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Sample records for pattern classification system

  1. An intelligent temporal pattern classification system using fuzzy ...

    Indian Academy of Sciences (India)

    In this paper, we propose a new pattern classification system by combining Temporal features with Fuzzy Min–Max (TFMM) neural network based classifier for effective decision support in medical diagnosis. Moreover, a Particle Swarm Optimization (PSO) algorithm based rule extractor is also proposed in this work for ...

  2. Formalization of the classification pattern: survey of classification modeling in information systems engineering.

    Science.gov (United States)

    Partridge, Chris; de Cesare, Sergio; Mitchell, Andrew; Odell, James

    2018-01-01

    Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the "one and the many." Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor's work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus

  3. Classification of time series patterns from complex dynamic systems

    Energy Technology Data Exchange (ETDEWEB)

    Schryver, J.C.; Rao, N.

    1998-07-01

    An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately, the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.

  4. Pattern classification

    CERN Document Server

    Duda, Richard O; Stork, David G

    2001-01-01

    The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

  5. An ontology-based intrusion patterns classification system | Shonubi ...

    African Journals Online (AJOL)

    Studies have shown that computer intrusions have been on the increase in recent times. Many techniques and patterns are being used by intruders to gain access to data on host computer networks. In this work, intrusion patterns were identified and classified and inherent knowledge were represented using an ontology of ...

  6. Classifications of Patterned Hair Loss: A Review.

    Science.gov (United States)

    Gupta, Mrinal; Mysore, Venkataram

    2016-01-01

    Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

  7. Acromioclavicular joint dislocations: radiological correlation between Rockwood classification system and injury patterns in human cadaver species.

    Science.gov (United States)

    Eschler, Anica; Rösler, Klaus; Rotter, Robert; Gradl, Georg; Mittlmeier, Thomas; Gierer, Philip

    2014-09-01

    The classification system of Rockwood and Young is a commonly used classification for acromioclavicular joint separations subdividing types I-VI. This classification hypothesizes specific lesions to anatomical structures (acromioclavicular and coracoclavicular ligaments, capsule, attached muscles) leading to the injury. In recent literature, our understanding for anatomical correlates leading to the radiological-based Rockwood classification is questioned. The goal of this experimental-based investigation was to approve the correlation between the anatomical injury pattern and the Rockwood classification. In four human cadavers (seven shoulders), the acromioclavicular and coracoclavicular ligaments were transected stepwise. Radiological correlates were recorded (Zanca view) with 15-kg longitudinal tension applied at the wrist. The resulting acromio- and coracoclavicular distances were measured. Radiographs after acromioclavicular ligament transection showed joint space enlargement (8.6 ± 0.3 vs. 3.1 ± 0.5 mm, p acromioclavicular joint space width increased to 16.7 ± 2.7 vs. 8.6 ± 0.3 mm, p acromioclavicular joint lesions higher than Rockwood type I and II. The clinical consequence for reconstruction of low-grade injuries might be a solely surgical approach for the acromioclavicular ligaments or conservative treatment. High-grade injuries were always based on additional structural damage to the coracoclavicular ligaments. Rockwood type V lesions occurred while muscle attachments were intact.

  8. Comparison of an automated classification system with an empirical classification of circulation patterns over the Pannonian basin, Central Europe

    Science.gov (United States)

    Maheras, Panagiotis; Tolika, Konstantia; Tegoulias, Ioannis; Anagnostopoulou, Christina; Szpirosz, Klicász; Károssy, Csaba; Makra, László

    2018-04-01

    The aim of the study is to compare the performance of the two classification methods, based on the atmospheric circulation types over the Pannonian basin in Central Europe. Moreover, relationships including seasonal occurrences and correlation coefficients, as well as comparative diagrams of the seasonal occurrences of the circulation types of the two classification systems are presented. When comparing of the automated (objective) and empirical (subjective) classification methods, it was found that the frequency of the empirical anticyclonic (cyclonic) types is much higher (lower) than that of the automated anticyclonic (cyclonic) types both on an annual and seasonal basis. The highest and statistically significant correlations between the circulation types of the two classification systems, as well as those between the cumulated seasonal anticyclonic and cyclonic types occur in winter for both classifications, since the weather-influencing effect of the atmospheric circulation in this season is the most prevalent. Precipitation amounts in Budapest display a decreasing trend in accordance with the decrease in the occurrence of the automated cyclonic types. In contrast, the occurrence of the empirical cyclonic types displays an increasing trend. There occur types in a given classification that are usually accompanied by high ratios of certain types in the other classification.

  9. Comparison of Pattern Classification Methods in Crossarm Reuse Judgement System Based on Rust Images

    Science.gov (United States)

    Yamana, Michiko; Murata, Hiroshi; Onoda, Takashi; Ohashi, Tohru; Kato, Seiji

    Japanese electric power companies currently utilize existing equipments completely and maintain facilities effectively. Human experts presently judge various hardwares whether they are be reusable or not to utilize equipments completely. Especially, this paper considers about crossarm reuse judgement. This judgement is based on rust, which attaches on crossarms, by human experts. However, this judgement depends on human expertise and it is difficult to keep constant judgement accuracy. Electric power companies want to take constant and good judgement accuracy. Therefore, we develop a crossarm reuse judgement system based on rust images using machine learning techniques. The system consists of commercial microscope and standard note PC to keep the cost. And we estimate the judgement accuracy of various pattern classification methods without the special image processing such as extracting features. The results show that support vector machine is the most suitable method for this judgement system.

  10. Classifications of patterned hair loss: a review

    Directory of Open Access Journals (Sweden)

    Mrinal Gupta

    2016-01-01

    Full Text Available Patterned hair loss is the most common cause of hair loss seen in both the sexes after puberty. Numerous classification systems have been proposed by various researchers for grading purposes. These systems vary from the simpler systems based on recession of the hairline to the more advanced multifactorial systems based on the morphological and dynamic parameters that affect the scalp and the hair itself. Most of these preexisting systems have certain limitations. Currently, the Hamilton-Norwood classification system for males and the Ludwig system for females are most commonly used to describe patterns of hair loss. In this article, we review the various classification systems for patterned hair loss in both the sexes. Relevant articles were identified through searches of MEDLINE and EMBASE. Search terms included but were not limited to androgenic alopecia classification, patterned hair loss classification, male pattern baldness classification, and female pattern hair loss classification. Further publications were identified from the reference lists of the reviewed articles.

  11. Pattern Classification in Kampo Medicine

    Directory of Open Access Journals (Sweden)

    S. Yakubo

    2014-01-01

    Full Text Available Pattern classification is very unique in traditional medicine. Kampo medical patterns have transformed over time during Japan’s history. In the 17th to 18th centuries, Japanese doctors advocated elimination of the Ming medical theory and followed the basic concepts put forth by Shang Han Lun and Jin Gui Yao Lue in the later Han dynasty (25–220 AD. The physician Todo Yoshimasu (1702–1773 emphasized that an appropriate treatment could be administered if a set of patterns could be identified. This principle is still referred to as “matching of pattern and formula” and is the basic concept underlying Kampo medicine today. In 1868, the Meiji restoration occurred, and the new government changed its policies to follow that of the European countries, adopting only Western medicine. Physicians trained in Western medicine played an important role in the revival of Kampo medicine, modernizing Kampo patterns to avoid confusion with Western biomedical terminology. In order to understand the Japanese version of traditional disorders and patterns, background information on the history of Kampo and its role in the current health care system in Japan is important. In this paper we overviewed the formation of Kampo patterns.

  12. Quantum computing for pattern classification

    OpenAIRE

    Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco

    2014-01-01

    It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning using the example of pattern classification. We introduce a quantum pattern classification algorithm that draws on Trugenberger's proposal for measuring the Hamming di...

  13. Computational Intelligence Paradigms in Advanced Pattern Classification

    CERN Document Server

    Jain, Lakhmi

    2012-01-01

    This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

  14. Pattern recognition and classification an introduction

    CERN Document Server

    Dougherty, Geoff

    2012-01-01

    The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

  15. Support Vector Machines for Pattern Classification

    CERN Document Server

    Abe, Shigeo

    2010-01-01

    A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empir

  16. Pattern Classification with Memristive Crossbar Circuits

    Science.gov (United States)

    2016-03-31

    Pattern Classification with Memristive Crossbar Circuits Dmitri B. Strukov Department of Electrical and Computer Engineering Department UC Santa...pattern classification ; deep learning; convolutional neural network networks. Introduction Deep-learning convolutional neural networks (DLCNN), which...the best classification performances on a variety of benchmark tasks [1]. The major challenge in building fast and energy- efficient networks of this

  17. Neuromuscular disease classification system

    Science.gov (United States)

    Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

    2013-06-01

    Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

  18. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  19. Sow-activity classification from acceleration patterns

    DEFF Research Database (Denmark)

    Escalante, Hugo Jair; Rodriguez, Sara V.; Cordero, Jorge

    2013-01-01

    sow-activity classification can be approached with standard machine learning methods for pattern classification. Individual predictions for elements of times series of arbitrary length are combined to classify it as a whole. An extensive comparison of representative learning algorithms, including......This paper describes a supervised learning approach to sow-activity classification from accelerometer measurements. In the proposed methodology, pairs of accelerometer measurements and activity types are considered as labeled instances of a usual supervised classification task. Under this scenario...... neural networks, support vector machines, and ensemble methods, is presented. Experimental results are reported using a data set for sow-activity classification collected in a real production herd. The data set, which has been widely used in related works, includes measurements from active (Feeding...

  20. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  1. Casemix classification systems.

    Science.gov (United States)

    Fetter, R B

    1999-01-01

    The idea of using casemix classification to manage hospital services is not new, but has been limited by available technology. It was not until after the introduction of Medicare in the United States in 1965 that serious attempts were made to measure hospital production in order to contain spiralling costs. This resulted in a system of casemix classification known as diagnosis related groups (DRGs). This paper traces the development of DRGs and their evolution from the initial version to the All Patient Refined DRGs developed in 1991.

  2. Indigenous systems of forest classification: understanding land use patterns and the role of NTFPs in shifting cultivators' subsistence economies.

    Science.gov (United States)

    Delang, Claudio O

    2006-04-01

    This article discusses the system of classification of forest types used by the Pwo Karen in Thung Yai Naresuan Wildlife Sanctuary in western Thailand and the role of nontimber forest products (NTFPs), focusing on wild food plants, in Karen livelihoods. The article argues that the Pwo Karen have two methods of forest classification, closely related to their swidden farming practices. The first is used for forest land that has been, or can be, swiddened, and classifies forest types according to growth conditions. The second system is used for land that is not suitable for cultivation and looks at soil properties and slope. The article estimates the relative importance of each forest type in what concerns the collection of wild food plants. A total of 134 wild food plant species were recorded in December 2004. They account for some 80-90% of the amount of edible plants consumed by the Pwo Karen, and have a base value of Baht 11,505 per year, comparable to the cash incomes of many households. The article argues that the Pwo Karen reliance on NTFPs has influenced their land-use and forest management practices. However, by restricting the length of the fallow period, the Thai government has caused ecological changes that are challenging the ability of the Karen to remain subsistence oriented. By ignoring shifting cultivators' dependence on such products, the involvement of governments in forest management, especially through restrictions imposed on swidden farming practices, is likely to have a considerable impact on the livelihood strategies of these communities.

