a single framework that builds codependent models of human electroencephalograph (EEG) and image data to generate fused target estimates. As a first step, we developed a novel convolutional neural network (CNN) architecture and applied it to EEG recordings of subjects classifying target and non-target image presentations during a rapid serial visual presentation (RSVP) image triage task. The low signal-to-noise ratio (SNR) of EEG inherently limits the accuracy of single-trial classification and when combined with the high dimensionality of EEG recordings, extremely large training sets are needed to prevent overfitting and achieve accurate classification from raw EEG data. This paper explores a new deep CNN architecture for generalized multi-class, single-trial EEG classification across subjects. We compare classification performance from the generalized CNN architecture trained across all subjects to the individualized XDAWN, HDCA, and CSP neural classifiers which are trained and tested on single subjects. Preliminary results show that our CNN meets and slightly exceeds the performance of the other classifiers despite being trained across subjects.

Which method of posttraumatic stress disorder classification best predicts psychosocial function in children with traumatic brain injury?

PubMed

Iselin, Greg; Le Brocque, Robyne; Kenardy, Justin; Anderson, Vicki; McKinlay, Lynne

2010-10-01

Controversy surrounds the classification of posttraumatic stress disorder (PTSD), particularly in children and adolescents with traumatic brain injury (TBI). In these populations, it is difficult to differentiate TBI-related organic memory loss from dissociative amnesia. Several alternative PTSD classification algorithms have been proposed for use with children. This paper investigates DSM-IV-TR and alternative PTSD classification algorithms, including and excluding the dissociative amnesia item, in terms of their ability to predict psychosocial function following pediatric TBI. A sample of 184 children aged 6-14 years were recruited following emergency department presentation and/or hospital admission for TBI. PTSD was assessed via semi-structured clinical interview (CAPS-CA) with the child at 3 months post-injury. Psychosocial function was assessed using the parent report CHQ-PF50. Two alternative classification algorithms, the PTSD-AA and 2 of 3 algorithms, reached statistical significance. While the inclusion of the dissociative amnesia item increased prevalence rates across algorithms, it generally resulted in weaker associations with psychosocial function. The PTSD-AA algorithm appears to have the strongest association with psychosocial function following TBI in children and adolescents. Removing the dissociative amnesia item from the diagnostic algorithm generally results in improved validity. Copyright 2010 Elsevier Ltd. All rights reserved.

A comparison of chemoembolization endpoints using angiographic versus transcatheter intraarterial perfusion/MR imaging monitoring.

PubMed

Lewandowski, Robert J; Wang, Dingxin; Gehl, James; Atassi, Bassel; Ryu, Robert K; Sato, Kent; Nemcek, Albert A; Miller, Frank H; Mulcahy, Mary F; Kulik, Laura; Larson, Andrew C; Salem, Riad; Omary, Reed A

2007-10-01

Transcatheter arterial chemoembolization (TACE) is an established treatment for unresectable liver cancer. This study was conducted to test the hypothesis that angiographic endpoints during TACE are measurable and reproducible by comparing subjective angiographic versus objective magnetic resonance (MR) endpoints of TACE. The study included 12 consecutive patients who presented for TACE for surgically unresectable HCC or progressive hepatic metastases despite chemotherapy. All procedures were performed with a dedicated imaging system. Angiographic series before and after TACE were reviewed independently by three board-certified interventional radiologists. A subjective angiographic chemoembolization endpoint (SACE) classification scheme, modified from an established angiographic grading system in the cardiology literature, was designed to assist in reproducibly classifying angiographic endpoints. Reproducibility in SACE classification level was compared among operators, and MR imaging perfusion reduction was compared with SACE levels for each observer. Twelve patients successfully underwent 15 separate TACE sessions. SACE levels ranged from I through IV. There was moderate agreement in SACE classification (kappa = 0.46 +/- 0.12). There was no correlation between SACE level and MR perfusion reduction (r = 0.16 for one operator and 0.02 for the other two). Angiographic endpoints during TACE vary widely, have moderate reproducibility among operators, and do not correlate with functional MR imaging perfusion endpoints. Future research should aim to determine ideal angiographic and functional MR imaging endpoints for TACE according to outcome measures such as imaging response, pathologic response, and survival.

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation.

Online adaptive decision trees: pattern classification and function approximation.