  3. An analysis of correlation between occlusion classification and skeletal pattern

    International Nuclear Information System (INIS)

    Lu Xinhua; Cai Bin; Wang Dawei; Wu Liping

    2003-01-01

    Objective: To study the correlation between dental relationship and skeletal pattern of individuals. Methods: 194 cases were selected and classified by angle classification, incisor relationship and skeletal pattern respectively. The correlation of angle classification and incisor relationship to skeletal pattern was analyzed with SPSS 10.0. Results: The values of correlation index (Kappa) were 0.379 and 0.494 respectively. Conclusion: The incisor relationship is more consistent with skeletal pattern than angle classification

  4. A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications

    Directory of Open Access Journals (Sweden)

    Jaime Vitola

    2017-02-01

    Full Text Available Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM system based on the use of a piezoelectric (PZT active system. The SHM system includes: (i the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii data organization; (iii advanced signal processing techniques to define the feature vectors; and finally; (iv the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed.

  5. Supervised Learning for Visual Pattern Classification

    Science.gov (United States)

    Zheng, Nanning; Xue, Jianru

    This chapter presents an overview of the topics and major ideas of supervised learning for visual pattern classification. Two prevalent algorithms, i.e., the support vector machine (SVM) and the boosting algorithm, are briefly introduced. SVMs and boosting algorithms are two hot topics of recent research in supervised learning. SVMs improve the generalization of the learning machine by implementing the rule of structural risk minimization (SRM). It exhibits good generalization even when little training data are available for machine training. The boosting algorithm can boost a weak classifier to a strong classifier by means of the so-called classifier combination. This algorithm provides a general way for producing a classifier with high generalization capability from a great number of weak classifiers.

  6. Neuroimaging classification of progression patterns in glioblastoma: a systematic review.

    Science.gov (United States)

    Piper, Rory J; Senthil, Keerthi K; Yan, Jiun-Lin; Price, Stephen J

    2018-03-30

    Our primary objective was to report the current neuroimaging classification systems of spatial patterns of progression in glioblastoma. In addition, we aimed to report the terminology used to describe 'progression' and to assess the compliance with the Response Assessment in Neuro-Oncology (RANO) Criteria. We conducted a systematic review to identify all neuroimaging studies of glioblastoma that have employed a categorical classification system of spatial progression patterns. Our review was registered with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) registry. From the included 157 results, we identified 129 studies that used labels of spatial progression patterns that were not based on radiation volumes (Group 1) and 50 studies that used labels that were based on radiation volumes (Group 2). In Group 1, we found 113 individual labels and the most frequent were: local/localised (58%), distant/distal (51%), diffuse (20%), multifocal (15%) and subependymal/subventricular zone (15%). We identified 13 different labels used to refer to 'progression', of which the most frequent were 'recurrence' (99%) and 'progression' (92%). We identified that 37% (n = 33/90) of the studies published following the release of the RANO classification were adherent compliant with the RANO criteria. Our review reports significant heterogeneity in the published systems used to classify glioblastoma spatial progression patterns. Standardization of terminology and classification systems used in studying progression would increase the efficiency of our research in our attempts to more successfully treat glioblastoma.

  7. Automatic classification of thermal patterns in diabetic foot based on morphological pattern spectrum

    Science.gov (United States)

    Hernandez-Contreras, D.; Peregrina-Barreto, H.; Rangel-Magdaleno, J.; Ramirez-Cortes, J.; Renero-Carrillo, F.

    2015-11-01

    This paper presents a novel approach to characterize and identify patterns of temperature in thermographic images of the human foot plant in support of early diagnosis and follow-up of diabetic patients. Composed feature vectors based on 3D morphological pattern spectrum (pecstrum) and relative position, allow the system to quantitatively characterize and discriminate non-diabetic (control) and diabetic (DM) groups. Non-linear classification using neural networks is used for that purpose. A classification rate of 94.33% in average was obtained with the composed feature extraction process proposed in this paper. Performance evaluation and obtained results are presented.

  8. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three...... readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  9. Bosniak Classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens

    2014-01-01

    Background: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management....... Purpose: To investigate the inter- and intra-observer agreement among experienced uroradiologists when categorizing complex renal cysts according to the Bosniak classification. Material and Methods: The original categories of 100 cystic renal masses were chosen as “Gold Standard” (GS), established...... to the calculated weighted κ all readers performed “very good” for both inter-observer and intra-observer variation. Most variation was seen in cysts catagorized as Bosniak II, IIF, and III. These results show that radiologists who evaluate complex renal cysts routinely may apply the Bosniak classification...

  10. Exploring the physical controls of regional patterns of flow duration curves – Part 3: A catchment classification system based on regime curve indicators

    Directory of Open Access Journals (Sweden)

    M. Sivapalan

    2012-11-01

    Full Text Available Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of flow duration curves (FDCs, motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser 3 (ID3 algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the five catchments' regime behavior and climate and catchment properties becomes clearer. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index

  11. Vascular anatomy of the medial sural artery perforator flap: a new classification system of intra-muscular branching patterns.

    Science.gov (United States)

    Dusseldorp, Joseph R; Pham, Quy J; Ngo, Quan; Gianoutsos, Mark; Moradi, Pouria

    2014-09-01

    The medial sural artery perforator (MSAP) flap is a versatile fasciocutaneous flap. The main difficulty encountered when raising the MSAP flap is in obtaining adequate pedicle length during intra-muscular dissection. The objective of this study was to determine the pattern of intra-muscular course of the MSAP flap pedicle. 14 cadaveric specimens were dissected and CT angiograms of 84 legs were examined. The intra-muscular branching pattern and depths of the medial sural artery branches were analyzed. The number of perforators, position of the dominant perforator and both intra-muscular and total pedicle length were also recorded and compared to existing anatomical data. Three types of arterial branching pattern were identified within the medial gastrocnemius, demonstrating one (31%), two (59%) or three or more (10%) main branches. A dominant perforator from the medial sural artery was present in 92% of anatomical specimens (13/14). Vertically, the location of the perforator from the popliteal crease was on average 13 cm (±2 cm). Transversely, the perforator originated 2.5 cm (±1 cm) from the posterior midline. Using CT angiography it was possible in 10 consecutive patients to identify a more superficial intra-muscular branch and determine the leg with the optimal branching pattern type for flap harvest. This study is the first to describe the variability of the intra-muscular arterial anatomy of the medial head of gastrocnemius muscle. Surgeons utilizing the MSAP flap option should be aware of the possible branching pattern types and consequently the differing perforator distribution and depths of intra-muscular branches. Routine use of pre-operative CT angiogram may help determine which leg has the most favorable branching pattern type and intra-muscular course for flap harvest. Copyright © 2014 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  12. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  13. Parametric classification of handvein patterns based on texture features

    Science.gov (United States)

    Al Mahafzah, Harbi; Imran, Mohammad; Supreetha Gowda H., D.

    2018-04-01

    In this paper, we have developed Biometric recognition system adopting hand based modality Handvein,which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have opted in choosing feature extraction algorithms such as LBP-visual descriptor, LPQ-blur insensitive texture operator, Log-Gabor-Texture descriptor. We have chosen well known classifiers such as KNN and SVM for classification. We have experimented and tabulated results of single algorithm recognition rate for Handvein under different distance measures and kernel options. The feature level fusion is carried out which increased the performance level.

  14. Completed Local Ternary Pattern for Rotation Invariant Texture Classification

    Directory of Open Access Journals (Sweden)

    Taha H. Rassem

    2014-01-01

    Full Text Available Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP and the Completed Local Binary Count (CLBC, have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP is proposed to be more robust to noise than LBP, however, the latter’s weakness may appear with the LTP as well as with LBP. In this paper, a novel completed modeling of the Local Ternary Pattern (LTP operator is proposed to overcome both LBP drawbacks, and an associated completed Local Ternary Pattern (CLTP scheme is developed for rotation invariant texture classification. The experimental results using four different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP and CLBC descriptors.

  15. Oral epithelial dysplasia classification systems

    DEFF Research Database (Denmark)

    Warnakulasuriya, S; Reibel, J; Bouquot, J

    2008-01-01

    At a workshop coordinated by the WHO Collaborating Centre for Oral Cancer and Precancer in the United Kingdom issues related to potentially malignant disorders of the oral cavity were discussed by an expert group. The consensus views of the Working Group are presented in a series of papers....... In this report, we review the oral epithelial dysplasia classification systems. The three classification schemes [oral epithelial dysplasia scoring system, squamous intraepithelial neoplasia and Ljubljana classification] were presented and the Working Group recommended epithelial dysplasia grading for routine...... use. Although most oral pathologists possibly recognize and accept the criteria for grading epithelial dysplasia, firstly based on architectural features and then of cytology, there is great variability in their interpretation of the presence, degree and significance of the individual criteria...

  16. A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation.

    Science.gov (United States)

    Cong, Rui; Li, Jing; Guo, Song

    2017-02-01

    To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all Pbreast mass diagnoses. Copyright © 2016. Published by Elsevier B.V.

  17. Classification using diffraction patterns for single-particle analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Hongli; Zhang, Kaiming [Department of Biophysics, the Health Science Centre, Peking University, Beijing 100191 (China); Meng, Xing, E-mail: xmeng101@gmail.com [Wadsworth Centre, New York State Department of Health, Albany, New York 12201 (United States)

    2016-05-15

    An alternative method has been assessed; diffraction patterns derived from the single particle data set were used to perform the first round of classification in creating the initial averages for proteins data with symmetrical morphology. The test protein set was a collection of Caenorhabditis elegans small heat shock protein 17 obtained by Cryo EM, which has a tetrahedral (12-fold) symmetry. It is demonstrated that the initial classification on diffraction patterns is workable as well as the real-space classification that is based on the phase contrast. The test results show that the information from diffraction patterns has the enough details to make the initial model faithful. The potential advantage using the alternative method is twofold, the ability to handle the sets with poor signal/noise or/and that break the symmetry properties. - Highlights: • New classification method. • Create the accurate initial model. • Better in handling noisy data.

  18. Classification using diffraction patterns for single-particle analysis

    International Nuclear Information System (INIS)

    Hu, Hongli; Zhang, Kaiming; Meng, Xing

    2016-01-01

    An alternative method has been assessed; diffraction patterns derived from the single particle data set were used to perform the first round of classification in creating the initial averages for proteins data with symmetrical morphology. The test protein set was a collection of Caenorhabditis elegans small heat shock protein 17 obtained by Cryo EM, which has a tetrahedral (12-fold) symmetry. It is demonstrated that the initial classification on diffraction patterns is workable as well as the real-space classification that is based on the phase contrast. The test results show that the information from diffraction patterns has the enough details to make the initial model faithful. The potential advantage using the alternative method is twofold, the ability to handle the sets with poor signal/noise or/and that break the symmetry properties. - Highlights: • New classification method. • Create the accurate initial model. • Better in handling noisy data.

  19. Classification and Target Group Selection Based Upon Frequent Patterns

    NARCIS (Netherlands)

    W.H.L.M. Pijls (Wim); R. Potharst (Rob)

    2000-01-01

    textabstractIn this technical report , two new algorithms based upon frequent patterns are proposed. One algorithm is a classification method. The other one is an algorithm for target group selection. In both algorithms, first of all, the collection of frequent patterns in the training set is

  20. In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

    Directory of Open Access Journals (Sweden)

    Vinicius Pegorini

    2015-11-01

    Full Text Available Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

  1. In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning.

    Science.gov (United States)

    Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito José; Ribeiro, Richardson; Bertotti, Fábio Luiz; Assmann, Tangriani Simioni

    2015-11-11

    Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

  2. A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Cong, Rui, E-mail: congrui2684@163.com; Li, Jing, E-mail: lijing@sj-hospital.org; Guo, Song, E-mail: 21751735@qq.com

    2017-02-15

    Highlights: • Qualitative SWE classification proposed here was significantly better than quantitative SWE parameters. • Qualitative classification proposed here was better than the classification proposed before. • Qualitative classification proposed here could obtain higher specificity without a loss of sensitivity. - Abstract: Objectives: To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. Methods: From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. Results: With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P < 0.05). When applying Qual1

  3. A new qualitative pattern classification of shear wave elastograghy for solid breast mass evaluation

    International Nuclear Information System (INIS)

    Cong, Rui; Li, Jing; Guo, Song

    2017-01-01

    Highlights: • Qualitative SWE classification proposed here was significantly better than quantitative SWE parameters. • Qualitative classification proposed here was better than the classification proposed before. • Qualitative classification proposed here could obtain higher specificity without a loss of sensitivity. - Abstract: Objectives: To examine the efficacy of qualitative shear wave elastography (SWE) in the classification and evaluation of solid breast masses, and to compare this method with conventional ultrasonograghy (US), quantitative SWE parameters and qualitative SWE classification proposed before. Methods: From April 2015 to March 2016, 314 consecutive females with 325 breast masses who decided to undergo core needle biopsy and/or surgical biopsy were enrolled. Conventional US and SWE were previously performed in all enrolled subjects. Each mass was classified by two different qualitative classifications. One was established in our study, herein named the Qual1. Qual1 could classify the SWE images into five color patterns by the visual evaluations: Color pattern 1 (homogeneous pattern); Color pattern 2 (comparative homogeneous pattern); Color pattern 3 (irregularly heterogeneous pattern); Color pattern 4 (intralesional echo pattern); and Color pattern 5 (the stiff rim sign pattern). The second qualitative classification was named Qual2 here, and included a four-color overlay pattern classification (Tozaki and Fukuma, Acta Radiologica, 2011). The Breast Imaging Reporting and Data System (BI-RADS) assessment and quantitative SWE parameters were recorded. Diagnostic performances of conventional US, SWE parameters, and combinations of US and SWE parameters were compared. Results: With pathological results as the gold standard, of the 325 examined breast masses, 139 (42.77%) samples were malignant and 186 (57.23%) were benign. The Qual1 showed a higher Az value than the Qual2 and quantitative SWE parameters (all P < 0.05). When applying Qual1

  4. SVM-based Partial Discharge Pattern Classification for GIS

    Science.gov (United States)

    Ling, Yin; Bai, Demeng; Wang, Menglin; Gong, Xiaojin; Gu, Chao

    2018-01-01

    Partial discharges (PD) occur when there are localized dielectric breakdowns in small regions of gas insulated substations (GIS). It is of high importance to recognize the PD patterns, through which we can diagnose the defects caused by different sources so that predictive maintenance can be conducted to prevent from unplanned power outage. In this paper, we propose an approach to perform partial discharge pattern classification. It first recovers the PRPD matrices from the PRPD2D images; then statistical features are extracted from the recovered PRPD matrix and fed into SVM for classification. Experiments conducted on a dataset containing thousands of images demonstrates the high effectiveness of the method.

  5. Classification of Magnetic Nanoparticle Systems

    DEFF Research Database (Denmark)

    Bogren, Sara; Fornara, Andrea; Ludwig, Frank

    2015-01-01

    and the size parameters are determined from electron microscopy and dynamic light scattering. Using these methods, we also show that the nanocrystal size and particle morphology determines the dynamic magnetic properties for both single- and multi-core particles. The presented results are obtained from...... the four year EU NMP FP7 project, NanoMag, which is focused on standardization of analysis methods for magnetic nanoparticles.......This study presents classification of different magnetic single- and multi-core particle systems using their measured dynamic magnetic properties together with their nanocrystal and particle sizes. The dynamic magnetic properties are measured with AC (dynamical) susceptometry and magnetorelaxometry...

  6. Classification of huminite-ICCP System 1994

    Energy Technology Data Exchange (ETDEWEB)

    Sykorova, I. [Institute of Rock Structure and Mechanics, Academy of Science of the Czech Republic, V Holesovicka 41, 182 09 Prague 8 (Czech Republic); Pickel, W. [Coal and Organic Petrology Services Pty Ltd, 23/80 Box Road, Taren Point, NSW 2229 (Australia); Christanis, K. [Department of Geology, University of Patras, 26500 Rio-Patras (Greece); Wolf, M. [Mergelskull 29, 47802 Krefeld (Germany); Taylor, G.H. [15 Hawkesbury Cres, Farrer Act 2607 (Australia); Flores, D. [Departamento de Geologia, Faculdade de Ciencias do Porto, Praca de Gomes Teixeira, 4099-002 Porto (Portugal)

    2005-04-12

    In the new classification (ICCP System 1994), the maceral group huminite has been revised from the previous classification (ICCP, 1971. Int. Handbook Coal Petr., suppl. to 2nd ed.) to accommodate the nomenclature to changes in the other maceral groups, especially the changes in the vitrinite classification (ICCP, 1998. The new vitrinite classification (ICCP System 1994). Fuel 77, 349-358.). The vitrinite and huminite systems have been correlated so that down to the level of sub-maceral groups, the two systems can be used in parallel. At the level of macerals and for finer classifications, the analyst now has, according to the nature of the coal and the purpose of the analysis, a choice of using either of the two classification systems for huminite and vitrinite. This is in accordance with the new ISO Coal Classification that covers low rank coals as well and allows for the simultaneous use of the huminite and vitrinite nomenclature for low rank coals.

  7. Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

    Directory of Open Access Journals (Sweden)

    MORARIU, N.

    2007-04-01

    Full Text Available The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.

  8. Territorial pattern and classification of soils of Kryvyi Rih Iron-Ore Basin

    OpenAIRE

    О. О. Dolina; О. М. Smetana

    2014-01-01

    The authors developed the classification of soils and adapted it to the conditions of Krivyi Rih industrial region. It became the basis for determining the degree of soil cover transformation in the iron-ore basin under technogenesis. The classification represents the system of hierarchical objects of different taxonomic levels. It allows determination of relationships between objects and their properties. Researched patterns of soil cover structures’ distribution were the basis for the relev...

  9. Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

    Science.gov (United States)

    Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

    2018-04-20

    Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

  10. An Ultrasonic Pattern Recognition Approach to Welding Defect Classification

    International Nuclear Information System (INIS)

    Song, Sung Jin

    1995-01-01

    Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic pattern recognition technique. Here brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on probabilistic neural networks as efficient classifiers for many practical classification problems. In an example probabilistic neural networks are applied to classify flaws in weldments into 3 classes such as cracks, porosity and slag inclusions. Probabilistic nets are shown to be able to exhibit high performance of other classifiers without any training time overhead. In addition, forward selection scheme for sensitive features is addressed to enhance network performance

  11. Hyperspectral image classification based on local binary patterns and PCANet

    Science.gov (United States)

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

    2018-04-01

    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  12. A supervised learning rule for classification of spatiotemporal spike patterns.

    Science.gov (United States)

    Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

    2016-08-01

    This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

  13. An eye tracking study of bloodstain pattern analysts during pattern classification.

    Science.gov (United States)

    Arthur, R M; Hoogenboom, J; Green, R D; Taylor, M C; de Bruin, K G

    2018-05-01

    Bloodstain pattern analysis (BPA) is the forensic discipline concerned with the classification and interpretation of bloodstains and bloodstain patterns at the crime scene. At present, it is unclear exactly which stain or pattern properties and their associated values are most relevant to analysts when classifying a bloodstain pattern. Eye tracking technology has been widely used to investigate human perception and cognition. Its application to forensics, however, is limited. This is the first study to use eye tracking as a tool for gaining access to the mindset of the bloodstain pattern expert. An eye tracking method was used to follow the gaze of 24 bloodstain pattern analysts during an assigned task of classifying a laboratory-generated test bloodstain pattern. With the aid of an automated image-processing methodology, the properties of selected features of the pattern were quantified leading to the delineation of areas of interest (AOIs). Eye tracking data were collected for each AOI and combined with verbal statements made by analysts after the classification task to determine the critical range of values for relevant diagnostic features. Eye-tracking data indicated that there were four main regions of the pattern that analysts were most interested in. Within each region, individual elements or groups of elements that exhibited features associated with directionality, size, colour and shape appeared to capture the most interest of analysts during the classification task. The study showed that the eye movements of trained bloodstain pattern experts and their verbal descriptions of a pattern were well correlated.

  14. Patterns in natural systems

    NARCIS (Netherlands)

    Sewalt, L.

    2016-01-01

    In the thesis, `Patterns in natural systems’ the formation and evolution of patterns as solutions of several partial differential systems are studied. These mathematical systems model three different biological and ecological processes. First, the way that plankton concentrates in the water column,

  15. AOSpine subaxial cervical spine injury classification system

    NARCIS (Netherlands)

    Vaccaro, Alexander R.; Koerner, John D.; Radcliff, Kris E.; Oner, F. Cumhur; Reinhold, Maximilian; Schnake, Klaus J.; Kandziora, Frank; Fehlings, Michael G.; Dvorak, Marcel F.; Aarabi, Bizhan; Rajasekaran, Shanmuganathan; Schroeder, Gregory D.; Kepler, Christopher K.; Vialle, Luiz R.

    2016-01-01

    Purpose: This project describes a morphology-based subaxial cervical spine traumatic injury classification system. Using the same approach as the thoracolumbar system, the goal was to develop a comprehensive yet simple classification system with high intra- and interobserver reliability to be used

  16. A Classification Scheme for Production System Processes

    DEFF Research Database (Denmark)

    Sørensen, Daniel Grud Hellerup; Brunø, Thomas Ditlev; Nielsen, Kjeld

    2018-01-01

    Manufacturing companies often have difficulties developing production platforms, partly due to the complexity of many production systems and difficulty determining which processes constitute a platform. Understanding production processes is an important step to identifying candidate processes...... for a production platform based on existing production systems. Reviewing a number of existing classifications and taxonomies, a consolidated classification scheme for processes in production of discrete products has been outlined. The classification scheme helps ensure consistency during mapping of existing...

  17. Supervised and Unsupervised Classification for Pattern Recognition Purposes

    Directory of Open Access Journals (Sweden)

    Catalina COCIANU

    2006-01-01

    Full Text Available A cluster analysis task has to identify the grouping trends of data, to decide on the sound clusters as well as to validate somehow the resulted structure. The identification of the grouping tendency existing in a data collection assumes the selection of a framework stated in terms of a mathematical model allowing to express the similarity degree between couples of particular objects, quasi-metrics expressing the similarity between an object an a cluster and between clusters, respectively. In supervised classification, we are provided with a collection of preclassified patterns, and the problem is to label a newly encountered pattern. Typically, the given training patterns are used to learn the descriptions of classes which in turn are used to label a new pattern. The final section of the paper presents a new methodology for supervised learning based on PCA. The classes are represented in the measurement/feature space by a continuous repartitions

  18. Staining pattern classification of antinuclear autoantibodies based on block segmentation in indirect immunofluorescence images.

    Directory of Open Access Journals (Sweden)

    Jiaqian Li

    Full Text Available Indirect immunofluorescence based on HEp-2 cell substrate is the most commonly used staining method for antinuclear autoantibodies associated with different types of autoimmune pathologies. The aim of this paper is to design an automatic system to identify the staining patterns based on block segmentation compared to the cell segmentation most used in previous research. Various feature descriptors and classifiers are tested and compared in the classification of the staining pattern of blocks and it is found that the technique of the combination of the local binary pattern and the k-nearest neighbor algorithm achieve the best performance. Relying on the results of block pattern classification, experiments on the whole images show that classifier fusion rules are able to identify the staining patterns of the whole well (specimen image with a total accuracy of about 94.62%.