PubMed

Basak, Jayanta

2006-09-01

Recently we have shown that decision trees can be trained in the online adaptive (OADT) mode (Basak, 2004), leading to better generalization score. OADTs were bottlenecked by the fact that they are able to handle only two-class classification tasks with a given structure. In this article, we provide an architecture based on OADT, ExOADT, which can handle multiclass classification tasks and is able to perform function approximation. ExOADT is structurally similar to OADT extended with a regression layer. We also show that ExOADT is capable not only of adapting the local decision hyperplanes in the nonterminal nodes but also has the potential of smoothly changing the structure of the tree depending on the data samples. We provide the learning rules based on steepest gradient descent for the new model ExOADT. Experimentally we demonstrate the effectiveness of ExOADT in the pattern classification and function approximation tasks. Finally, we briefly discuss the relationship of ExOADT with other classification models.

Image Classification Workflow Using Machine Learning Methods

NASA Astrophysics Data System (ADS)

Christoffersen, M. S.; Roser, M.; Valadez-Vergara, R.; Fernández-Vega, J. A.; Pierce, S. A.; Arora, R.

2016-12-01

Recent increases in the availability and quality of remote sensing datasets have fueled an increasing number of scientifically significant discoveries based on land use classification and land use change analysis. However, much of the software made to work with remote sensing data products, specifically multispectral images, is commercial and often prohibitively expensive. The free to use solutions that are currently available come bundled up as small parts of much larger programs that are very susceptible to bugs and difficult to install and configure. What is needed is a compact, easy to use set of tools to perform land use analysis on multispectral images. To address this need, we have developed software using the Python programming language with the sole function of land use classification and land use change analysis. We chose Python to develop our software because it is relatively readable, has a large body of relevant third party libraries such as GDAL and Spectral Python, and is free to install and use on Windows, Linux, and Macintosh operating systems. In order to test our classification software, we performed a K-means unsupervised classification, Gaussian Maximum Likelihood supervised classification, and a Mahalanobis Distance based supervised classification. The images used for testing were three Landsat rasters of Austin, Texas with a spatial resolution of 60 meters for the years of 1984 and 1999, and 30 meters for the year 2015. The testing dataset was easily downloaded using the Earth Explorer application produced by the USGS. The software should be able to perform classification based on any set of multispectral rasters with little to no modification. Our software makes the ease of land use classification using commercial software available without an expensive license.

Tools and Functions of Reconfigurable Colloidal Assembly.

PubMed

Solomon, Michael J

2018-02-19

We review work in reconfigurable colloidal assembly, a field in which rapid, back-and-forth transitions between the equilibrium states of colloidal self-assembly are accomplished by dynamic manipulation of the size, shape, and interaction potential of colloids, as well as the magnitude and direction of the fields applied to them. It is distinguished from the study of colloidal phase transitions by the centrality of thermodynamic variables and colloidal properties that are time switchable; by the applicability of these changes to generate transitions in assembled colloids that may be spatially localized; and by its incorporation of the effects of generalized potentials due to, for example, applied electric and magnetic fields. By drawing upon current progress in the field, we propose a matrix classification of reconfigurable colloidal systems based on the tool used and function performed by reconfiguration. The classification distinguishes between the multiple means by which reconfigurable assembly can be accomplished (i.e., the tools of reconfiguration) and the different kinds of structural transitions that can be achieved by it (i.e., the functions of reconfiguration). In the first case, the tools of reconfiguration can be broadly classed as (i) those that control the colloidal contribution to the system entropy-as through volumetric and/or shape changes of the particles; (ii) those that control the internal energy of the colloids-as through manipulation of colloidal interaction potentials; and (iii) those that control the spatially resolved potential energy that is imposed on the colloids-as through the introduction of field-induced phoretic mechanisms that yield colloidal displacement and accumulation. In the second case, the functions of reconfiguration include reversible: (i) transformation between different phases-including fluid, cluster, gel, and crystal structures; (ii) manipulation of the spacing between colloids in crystals and clusters; and (iii) translation, rotation, or shape-change of finite-size objects self-assembled from colloids. With this classification in hand, we correlate the current limits on the spatiotemporal scales for reconfigurable colloidal assembly and identify a set of future research challenges.

Surgical management of morbidity due to lymphatic filariasis: the usefulness of a standardized international clinical classification of hydroceles.