  19. In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

    OpenAIRE

    Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito Jos?; Ribeiro, Richardson; Bertotti, F?bio Luiz; Assmann, Tangriani Simioni

    2015-01-01

    Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for th...

  20. Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm

    Directory of Open Access Journals (Sweden)

    M. José H. Erazo Macias

    2006-01-01

    Full Text Available This paper deals with the statistical analysis and pattern classification of electromyographic signals from the biceps of a person with amputation below the humerus. Such signals collected from an amputation simulator are synergistically generated to produce discrete elbow movements. The purpose of this study is to utilise these signals to control an electrically driven prosthetic or orthotic elbow with minimum extra mental effort on the part of the subject. The results show very good separability of classes of movements when a learning pattern classification scheme is used, and a superposition of any composite motion to the three basic primitive motions—humeral rotation in and out, flexion and extension, and pronation and supination. Since no synergy was detected for the wrist movement, different inputs have to be provided for a grip. In addition, the method described is not limited by the location of the electrodes. For amputees with shorter stumps, synergistic signals could be obtained from the shoulder muscles. However, the presentation in this paper is limited to biceps signal classification only.

  1. Heterogeneous patterns enhancing static and dynamic texture classification

    International Nuclear Information System (INIS)

    Silva, Núbia Rosa da; Martinez Bruno, Odemir

    2013-01-01

    Some mixtures, such as colloids like milk, blood, and gelatin, have homogeneous appearance when viewed with the naked eye, however, to observe them at the nanoscale is possible to understand the heterogeneity of its components. The same phenomenon can occur in pattern recognition in which it is possible to see heterogeneous patterns in texture images. However, current methods of texture analysis can not adequately describe such heterogeneous patterns. Common methods used by researchers analyse the image information in a global way, taking all its features in an integrated manner. Furthermore, multi-scale analysis verifies the patterns at different scales, but still preserving the homogeneous analysis. On the other hand various methods use textons to represent the texture, breaking texture down into its smallest unit. To tackle this problem, we propose a method to identify texture patterns not small as textons at distinct scales enhancing the separability among different types of texture. We find sub patterns of texture according to the scale and then group similar patterns for a more refined analysis. Tests were performed in four static texture databases and one dynamical one. Results show that our method provide better classification rate compared with conventional approaches both in static and in dynamic texture.

  2. Discriminant forest classification method and system

    Science.gov (United States)

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  3. New C2 synchondrosal fracture classification system

    Energy Technology Data Exchange (ETDEWEB)

    Rusin, Jerome A.; Ruess, Lynne [Department of Radiology, Nationwide Children' s Hospital, Columbus, OH (United States); The Ohio State University College of Medicine and Public Health, Columbus, OH (United States); Daulton, Robert S. [Department of Radiology, Nationwide Children' s Hospital, Columbus, OH (United States)

    2015-06-15

    Excessive cervical flexion-extension accompanying mild to severe impact injuries can lead to C2 synchondrosal fractures in young children. To characterize and classify C2 synchondrosal fracture patterns. We retrospectively reviewed imaging and medical records of children who were treated for cervical spine fractures at our institution between 1995 and 2014. We reviewed all fractures involving the five central C2 synchondroses with regard to patient demographics, mechanism of injury, fracture pattern, associated fractures and other injuries, treatment plans and outcome. Fourteen children had fractures involving the central C2 synchondroses. There were nine boys and five girls, all younger than 6 years. We found four distinct fracture patterns. Eleven complete fractures were further divided into four subtypes (a, b, c and d) based on degree of anterior displacement of the odontoid segment and presence of distraction. Nine of these 11 children had fractures through both odontoneural synchondroses and the odontocentral synchondrosis; one had fractures involving both neurocentral synchondroses and the odontoneural synchondrosis; one had fractures through bilateral odontoneural and bilateral neurocentral synchondroses. Three children had incomplete fractures, defined as a fracture through a single odontoneural synchondrosis with or without partial extension into either the odontocentral or the adjacent neurocentral synchondroses. All complete fractures were displaced or angulated. Four had associated spinal cord injury, including two contusions (subtype c fractures) and two fatal transections (subtype d fractures). Most children were treated with primary halo stabilization. Subtype c fractures required surgical fixation. We describe four patterns of central C2 synchondrosal fractures, including two unique patterns that have not been reported. We propose a classification system to distinguish these fractures and aid in treatment planning. (orig.)

  4. Music Genre Classification Systems - A Computational Approach

    DEFF Research Database (Denmark)

    Ahrendt, Peter

    2006-01-01

    Automatic music genre classification is the classification of a piece of music into its corresponding genre (such as jazz or rock) by a computer. It is considered to be a cornerstone of the research area Music Information Retrieval (MIR) and closely linked to the other areas in MIR. It is thought...... that MIR will be a key element in the processing, searching and retrieval of digital music in the near future. This dissertation is concerned with music genre classification systems and in particular systems which use the raw audio signal as input to estimate the corresponding genre. This is in contrast...... to systems which use e.g. a symbolic representation or textual information about the music. The approach to music genre classification systems has here been system-oriented. In other words, all the different aspects of the systems have been considered and it is emphasized that the systems should...

  5. Image Classification Using Biomimetic Pattern Recognition with Convolutional Neural Networks Features

    Science.gov (United States)

    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

  6. Multi-q pattern classification of polarization curves

    Science.gov (United States)

    Fabbri, Ricardo; Bastos, Ivan N.; Neto, Francisco D. Moura; Lopes, Francisco J. P.; Gonçalves, Wesley N.; Bruno, Odemir M.

    2014-02-01

    Several experimental measurements are expressed in the form of one-dimensional profiles, for which there is a scarcity of methodologies able to classify the pertinence of a given result to a specific group. The polarization curves that evaluate the corrosion kinetics of electrodes in corrosive media are applications where the behavior is chiefly analyzed from profiles. Polarization curves are indeed a classic method to determine the global kinetics of metallic electrodes, but the strong nonlinearity from different metals and alloys can overlap and the discrimination becomes a challenging problem. Moreover, even finding a typical curve from replicated tests requires subjective judgment. In this paper, we used the so-called multi-q approach based on the Tsallis statistics in a classification engine to separate the multiple polarization curve profiles of two stainless steels. We collected 48 experimental polarization curves in an aqueous chloride medium of two stainless steel types, with different resistance against localized corrosion. Multi-q pattern analysis was then carried out on a wide potential range, from cathodic up to anodic regions. An excellent classification rate was obtained, at a success rate of 90%, 80%, and 83% for low (cathodic), high (anodic), and both potential ranges, respectively, using only 2% of the original profile data. These results show the potential of the proposed approach towards efficient, robust, systematic and automatic classification of highly nonlinear profile curves.

  7. Evaluation of classification systems for nonspecific idiopathic orbital inflammation

    NARCIS (Netherlands)

    Bijlsma, Ward R.; van 't Hullenaar, Fleur C.; Mourits, Maarten P.; Kalmann, Rachel

    2012-01-01

    To systematically analyze existing classification systems for idiopathic orbital inflammation (IOI) and propose and test a new best practice classification system. A systematic literature search was conducted to find all studies that described and applied a classification system for IOI.

  8. QA CLASSIFICATION ANALYSIS OF GROUND SUPPORT SYSTEMS

    International Nuclear Information System (INIS)

    D. W. Gwyn

    1996-01-01

    The purpose and objective of this analysis is to determine if the permanent function Ground Support Systems (CI: BABEEOOOO) are quality-affecting items and if so, to establish the appropriate Quality Assurance (QA) classification

  9. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  10. A Confidence Paradigm for Classification Systems

    Science.gov (United States)

    2008-09-01

    methodology to determine how much confi- dence one should have in a classifier output. This research proposes a framework to determine the level of...theoretical framework that attempts to unite the viewpoints of the classification system developer (or engineer) and the classification system user (or...operating point. An algorithm is developed that minimizes a “confidence” measure called Binned Error in the Posterior ( BEP ). Then, we prove that training a

  11. Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

    Science.gov (United States)

    Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

    2010-12-01

    The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns. Copyright © 2010 Elsevier Ltd. All rights reserved.

  12. Patterns and Intelligent Systems

    International Nuclear Information System (INIS)

    Cordes, Gail A.

    2003-01-01

    The recognition and analysis of evolving patterns provides a unifying concept for studying and implementing intelligent information processing for open feedback control systems within the nuclear industry. Control is considered as influence of a large system to achieve the goals of the human (who might or might not be part of an open feedback loop) and is not limited to operation of a component within a nuclear power plant. The intelligent control system includes open logic and can automatically react to new data in an unprogrammed way. This application of evolving patterns integrates current research developments in human cognition and scientific semiotics with traditional feedback control. A preliminary implementation of such a system using existing computational techniques is postulated, and tools that are lacking at this time are identified. Proof-of-concept applications for the nuclear industry are referenced

  13. Pattern graph rewrite systems

    Directory of Open Access Journals (Sweden)

    Aleks Kissinger

    2014-03-01

    Full Text Available String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. Dixon, Duncan and Kissinger introduced string graphs, which are a combinatoric representations of string diagrams, amenable to automated reasoning about diagrammatic theories via graph rewrite systems. In this extended abstract, we show how the power of such rewrite systems can be greatly extended by introducing pattern graphs, which provide a means of expressing infinite families of rewrite rules where certain marked subgraphs, called !-boxes ("bang boxes", on both sides of a rule can be copied any number of times or removed. After reviewing the string graph formalism, we show how string graphs can be extended to pattern graphs and how pattern graphs and pattern rewrite rules can be instantiated to concrete string graphs and rewrite rules. We then provide examples demonstrating the expressive power of pattern graphs and how they can be applied to study interacting algebraic structures that are central to categorical quantum mechanics.

  14. Enhancement of force patterns classification based on Gaussian distributions.

    Science.gov (United States)

    Ertelt, Thomas; Solomonovs, Ilja; Gronwald, Thomas

    2018-01-23

    Description of the patterns of ground reaction force is a standard method in areas such as medicine, biomechanics and robotics. The fundamental parameter is the time course of the force, which is classified visually in particular in the field of clinical diagnostics. Here, the knowledge and experience of the diagnostician is relevant for its assessment. For an objective and valid discrimination of the ground reaction force pattern, a generic method, especially in the medical field, is absolutely necessary to describe the qualities of the time-course. The aim of the presented method was to combine the approaches of two existing procedures from the fields of machine learning and the Gauss approximation in order to take advantages of both methods for the classification of ground reaction force patterns. The current limitations of both methods could be eliminated by an overarching method. Twenty-nine male athletes from different sports were examined. Each participant was given the task of performing a one-legged stopping maneuver on a force plate from the maximum possible starting speed. The individual time course of the ground reaction force of each subject was registered and approximated on the basis of eight Gaussian distributions. The descriptive coefficients were then classified using Bayesian regulated neural networks. The different sports served as the distinguishing feature. Although the athletes were all given the same task, all sports referred to a different quality in the time course of ground reaction force. Meanwhile within each sport, the athletes were homogeneous. With an overall prediction (R = 0.938) all subjects/sports were classified correctly with 94.29% accuracy. The combination of the two methods: the mathematical description of the time course of ground reaction forces on the basis of Gaussian distributions and their classification by means of Bayesian regulated neural networks, seems an adequate and promising method to discriminate the

  15. A statistical approach to root system classification.

    Directory of Open Access Journals (Sweden)

    Gernot eBodner

    2013-08-01

    Full Text Available 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. We demonstrate that combining principal component and cluster analysis yields a meaningful classification of rooting types based on morphological traits. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. Biplot inspection is used to determine key traits and to ensure stability in cluster based grouping. 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. Three rooting types emerged from measured data, distinguished by diameter/weight, density and spatial distribution respectively. 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

  16. Classification of interstitial lung disease patterns with topological texture features

    Science.gov (United States)

    Huber, Markus B.; Nagarajan, Mahesh; Leinsinger, Gerda; Ray, Lawrence A.; Wismüller, Axel

    2010-03-01

    Topological texture features were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honey-combing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. A set of 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions and the significance thresholds were adjusted for multiple comparisons by the Bonferroni correction. The best classification results were obtained by the MF features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers. The highest accuracy was found for MF.euler (97.5%, 96.6%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced topological texture features can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

  17. Median Robust Extended Local Binary Pattern for Texture Classification.

    Science.gov (United States)

    Liu, Li; Lao, Songyang; Fieguth, Paul W; Guo, Yulan; Wang, Xiaogang; Pietikäinen, Matti

    2016-03-01

    Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image noise and is unable to capture macrostructure information. To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Different from the traditional LBP and many LBP variants, MRELBP compares regional image medians rather than raw image intensities. A multiscale LBP type descriptor is computed by efficiently comparing image medians over a novel sampling scheme, which can capture both microstructure and macrostructure texture information. A comprehensive evaluation on benchmark data sets reveals MRELBP's high performance-robust to gray scale variations, rotation changes and noise-but at a low computational cost. MRELBP produces the best classification scores of 99.82%, 99.38%, and 99.77% on three popular Outex test suites. More importantly, MRELBP is shown to be highly robust to image noise, including Gaussian noise, Gaussian blur, salt-and-pepper noise, and random pixel corruption.

  18. PATTERN CLASSIFICATION APPROACHES TO MATCHING BUILDING POLYGONS AT MULTIPLE SCALES

    Directory of Open Access Journals (Sweden)

    X. Zhang

    2012-07-01

    Full Text Available Matching of building polygons with different levels of detail is crucial in the maintenance and quality assessment of multi-representation databases. Two general problems need to be addressed in the matching process: (1 Which criteria are suitable? (2 How to effectively combine different criteria to make decisions? This paper mainly focuses on the second issue and views data matching as a supervised pattern classification. Several classifiers (i.e. decision trees, Naive Bayes and support vector machines are evaluated for the matching task. Four criteria (i.e. position, size, shape and orientation are used to extract information for these classifiers. Evidence shows that these classifiers outperformed the weighted average approach.

  19. Classification of natural circulation two-phase flow patterns using fuzzy inference on image analysis

    International Nuclear Information System (INIS)

    Mesquita, R.N. de; Masotti, P.H.F.; Penha, R.M.L.; Andrade, D.A.; Sabundjian, G.; Torres, W.M.

    2012-01-01

    Highlights: ► A fuzzy classification system for two-phase flow instability patterns is developed. ► Flow patterns are classified based on images of natural circulation experiments. ► Fuzzy inference is optimized to use single grayscale profiles as input. - Abstract: Two-phase flow on natural circulation phenomenon has been an important theme on recent studies related to nuclear reactor designs. The accuracy of heat transfer estimation has been improved with new models that require precise prediction of pattern transitions of flow. In this work, visualization of natural circulation cycles is used to study two-phase flow patterns associated with phase transients and static instabilities of flow. A Fuzzy Flow-type Classification System (FFCS) was developed to classify these patterns based only on image extracted features. Image acquisition and temperature measurements were simultaneously done. Experiments in natural circulation facility were adjusted to generate a series of characteristic two-phase flow instability periodic cycles. The facility is composed of a loop of glass tubes, a heat source using electrical heaters, a cold source using a helicoidal heat exchanger, a visualization section and thermocouples positioned over different loop sections. The instability cyclic period is estimated based on temperature measurements associated with the detection of a flow transition image pattern. FFCS shows good results provided that adequate image acquisition parameters and pre-processing adjustments are used.

  20. A Framework to Support Automated Classification and Labeling of Brain Electromagnetic Patterns

    Directory of Open Access Journals (Sweden)

    Gwen A. Frishkoff

    2007-01-01

    Full Text Available This paper describes a framework for automated classification and labeling of patterns in electroencephalographic (EEG and magnetoencephalographic (MEG data. We describe recent progress on four goals: 1 specification of rules and concepts that capture expert knowledge of event-related potentials (ERP patterns in visual word recognition; 2 implementation of rules in an automated data processing and labeling stream; 3 data mining techniques that lead to refinement of rules; and 4 iterative steps towards system evaluation and optimization. This process combines top-down, or knowledge-driven, methods with bottom-up, or data-driven, methods. As illustrated here, these methods are complementary and can lead to development of tools for pattern classification and labeling that are robust and conceptually transparent to researchers. The present application focuses on patterns in averaged EEG (ERP data. We also describe efforts to extend our methods to represent patterns in MEG data, as well as EM patterns in source (anatomical space. The broader aim of this work is to design an ontology-based system to support cross-laboratory, cross-paradigm, and cross-modal integration of brain functional data. Tools developed for this project are implemented in MATLAB and are freely available on request.

  1. Classification of data patterns using an autoassociative neural network topology

    Science.gov (United States)

    Dietz, W. E.; Kiech, E. L.; Ali, M.

    1989-01-01

    A diagnostic expert system based on neural networks is developed and applied to the real-time diagnosis of jet and rocket engines. The expert system methodologies are based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. The approach addresses deficiencies inherent in many feedforward neural network models and greatly reduces the number of networks necessary to identify the existence of a fault condition and estimate the duration and severity of the identified fault. The network topology used in the present implementation of the diagnostic system is described, as well as the training regimen used and the response of the system to inputs representing both previously observed and unknown fault scenarios. Noise effects on the integrity of the diagnosis are also evaluated.

  2. An evaluation of classification systems for stillbirth

    Directory of Open Access Journals (Sweden)

    Pattinson Robert

    2009-06-01

    Full Text Available Abstract Background Audit and classification of stillbirths is an essential part of clinical practice and a crucial step towards stillbirth prevention. Due to the limitations of the ICD system and lack of an international approach to an acceptable solution, numerous disparate classification systems have emerged. We assessed the performance of six contemporary systems to inform the development of an internationally accepted approach. Methods We evaluated the following systems: Amended Aberdeen, Extended Wigglesworth; PSANZ-PDC, ReCoDe, Tulip and CODAC. Nine teams from 7 countries applied the classification systems to cohorts of stillbirths from their regions using 857 stillbirth cases. The main outcome measures were: the ability to retain the important information about the death using the InfoKeep rating; the ease of use according to the Ease rating (both measures used a five-point scale with a score Results InfoKeep scores were significantly different across the classifications (p ≤ 0.01 due to low scores for Wigglesworth and Aberdeen. CODAC received the highest mean (SD score of 3.40 (0.73 followed by PSANZ-PDC, ReCoDe and Tulip [2.77 (1.00, 2.36 (1.21, 1.92 (1.24 respectively]. Wigglesworth and Aberdeen resulted in a high proportion of unexplained stillbirths and CODAC and Tulip the lowest. While Ease scores were different (p ≤ 0.01, all systems received satisfactory scores; CODAC received the highest score. Aberdeen and Wigglesworth showed poor agreement with kappas of 0.35 and 0.25 respectively. Tulip performed best with a kappa of 0.74. The remainder had good to fair agreement. Conclusion The Extended Wigglesworth and Amended Aberdeen systems cannot be recommended for classification of stillbirths. Overall, CODAC performed best with PSANZ-PDC and ReCoDe performing well. Tulip was shown to have the best agreement and a low proportion of unexplained stillbirths. The virtues of these systems need to be considered in the development of an

  3. An evaluation of classification systems for stillbirth.

    Science.gov (United States)

    Flenady, Vicki; Frøen, J Frederik; Pinar, Halit; Torabi, Rozbeh; Saastad, Eli; Guyon, Grace; Russell, Laurie; Charles, Adrian; Harrison, Catherine; Chauke, Lawrence; Pattinson, Robert; Koshy, Rachel; Bahrin, Safiah; Gardener, Glenn; Day, Katie; Petersson, Karin; Gordon, Adrienne; Gilshenan, Kristen

    2009-06-19

    Audit and classification of stillbirths is an essential part of clinical practice and a crucial step towards stillbirth prevention. Due to the limitations of the ICD system and lack of an international approach to an acceptable solution, numerous disparate classification systems have emerged. We assessed the performance of six contemporary systems to inform the development of an internationally accepted approach. We evaluated the following systems: Amended Aberdeen, Extended Wigglesworth; PSANZ-PDC, ReCoDe, Tulip and CODAC. Nine teams from 7 countries applied the classification systems to cohorts of stillbirths from their regions using 857 stillbirth cases. The main outcome measures were: the ability to retain the important information about the death using the InfoKeep rating; the ease of use according to the Ease rating (both measures used a five-point scale with a score <2 considered unsatisfactory); inter-observer agreement and the proportion of unexplained stillbirths. A randomly selected subset of 100 stillbirths was used to assess inter-observer agreement. InfoKeep scores were significantly different across the classifications (p < or = 0.01) due to low scores for Wigglesworth and Aberdeen. CODAC received the highest mean (SD) score of 3.40 (0.73) followed by PSANZ-PDC, ReCoDe and Tulip [2.77 (1.00), 2.36 (1.21), 1.92 (1.24) respectively]. Wigglesworth and Aberdeen resulted in a high proportion of unexplained stillbirths and CODAC and Tulip the lowest. While Ease scores were different (p < or = 0.01), all systems received satisfactory scores; CODAC received the highest score. Aberdeen and Wigglesworth showed poor agreement with kappas of 0.35 and 0.25 respectively. Tulip performed best with a kappa of 0.74. The remainder had good to fair agreement. The Extended Wigglesworth and Amended Aberdeen systems cannot be recommended for classification of stillbirths. Overall, CODAC performed best with PSANZ-PDC and ReCoDe performing well. Tulip was shown to have the

  4. Fission--fusion systems: classification and critique

    International Nuclear Information System (INIS)

    Lidsky, L.M.

    1974-01-01

    A useful classification scheme for hybrid systems is described and some common features that the scheme makes apparent are pointed out. The early history of fusion-fission systems is reviewed. Some designs are described along with advantages and disadvantages of each. The extension to low and moderate Q devices is noted. (U.S.)

  5. Mapping a classification system to architectural education

    DEFF Research Database (Denmark)

    Hermund, Anders; Klint, Lars; Rostrup, Nicolai

    2015-01-01

    This paper examines to what extent a new classification system, Cuneco Classification System, CCS, proves useful in the education of architects, and to what degree the aim of an architectural education, rather based on an arts and crafts approach than a polytechnic approach, benefits from...... the distinct terminology of the classification system. The method used to examine the relationship between education, practice and the CCS bifurcates in a quantitative and a qualitative exploration: Quantitative comparison of the curriculum with the students’ own descriptions of their studies through...... a questionnaire survey among 88 students in graduate school. Qualitative interviews with a handful of practicing architects, to be able to cross check the relevance of the education with the profession. The examination indicates the need of a new definition, in addition to the CCS’s scale, covering the earliest...