PubMed

Capuano, G P; Capuano, C

2012-03-01

The objective of this work is to evaluate the usefulness of a standardized clinical classification of hydroceles in lymphatic filariasis endemic countries to guide their surgical management. 64 patients with hydroceles were operated in 2009-2010, in Level II hospitals (WHO classification), during two visits to Fiji, by the same mobile surgical team. The number of hydroceles treated was 83. We developed and evaluated a much needed clinical classification of hydroceles based on four criteria: Type (uni/bilateral); Side (left/right); Stage of enlargement of the scrotum rated from I to VI; Grade of burial of the penis rated from 0 to 4. It lead to the conclusion that 1) A Stage I or II hydrocele, associated with Grade 0 or 1 penis burial could be considered a "Simple Hydrocele". The surgical treatment is simple with no anticipated early complication. WHO Level II of health care structure seems adapted. 2) A Stage III or IV hydrocele associated with Grade 2, 3 or 4 penis burial could be considered a "Complicated Hydrocele". The operation is longer, more complicated and the possibility of occurrence of complications seems greater. A level III health care facility would be more adapted under the normal functioning of the health system. We conclude that a standardized clinical classification of hydroceles based on the Stage of enlargement of the scrotum and the Grade of burial of the penis appears to be a useful tool to guide the decision about the level of care and the surgical technique required. We use the same classification for penoscrotal lymphoedema. A decision tree is presented for the management of hydroceles in lymphatic filariasis endemic countries which could usefully complement the "Algorithm for management of scrotal swelling" proposed by WHO in 2002. An international classification system of hydroceles would also allow standardization and facilitate study design and comparisons of their results.

Spectrally based mapping of riverbed composition

USGS Publications Warehouse

Legleiter, Carl; Stegman, Tobin K.; Overstreet, Brandon T.

2016-01-01

Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader range of fluvial environments is needed to substantiate our initial results, this case study suggests that bed composition in shallow, clear-flowing rivers potentially could be mapped remotely.

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

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

Young, M; Craft, D

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchicalmore » clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve cancer classification using biological pathways. Patients are classified with greater specificity and physiological relevance as compared to current gene-specific approaches. Focus now moves to utilizing PICS for pan-cancer patient-specific treatment response prediction.« less

Bands selection and classification of hyperspectral images based on hybrid kernels SVM by evolutionary algorithm

NASA Astrophysics Data System (ADS)

Hu, Yan-Yan; Li, Dong-Sheng

2016-01-01

The hyperspectral images(HSI) consist of many closely spaced bands carrying the most object information. While due to its high dimensionality and high volume nature, it is hard to get satisfactory classification performance. In order to reduce HSI data dimensionality preparation for high classification accuracy, it is proposed to combine a band selection method of artificial immune systems (AIS) with a hybrid kernels support vector machine (SVM-HK) algorithm. In fact, after comparing different kernels for hyperspectral analysis, the approach mixed radial basis function kernel (RBF-K) with sigmoid kernel (Sig-K) and applied the optimized hybrid kernels in SVM classifiers. Then the SVM-HK algorithm used to induce the bands selection of an improved version of AIS. The AIS was composed of clonal selection and elite antibody mutation, including evaluation process with optional index factor (OIF). Experimental classification performance was on a San Diego Naval Base acquired by AVIRIS, the HRS dataset shows that the method is able to efficiently achieve bands redundancy removal while outperforming the traditional SVM classifier.

HVM die yield improvement as a function of DRSEM ADC

NASA Astrophysics Data System (ADS)

Maheshwary, Sonu; Haas, Terry; McGarvey, Steve

2010-03-01

Given the current manufacturing technology roadmap and the competitiveness of the global semiconductor manufacturing environment in conjunction with the semiconductor manufacturing market dynamics, the market place continues to demand a reduced die manufacturing cost. This continuous pressure on lowering die cost in turn drives an aggressive yield learning curve, a key component of which is defect reduction of manufacturing induced anomalies. In order to meet and even exceed line and die yield targets there is a need to revamp defect classification strategies and place a greater emphasize on increasing the accuracy and purity of the Defect Review Scanning Electron Microscope (DRSEM) Automated Defect Classification (ADC) results while placing less emphasis on the ADC results of patterned/un-patterned wafer inspection systems. The increased emphasis on DRSEM ADC results allows for a high degree of automation and consistency in the classification data and eliminates variance induced by the manufacturing staff. This paper examines the use of SEM based Auto Defect Classification in a high volume manufacturing environment as a key driver in the reduction of defect limited yields.

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.

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces.

PubMed

Micera, Silvestro; Rossini, Paolo M; Rigosa, Jacopo; Citi, Luca; Carpaneto, Jacopo; Raspopovic, Stanisa; Tombini, Mario; Cipriani, Christian; Assenza, Giovanni; Carrozza, Maria C; Hoffmann, Klaus-Peter; Yoshida, Ken; Navarro, Xavier; Dario, Paolo

2011-09-05

The restoration of complex hand functions by creating a novel bidirectional link between the nervous system and a dexterous hand prosthesis is currently pursued by several research groups. This connection must be fast, intuitive, with a high success rate and quite natural to allow an effective bidirectional flow of information between the user's nervous system and the smart artificial device. This goal can be achieved with several approaches and among them, the use of implantable interfaces connected with the peripheral nervous system, namely intrafascicular electrodes, is considered particularly interesting. Thin-film longitudinal intra-fascicular electrodes were implanted in the median and ulnar nerves of an amputee's stump during a four-week trial. The possibility of decoding motor commands suitable to control a dexterous hand prosthesis was investigated for the first time in this research field by implementing a spike sorting and classification algorithm. The results showed that motor information (e.g., grip types and single finger movements) could be extracted with classification accuracy around 85% (for three classes plus rest) and that the user could improve his ability to govern motor commands over time as shown by the improved discrimination ability of our classification algorithm. These results open up new and promising possibilities for the development of a neuro-controlled hand prosthesis.