  6. Application of Classification Methods for Forecasting Mid-Term Power Load Patterns

    Science.gov (United States)

    Piao, Minghao; Lee, Heon Gyu; Park, Jin Hyoung; Ryu, Keun Ho

    Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed approach in this paper consists of three stages: (i) data preprocessing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

  7. A Novel Classification System for Injuries After Electronic Cigarette Explosions.

    Science.gov (United States)

    Patterson, Scott B; Beckett, Allison R; Lintner, Alicia; Leahey, Carly; Greer, Ashley; Brevard, Sidney B; Simmons, Jon D; Kahn, Steven A

    Electronic cigarettes (e-cigarettes) contain lithium batteries that have been known to explode and/or cause fires that have resulted in burn injury. The purpose of this article is to present a case study, review injuries caused by e-cigarettes, and present a novel classification system from the newly emerging patterns of burns. A case study was presented and online media reports for e-cigarette burns were queried with search terms "e-cigarette burns" and "electronic cigarette burns." The reports and injury patterns were tabulated. Analysis was then performed to create a novel classification system based on the distinct injury patterns seen in the study. Two patients were seen at our regional burn center after e-cigarette burns. One had an injury to his thigh and penis that required operative intervention after ignition of this device in his pocket. The second had a facial burn and corneal abrasions when the device exploded while he was inhaling vapor. The Internet search and case studies resulted in 26 cases for evaluation. The burn patterns were divided in direct injury from the device igniting and indirect injury when the device caused a house or car fire. A numerical classification was created: direct injury: type 1 (hand injury) 7 cases, type 2 (face injury) 8 cases, type 3 (waist/groin injury) 11 cases, and type 5a (inhalation injury from using device) 2 cases; indirect injury: type 4 (house fire injury) 7 cases and type 5b (inhalation injury from fire started by the device) 4 cases. Multiple e-cigarette injuries are occurring in the United States and distinct patterns of burns are emerging. The classification system developed in this article will aid in further study and future regulation of these dangerous devices.

  8. A proposed United States resource classification system

    International Nuclear Information System (INIS)

    Masters, C.D.

    1980-01-01

    Energy is a world-wide problem calling for world-wide communication to resolve the many supply and distribution problems. Essential to a communication problem are a definition and comparability of elements being communicated. The US Geological Survey, with the co-operation of the US Bureau of Mines and the US Department of Energy, has devised a classification system for all mineral resources, the principles of which, it is felt, offer the possibility of world communication. At present several other systems, extant or under development (Potential Gas Committee of the USA, United Nations Resource Committee, and the American Society of Testing and Materials) are internally consistent and provide easy communication linkage. The system in use by the uranium community in the United States of America, however, ties resource quantities to forward-cost dollar values rendering them inconsistent with other classifications and therefore not comparable. This paper develops the rationale for the new USGS resource classification and notes its benefits relative to a forward-cost classification and its relationship specifically to other current classifications. (author)

  9. A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

    Directory of Open Access Journals (Sweden)

    Jin Xie

    2012-06-01

    Full Text Available Human hand back skin texture (HBST is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands. An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the -minimization based sparse representation (SR technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification.

  10. CLASSIFICATION OF THE MGR MUCK HANDLING SYSTEM

    International Nuclear Information System (INIS)

    R. Garrett

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) muck handling system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description (QARD) (DOE 1998). This QA classification incorporates the current MGR design and the results of the ''Preliminary Preclosure Design Basis Event Calculations for the Monitored Geologic Repository (CRWMS M and O 1998a)

  11. Territorial pattern and classification of soils of Kryvyi Rih Iron-Ore Basin

    Directory of Open Access Journals (Sweden)

    О. О. Dolina

    2014-10-01

    Full Text Available The authors developed the classification of soils and adapted it to the conditions of Krivyi Rih industrial region. It became the basis for determining the degree of soil cover transformation in the iron-ore basin under technogenesis. The classification represents the system of hierarchical objects of different taxonomic levels. It allows determination of relationships between objects and their properties. Researched patterns of soil cover structures’ distribution were the basis for the relevant mapping and classification of soils. The classification is adapted to highly-influential industrial conditions of soils formation in the region. The adaptation measures were specific classification levels and units, which provided more detailed differentiation of soils. The authors proposed to separate the soils by the degree of soil formation potential realization for super-divisions. The potential determination allowed predicting the outcome of soil formation and identification of transformation degree of soil cover structures in the region. The results indicated that the main type of soil structures in the industrial region was represented by primitive soils (indicated as a separate type. These soils were determined as dynamic elements in the structure of industrial region soil cover. The article indicated that presence of soil cover structures with the domination of technogenic soils, particularly post-technogenic soils, was the marker of the soil cover in Krivyi Rih Iron-Ore Basin

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

    Science.gov (United States)

    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

  13. Low-cost real-time automatic wheel classification system

    Science.gov (United States)

    Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

    1992-11-01

    This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

  14. A Challenge to Change: Necessary Changes in the Library Classification System for the Chicago Public Schools.

    Science.gov (United States)

    Williams, Florence M.

    This report addresses the feasibility of changing the classification of library materials in the Chicago Public School libraries from the Dewey Decimal classification system (DDC) to the Library of Congress system (LC), thus patterning the city school libraries after the Chicago Public Library and strengthening the existing close relationship…

  15. Automatic music genres classification as a pattern recognition problem

    Science.gov (United States)

    Ul Haq, Ihtisham; Khan, Fauzia; Sharif, Sana; Shaukat, Arsalan

    2013-12-01

    Music genres are the simplest and effect descriptors for searching music libraries stores or catalogues. The paper compares the results of two automatic music genres classification systems implemented by using two different yet simple classifiers (K-Nearest Neighbor and Naïve Bayes). First a 10-12 second sample is selected and features are extracted from it, and then based on those features results of both classifiers are represented in the form of accuracy table and confusion matrix. An experiment carried out on test 60 taken from middle of a song represents the true essence of its genre as compared to the samples taken from beginning and ending of a song. The novel techniques have achieved an accuracy of 91% and 78% by using Naïve Bayes and KNN classifiers respectively.

  16. Classification of ERP System Services

    Directory of Open Access Journals (Sweden)

    Petr Sodomka

    2016-07-01

    Full Text Available Today the ERP business information systems are an essential tool for organization management, regardless of size and field of activity. Their successful implementation and use is conditioned predominantly by IS/ICT knowledge and managerial skills required for directing their life cycle correctly. Defining and correct setting of the service level is a key requirement and skill, usually provided by a service provider based on an implementation and service contract, or an advisory organization, in particular when presale services concerning analyses and tender documentation processing are provided. The following paper discusses the characteristics of the individual service types and the particulars of their practical use. Moreover, it presents the selected significant results of the long-term research performed by the authors in the Center for inVestigations into Information Systems.

  17. The development of a classification system for inland aquatic ...

    African Journals Online (AJOL)

    A classification system is described that was developed for inland aquatic ecosystems in South Africa, including wetlands. The six-tiered classification system is based on a top-down, hierarchical classification of aquatic ecosystems, following the functionally-oriented hydrogeomorphic (HGM) approach to classification but ...

  18. Common occupational classification system - revision 3

    Energy Technology Data Exchange (ETDEWEB)

    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 in 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.

  19. Fusion of fuzzy statistical distributions for classification of thyroid ultrasound patterns.

    Science.gov (United States)

    Iakovidis, Dimitris K; Keramidas, Eystratios G; Maroulis, Dimitris

    2010-09-01

    This paper proposes a novel approach for thyroid ultrasound pattern representation. Considering that texture and echogenicity are correlated with thyroid malignancy, the proposed approach encodes these sonographic features via a noise-resistant representation. This representation is suitable for the discrimination of nodules of high malignancy risk from normal thyroid parenchyma. The material used in this study includes a total of 250 thyroid ultrasound patterns obtained from 75 patients in Greece. The patterns are represented by fused vectors of fuzzy features. Ultrasound texture is represented by fuzzy local binary patterns, whereas echogenicity is represented by fuzzy intensity histograms. The encoded thyroid ultrasound patterns are discriminated by support vector classifiers. The proposed approach was comprehensively evaluated using receiver operating characteristics (ROCs). The results show that the proposed fusion scheme outperforms previous thyroid ultrasound pattern representation methods proposed in the literature. The best classification accuracy was obtained with a polynomial kernel support vector machine, and reached 97.5% as estimated by the area under the ROC curve. The fusion of fuzzy local binary patterns and fuzzy grey-level histogram features is more effective than the state of the art approaches for the representation of thyroid ultrasound patterns and can be effectively utilized for the detection of nodules of high malignancy risk in the context of an intelligent medical system. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  20. CLASSIFICATION OF THE MGR SITE LAYOUT SYSTEM

    International Nuclear Information System (INIS)

    S.E. Salzman

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) site layout system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  1. CLASSIFICATION OF THE MGR OFFSITE UTILITIES SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) offsite utilities system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  2. CLASSIFICATION OF THE MGR SITE OPERATIONS SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) site operations system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  3. CLASSIFICATION OF THE MGR SUBSURFACE VENTILATION SYSTEM

    International Nuclear Information System (INIS)

    R.J. Garrett

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) subsurface ventilation system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P7 ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  4. Classification of the MGR Assembly Transfer System

    International Nuclear Information System (INIS)

    S.E. Salzman

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) assembly transfer system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  5. CLASSIFICATION OF THE MGR SITE WATER SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) site water system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  6. CLASSIFICATION OF THE MGR EMERGENCY RESPONSE SYSTEM

    International Nuclear Information System (INIS)

    Zeigler, J.A.

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) emergency response system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P7 ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  7. CLASSIFICATION OF THE MGR SUBSURFACE EXCAVATION SYSTEM

    International Nuclear Information System (INIS)

    R. Garrett

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) subsurface excavation system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  8. Automotive System for Remote Surface Classification.

    Science.gov (United States)

    Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

    2017-04-01

    In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

  9. The new vitrinite classification (ICCP System 1994)

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-04-01

    This paper has been prepared by the International Committee for Coal and Organic Petrology (ICCP). Within the new vitrinite classification (ICCP System 1994) the maceral group vitrinite is divided into three subgroups, telovitrinite, detrovitrinite and gelovitrinite, which are each further sub-divided into two macerals. The dominant parameter for these newly ordered and in part newly defined sub-groups is the degree of destruction (degradation), whereas the macerals can be further distinguished by their morphological characteristics and their degree of gelificiation. The new system is furthermore related more closely to the huminite classification system still in use and a future one to be published by the ICCP. 69 refs., 2 figs., 2 tabs.

  10. Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

    Directory of Open Access Journals (Sweden)

    H Kimura

    2009-04-01

    Full Text Available In climate research, pressure patterns are often very important. When a climatologists need to know the days of a specific pressure pattern, for example "low pressure in Western areas of Japan and high pressure in Eastern areas of Japan (Japanese winter-type weather," they have to visually check a huge number of surface weather charts. To overcome this problem, we propose an automatic classification system using a support vector machine (SVM, which is a machine-learning method. We attempted to classify pressure patterns into two classes: "winter type" and "non-winter type". For both training datasets and test datasets, we used the JRA-25 dataset from 1981 to 2000. An experimental evaluation showed that our method obtained a greater than 0.8 F-measure. We noted that variations in results were based on differences in training datasets.

  11. Interrater reliability of a Pilates movement-based classification system.

    Science.gov (United States)

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

    2015-01-01

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

  12. Intelligent Computer Vision System for Automated Classification

    International Nuclear Information System (INIS)

    Jordanov, Ivan; Georgieva, Antoniya

    2010-01-01

    In this paper we investigate an Intelligent Computer Vision System applied for recognition and classification of commercially available cork tiles. The system is capable of acquiring and processing gray images using several feature generation and analysis techniques. Its functionality includes image acquisition, feature extraction and preprocessing, and feature classification with neural networks (NN). We also discuss system test and validation results from the recognition and classification tasks. The system investigation also includes statistical feature processing (features number and dimensionality reduction techniques) and classifier design (NN architecture, target coding, learning complexity and performance, and training with our own metaheuristic optimization method). The NNs trained with our genetic low-discrepancy search method (GLPτS) for global optimisation demonstrated very good generalisation abilities. In our view, the reported testing success rate of up to 95% is due to several factors: combination of feature generation techniques; application of Analysis of Variance (ANOVA) and Principal Component Analysis (PCA), which appeared to be very efficient for preprocessing the data; and use of suitable NN design and learning method.

  13. Complex Systems and Patterns

    NARCIS (Netherlands)

    Pieters, C.P.

    2008-01-01

    Although the term 'pattern' is often used in science, it is an elusive term and can have different dialectic meanings in various disciplines. Yet, the 'feel' for this term is fairly consistent; it usually requires little explanation to understand what a pattern is, and therefore it usually tends to

  14. Semantic Document Image Classification Based on Valuable Text Pattern

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2011-01-01

    Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

  15. Fuzzy Pattern Classification Based Detection of Faulty Electronic Fuel Control (EFC Valves Used in Diesel Engines

    Directory of Open Access Journals (Sweden)

    Umut Tugsal

    2014-05-01

    Full Text Available In this paper, we develop mathematical models of a rotary Electronic Fuel Control (EFC valve used in a Diesel engine based on dynamic performance test data and system identification methodology in order to detect the faulty EFC valves. The model takes into account the dynamics of the electrical and mechanical portions of the EFC valves. A recursive least squares (RLS type system identification methodology has been utilized to determine the transfer functions of the different types of EFC valves that were investigated in this study. Both in frequency domain and time domain methods have been utilized for this purpose. Based on the characteristic patterns exhibited by the EFC valves, a fuzzy logic based pattern classification method was utilized to evaluate the residuals and identify faulty EFC valves from good ones. The developed methodology has been shown to provide robust diagnostics for a wide range of EFC valves.

  16. Search techniques in intelligent classification systems

    CERN Document Server

    Savchenko, Andrey V

    2016-01-01

    A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

  17. Multivariate pattern classification reveals autonomic and experiential representations of discrete emotions.

    Science.gov (United States)

    Kragel, Philip A; Labar, Kevin S

    2013-08-01

    Defining the structural organization of emotions is a central unresolved question in affective science. In particular, the extent to which autonomic nervous system activity signifies distinct affective states remains controversial. Most prior research on this topic has used univariate statistical approaches in attempts to classify emotions from psychophysiological data. In the present study, electrodermal, cardiac, respiratory, and gastric activity, as well as self-report measures were taken from healthy subjects during the experience of fear, anger, sadness, surprise, contentment, and amusement in response to film and music clips. Information pertaining to affective states present in these response patterns was analyzed using multivariate pattern classification techniques. Overall accuracy for classifying distinct affective states was 58.0% for autonomic measures and 88.2% for self-report measures, both of which were significantly above chance. Further, examining the error distribution of classifiers revealed that the dimensions of valence and arousal selectively contributed to decoding emotional states from self-report, whereas a categorical configuration of affective space was evident in both self-report and autonomic measures. Taken together, these findings extend recent multivariate approaches to study emotion and indicate that pattern classification tools may improve upon univariate approaches to reveal the underlying structure of emotional experience and physiological expression. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  18. A system for heart sounds classification.

    Directory of Open Access Journals (Sweden)

    Grzegorz Redlarski

    Full Text Available The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases - one of the major causes of death around the globe - a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However, appropriate algorithms for auto-diagnosis systems of heart diseases that could be capable of distinguishing most of known pathological states have not been yet developed. The main issue is non-stationary character of phonocardiography signals as well as a wide range of distinguishable pathological heart sounds. In this paper a new heart sound classification technique, which might find use in medical diagnostic systems, is presented. It is shown that by combining Linear Predictive Coding coefficients, used for future extraction, with a classifier built upon combining Support Vector Machine and Modified Cuckoo Search algorithm, an improvement in performance of the diagnostic system, in terms of accuracy, complexity and range of distinguishable heart sounds, can be made. The developed system achieved accuracy above 93% for all considered cases including simultaneous identification of twelve different heart sound classes. The respective system is compared with four different major classification methods, proving its reliability.

  19. Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

    Science.gov (United States)

    Huntsberger, Terry

    2011-01-01

    The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

  20. Fingerprint classification using a simplified rule-set based on directional patterns and singularity features

    CSIR Research Space (South Africa)

    Dorasamy, K

    2015-07-01

    Full Text Available The use of directional patterns has recently received more attention in fingerprint classification. It provides a global representation of a fingerprint, by dividing it into homogeneous orientation partitions. With this technique, the challenge...

  1. Ethnicity prediction and classification from iris texture patterns: A survey on recent advances

    CSIR Research Space (South Africa)

    Mabuza-Hocquet, Gugulethu

    2017-03-01

    Full Text Available The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research...

  2. Explosives Classifications Tracking System User Manual

    Energy Technology Data Exchange (ETDEWEB)

    Genoni, R.P.

    1993-10-01

    The Explosives Classification Tracking System (ECTS) presents information and data for U.S. Department of Energy (DOE) explosives classifications of interest to EM-561, Transportation Management Division, other DOE facilities, and contractors. It is intended to be useful to the scientist, engineer, and transportation professional, who needs to classify or transport explosives. This release of the ECTS reflects upgrading of the software which provides the user with an environment that makes comprehensive retrieval of explosives related information quick and easy. Quarterly updates will be provided to the ECTS throughout its development in FY 1993 and thereafter. The ECTS is a stand alone, single user system that contains unclassified, publicly available information, and administrative information (contractor names, product descriptions, transmittal dates, EX-Numbers, etc.) information from many sources for non-decisional engineering and shipping activities. The data is the most up-to-date and accurate available to the knowledge of the system developer. The system is designed to permit easy revision and updating as new information and data become available. These, additions and corrections are welcomed by the developer. This user manual is intended to help the user install, understand, and operate the system so that the desired information may be readily obtained, reviewed, and reported.

  3. Pap-smear Benchmark Data For Pattern Classification

    DEFF Research Database (Denmark)

    Jantzen, Jan; Norup, Jonas; Dounias, Georgios

    2005-01-01

    This case study provides data and a baseline for comparing classification methods. The data consists of 917 images of Pap-smear cells, classified carefully by cyto-technicians and doctors. Each cell is described by 20 numerical features, and the cells fall into 7 classes. A basic data analysis in...

  4. Identification, classification and expression pattern analysis of sugarcane cysteine proteinases

    Directory of Open Access Journals (Sweden)

    Gustavo Coelho Correa

    2001-12-01

    Full Text Available Cysteine proteases are peptidyl hydrolyses dependent on a cysteine residue at the active center. The physical and chemical properties of cysteine proteases have been extensively characterized, but their precise biological functions have not yet been completely understood, although it is known that they are involved in a number of events such as protein turnover, cancer, germination, programmed cell death and senescence. Protein sequences from different cysteine proteinases, classified as members of the E.C.3.4.22 sub-sub-class, were used to perform a T-BLAST-n search on the Brazilian Sugarcane Expressed Sequence Tags project (SUCEST data bank. Sequence homology was found with 76 cluster sequences that corresponded to possible cysteine proteinases. The alignments of these SUCEST clusters with the sequence of cysteine proteinases of known origins provided important information about the classification and possible function of these sugarcane enzymes. Inferences about the expression pattern of each gene were made by direct correlation with the SUCEST cDNA libraries from which each cluster was derived. Since no previous reports of sugarcane cysteine proteinases genes exists, this study represents a first step in the study of new biochemical, physiological and biotechnological aspects of sugarcane cysteine proteases.Proteinases cisteínicas são peptidil-hidrolases dependentes de um resíduo de cisteína em seu sítio ativo. As propriedades físico-químicas destas proteinases têm sido amplamente caracterizadas, entretanto suas funções biológicas ainda não foram completamente elucidadas. Elas estão envolvidas em um grande número de eventos, tais como: processamento e degradação protéica, câncer, germinação, morte celular programada e processos de senescência. Diferentes proteinases cisteínicas, classificadas pelo Comitê de Nomenclatura da União Internacional de Bioquímica e Biologia Molecular (IUBMB como pertencentes à sub

  5. Extensions to the Speech Disorders Classification System (SDCS)

    Science.gov (United States)

    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.…

  6. Validation of potential classification criteria for systemic sclerosis.

    NARCIS (Netherlands)

    Johnson, S.R.; Fransen, J.; Khanna, D.; Baron, M.; Hoogen, F. van den; Medsger TA, J.r.; Peschken, C.A.; Carreira, P.E.; Riemekasten, G.; Tyndall, A.; Matucci-Cerinic, M.; Pope, J.E.

    2012-01-01

    OBJECTIVE: Classification criteria for systemic sclerosis (SSc; scleroderma) are being updated jointly by the American College of Rheumatology and European League Against Rheumatism. Potential items for classification were reduced to 23 using Delphi and nominal group techniques. We evaluated the

  7. Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

    International Nuclear Information System (INIS)

    Oliveira, D L L; Batista, V R; Duarte, Y A S; Nascimento, M Z; Neves, L A; Godoy, M F; Jacomini, R S; Arruda, P F F; Neto, D S

    2014-01-01

    In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis

  8. Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.

    Directory of Open Access Journals (Sweden)

    Neethu Robinson

    Full Text Available Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS for developing Brain-Computer Interface (BCI by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM, so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity.

  9. Automated recognition system for ELM classification in JET

    International Nuclear Information System (INIS)

    Duro, N.; Dormido, R.; Vega, J.; Dormido-Canto, S.; Farias, G.; Sanchez, J.; Vargas, H.; Murari, A.

    2009-01-01

    Edge localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. Considerable efforts are being devoted to understanding the physics behind this non-linear phenomenon. A first characterization of ELMs is usually their identification as type I or type III. An automated pattern recognition system has been developed in JET for off-line ELM recognition and classification. The empirical method presented in this paper analyzes each individual ELM instead of starting from a temporal segment containing many ELM bursts. The ELM recognition and isolation is carried out using three signals: Dα, line integrated electron density and stored diamagnetic energy. A reduced set of characteristics (such as diamagnetic energy drop, ELM period or Dα shape) has been extracted to build supervised and unsupervised learning systems for classification purposes. The former are based on support vector machines (SVM). The latter have been developed with hierarchical and K-means clustering methods. The success rate of the classification systems is about 98% for a database of almost 300 ELMs.

  10. Gender classification system in uncontrolled environments

    Science.gov (United States)

    Zeng, Pingping; Zhang, Yu-Jin; Duan, Fei

    2011-01-01

    Most face analysis systems available today perform mainly on restricted databases of images in terms of size, age, illumination. In addition, it is frequently assumed that all images are frontal and unconcealed. Actually, in a non-guided real-time supervision, the face pictures taken may often be partially covered and with head rotation less or more. In this paper, a special system supposed to be used in real-time surveillance with un-calibrated camera and non-guided photography is described. It mainly consists of five parts: face detection, non-face filtering, best-angle face selection, texture normalization, and gender classification. Emphases are focused on non-face filtering and best-angle face selection parts as well as texture normalization. Best-angle faces are figured out by PCA reconstruction, which equals to an implicit face alignment and results in a huge increase of the accuracy for gender classification. Dynamic skin model and a masked PCA reconstruction algorithm are applied to filter out faces detected in error. In order to fully include facial-texture and shape-outline features, a hybrid feature that is a combination of Gabor wavelet and PHoG (pyramid histogram of gradients) was proposed to equitable inner texture and outer contour. Comparative study on the effects of different non-face filtering and texture masking methods in the context of gender classification by SVM is reported through experiments on a set of UT (a company name) face images, a large number of internet images and CAS (Chinese Academy of Sciences) face database. Some encouraging results are obtained.