Computed aided system for separation and classification of the abnormal erythrocytes in human blood

NASA Astrophysics Data System (ADS)

Wąsowicz, Michał; Grochowski, Michał; Kulka, Marek; Mikołajczyk, Agnieszka; Ficek, Mateusz; Karpieńko, Katarzyna; Cićkiewicz, Maciej

2017-12-01

The human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified diamonds and oxidation modified. The blood was put under an impact of two diamond concentrations: 20μl and 100μl. The amount of abnormal cells increased with time. The percentage of echinocytes as a result of interaction with nanodiamonds in various time intervals for individual specimens was scarce. The impact of the two diamond types had no clinical importance on red blood cells. It is supposed that as a result of longlasting exposure a dehydratation of red cells takes place, because of the function of the cells. The analysis of an influence of nanodiamond particles on blood elements was supported by computer system designed for automatic counting and classification of the Red Blood Cells (RBC). The system utilizes advanced image processing methods for RBCs separation and counting and Eigenfaces method coupled with the neural networks for RBCs classification into normal and abnormal cells purposes.

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect

PubMed Central

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs. PMID:24550865

Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

PubMed

Folia, Vasiliki; Petersson, Karl Magnus

2014-01-01

In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

Neighborhood graph and learning discriminative distance functions for clinical decision support.

PubMed

Tsymbal, Alexey; Zhou, Shaohua Kevin; Huber, Martin

2009-01-01

There are two essential reasons for the slow progress in the acceptance of clinical case retrieval and similarity search-based decision support systems; the especial complexity of clinical data making it difficult to define a meaningful and effective distance function on them and the lack of transparency and explanation ability in many existing clinical case retrieval decision support systems. In this paper, we try to address these two problems by introducing a novel technique for visualizing inter-patient similarity based on a node-link representation with neighborhood graphs and by considering two techniques for learning discriminative distance function that help to combine the power of strong "black box" learners with the transparency of case retrieval and nearest neighbor classification.

Soil Taxonomy and land evaluation for forest establishment

Treesearch

Haruyoshi Ikawa

1992-01-01

Soil Taxonomy, the United States system of soil classification, can be used for land evaluation for selected purposes. One use is forest establishment in the tropics, and the soil family category is especially functional for this purpose. The soil family is a bionomial name with descriptions usually of soil texture, mineralogy, and soil temperature classes. If the...

Qualitative Differences Among Gender-Stereotyped Toys: Implications for Cognitive and Social Development in Girls and Boys.

ERIC Educational Resources Information Center

Miller, Cynthia L.

1987-01-01

Evaluates a system of toy classification developed to improve the assessment of gender differences in cognitive and social development. One hundred adults rated 50 children's toys on 122 "functional" dimensions. Results showed that these toys could be reliably described according to multidimensional similarities, and confirmed that toys considered…

Measurement of Habitual Physical Activity Performance in Adolescents with Cerebral Palsy: A Systematic Review

ERIC Educational Resources Information Center

Clanchy, Kelly M.; Tweedy, Sean M.; Boyd, Roslyn

2011-01-01

Aim: This systematic review compares the validity, reliability, and clinical use of habitual physical activity (HPA) performance measures in adolescents with cerebral palsy (CP). Method: Measures of HPA across Gross Motor Function Classification System (GMFCS) levels I-V for adolescents (10-18y) with CP were included if at least 60% of items…

Narrowing Historical Uncertainty: Probabilistic Classification of Ambiguously Identified Tree Species in Historical Forest Survey Data

Treesearch

David J. Mladenoff; Sally E. Dahir; Eric V. Nordheim; Lisa A. Schulte; Glenn G. Gutenspergen

2002-01-01

Historical data have increasingly become appreciated for insight into the past conditions of ecosystems, Uses of such data include assessing the extent of ecosystem change; deriving ecological baselines for management, restoration, and modeling; and assessing the importance of past conditions on the composition and function of current systems. One historical data set...

A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

PubMed

Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

2018-01-01

The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

EEG classification of emotions using emotion-specific brain functional network.

PubMed

Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

2015-08-01

The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.