  11. A systematic framework to discover pattern for web spam classification

    OpenAIRE

    Jelodar, Hamed; Wang, Yongli; Yuan, Chi; Jiang, Xiaohui

    2017-01-01

    Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites. There are several methods and algorithms for detecting those websites, such as decision t...

  12. Nuclear reactors transients identification and classification system

    International Nuclear Information System (INIS)

    Bianchi, Paulo Henrique

    2008-01-01

    This work describes the study and test of a system capable to identify and classify transients in thermo-hydraulic systems, using a neural network technique of the self-organizing maps (SOM) type, with the objective of implanting it on the new generations of nuclear reactors. The technique developed in this work consists on the use of multiple networks to do the classification and identification of the transient states, being each network a specialist at one respective transient of the system, that compete with each other using the quantization error, that is a measure given by this type of neural network. This technique showed very promising characteristics that allow the development of new functionalities in future projects. One of these characteristics consists on the potential of each network, besides responding what transient is in course, could give additional information about that transient. (author)

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

    Science.gov (United States)

    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.

  14. Functional classifications for cerebral palsy: correlations between the gross motor function classification system (GMFCS), the manual ability classification system (MACS) and the communication function classification system (CFCS).

    Science.gov (United States)

    Compagnone, Eliana; Maniglio, Jlenia; Camposeo, Serena; Vespino, Teresa; Losito, Luciana; De Rinaldis, Marta; Gennaro, Leonarda; Trabacca, Antonio

    2014-11-01

    This study aimed to investigate a possible correlation between the gross motor function classification system-expanded and revised (GMFCS-E&R), the manual abilities classification system (MACS) and the communication function classification system (CFCS) functional levels in children with cerebral palsy (CP) by CP subtype. It was also geared to verify whether there is a correlation between these classification systems and intellectual functioning (IF) and parental socio-economic status (SES). A total of 87 children (47 males and 40 females, age range 4-18 years, mean age 8.9±4.2) were included in the study. A strong correlation was found between the three classifications: Level V of the GMFCS-E&R corresponds to Level V of the MACS (rs=0.67, p=0.001); the same relationship was found for the CFCS and the MACS (rs=0.73, p<0.001) and for the GMFCS-E&R and the CFCS (rs=0.61, p=0.001). The correlations between the IQ and the global functional disability profile were strong or moderate (GMFCS and IQ: rs=0.66, p=0.001; MACS and IQ: rs=0.58, p=0.001; CFCS and MACS: rs=0.65, p=0.001). The Kruskal-Wallis test was used to determine if there were differences between the GMFCS-E&R, the CFCS and the MACS by CP type. CP types showed different scores for the IQ level (Chi-square=8.59, df=2, p=0.014), the GMFCS-E&R (Chi-square=36.46, df=2, p<0.001), the CFCS (Chi-square=12.87, df=2, p=0.002), and the MACS Level (Chi-square=13.96, df=2, p<0.001) but no significant differences emerged for the SES (Chi-square=1.19, df=2, p=0.554). This study shows how the three functional classifications (GMFCS-E&R, CFCS and MACS) complement each other to provide a better description of the functional profile of CP. The systematic evaluation of the IQ can provide useful information about a possible future outcome for every functional level. The SES does not appear to affect functional profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Automatic classification of liver scintigram patterns by computer

    International Nuclear Information System (INIS)

    Csernay, L.; Csirik, J.

    1976-01-01

    The pattern recognition of projection is one of the problems in the automatic evaluation of scintigrams. An algorythm and a computerized programme with the ability to classify the shapes of liver scintigrams has been elaborated by the authors. The programme differentiates not only normal and pathologic basic forms, but performs the identification of nine normal forms described by the literature. To pattern recognition structural and local parameters of the picture were defined. A detailed mechanism of the programme is given in their reports. The programme can classify 55 out of 60 actual liver scintigrams, a result different from subjective definition obtained in 5 cases. These were normal pattern of liver scans. No wrong definition was obtained when classifying normal and pathologic patterns

  16. Classification system for oral submucous fibrosis

    Directory of Open Access Journals (Sweden)

    Chandramani Bhagvan More

    2012-01-01

    Full Text Available Oral submucous fibrosis (OSMF is a potentially malignant disorder (PMD and crippling condition of oral mucosa. It is a chronic insidious scarring disease of oral cavity, pharynx and upper digestive tract, characterized by progressive inability to open the mouth due to loss of elasticity and development of vertical fibrous bands in labial and buccal tissues. OSMF is a debilitating but preventable oral disease. It predominantly affects people of Southeast Asia and Indian subcontinent, where chewing of arecanut and its commercial preparation is high. Presence of fibrous bands is the main characteristic feature of OSMF. The present literature review provides the compilation of various classification system based on clinical and/or histopathological features of OSMF from several databases. The advantages and drawbacks of these classifications supersede each other, leading to perplexity. An attempt is made to provide and update the knowledge about this potentially malignant disorder to health care providers in order to help in early detection and treatment, thus reducing the mortality of oral cancer.

  17. Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach.

    Directory of Open Access Journals (Sweden)

    Andre F Marquand

    Full Text Available Progressive supranuclear palsy (PSP, multiple system atrophy (MSA and idiopathic Parkinson's disease (IPD can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs. An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i a subcortical motor network; (ii each of its component regions and (iii the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.

  18. Learning-induced pattern classification in a chaotic neural network

    International Nuclear Information System (INIS)

    Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki

    2012-01-01

    In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.

  19. Classification of pulsating flow patterns in curved pipes.

    Science.gov (United States)

    Tada, S; Oshima, S; Yamane, R

    1996-08-01

    The fully developed periodic laminar flow of incompressible Newtonian fluids through a pipe of circular cross section, which is coiled in a circle, was simulated numerically. The flow patterns are characterized by three parameters: the Womersley number Wo, the Dean number De, and the amplitude ratio beta. The effect of these parameters on the flow was studied in the range 2.19 secondary flow evolved with increasing Womersley number and Dean number is explained. The secondary flow patterns are classified into three main groups: the viscosity-dominated type, the inertia-dominated type, and the convection-dominated type. It was found that when the amplitude ratio of the volumetric flow rate is equal to 1.0, four to six vortices of the secondary flow appear at high Dean numbers, and the Lyne-type flow patterns disappear at beta > or = 0.50.

  20. General method of pattern classification using the two-domain theory

    Science.gov (United States)

    Rorvig, Mark E. (Inventor)

    1993-01-01

    Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

  1. Asynchronous data-driven classification of weapon systems

    International Nuclear Information System (INIS)

    Jin, Xin; Mukherjee, Kushal; Gupta, Shalabh; Ray, Asok; Phoha, Shashi; Damarla, Thyagaraju

    2009-01-01

    This communication addresses real-time weapon classification by analysis of asynchronous acoustic data, collected from microphones on a sensor network. The weapon classification algorithm consists of two parts: (i) feature extraction from time-series data using symbolic dynamic filtering (SDF), and (ii) pattern classification based on the extracted features using the language measure (LM) and support vector machine (SVM). The proposed algorithm has been tested on field data, generated by firing of two types of rifles. The results of analysis demonstrate high accuracy and fast execution of the pattern classification algorithm with low memory requirements. Potential applications include simultaneous shooter localization and weapon classification with soldier-wearable networked sensors. (rapid communication)

  2. Identification and classification of vertical chlorophyll patterns in the ...

    African Journals Online (AJOL)

    A type of artificial neural network called a self-organizing map (SOM) was then used on these four parameters to identify characteristic profiles. The analysis identified a continuum of chlorophyll patterns, from those with large surface peaks (>10 mg m-3) to those with smaller near-surface peaks (<2 mg m-3). The frequency of ...

  3. Texture Classification in Lung CT Using Local Binary Patterns

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs; Shaker, Saher B.; de Bruijne, Marleen

    2008-01-01

    the k nearest neighbor classifier with histogram similarity as distance measure. The proposed method is evaluated on a set of 168 regions of interest comprising normal tissue and different emphysema patterns, and compared to a filter bank based on Gaussian derivatives. The joint LBP and intensity...

  4. Pattern classification by memristive crossbar circuits using ex situ and in situ training

    Science.gov (United States)

    Alibart, Fabien; Zamanidoost, Elham; Strukov, Dmitri B.

    2013-06-01

    Memristors are memory resistors that promise the efficient implementation of synaptic weights in artificial neural networks. Whereas demonstrations of the synaptic operation of memristors already exist, the implementation of even simple networks is more challenging and has yet to be reported. Here we demonstrate pattern classification using a single-layer perceptron network implemented with a memrisitive crossbar circuit and trained using the perceptron learning rule by ex situ and in situ methods. In the first case, synaptic weights, which are realized as conductances of titanium dioxide memristors, are calculated on a precursor software-based network and then imported sequentially into the crossbar circuit. In the second case, training is implemented in situ, so the weights are adjusted in parallel. Both methods work satisfactorily despite significant variations in the switching behaviour of the memristors. These results give hope for the anticipated efficient implementation of artificial neuromorphic networks and pave the way for dense, high-performance information processing systems.

  5. Fabric Weave Pattern and Yarn Color Recognition and Classification Using a Deep ELM Network

    Directory of Open Access Journals (Sweden)

    Babar Khan

    2017-10-01

    Full Text Available Usually, a fabric weave pattern is recognized using methods which identify the warp floats and weft floats. Although these methods perform well for uniform or repetitive weave patterns, in the case of complex weave patterns, these methods become computationally complex and the classification error rates are comparatively higher. Furthermore, the fault-tolerance (invariance and stability (selectivity of the existing methods are still to be enhanced. We present a novel biologically-inspired method to invariantly recognize the fabric weave pattern (fabric texture and yarn color from the color image input. We proposed a model in which the fabric weave pattern descriptor is based on the HMAX model for computer vision inspired by the hierarchy in the visual cortex, the color descriptor is based on the opponent color channel inspired by the classical opponent color theory of human vision, and the classification stage is composed of a multi-layer (deep extreme learning machine. Since the weave pattern descriptor, yarn color descriptor, and the classification stage are all biologically inspired, we propose a method which is completely biologically plausible. The classification performance of the proposed algorithm indicates that the biologically-inspired computer-aided-vision models might provide accurate, fast, reliable and cost-effective solution to industrial automation.

  6. A new tree classification system for southern hardwoods

    Science.gov (United States)

    James S. Meadows; Daniel A. Jr. Skojac

    2008-01-01

    A new tree classification system for southern hardwoods is described. The new system is based on the Putnam tree classification system, originally developed by Putnam et al., 1960, Management ond inventory of southern hardwoods, Agriculture Handbook 181, US For. Sew., Washington, DC, which consists of four tree classes: (1) preferred growing stock, (2) reserve growing...

  7. A proposed data base system for detection, classification and ...

    African Journals Online (AJOL)

    A proposed data base system for detection, classification and location of fault on electricity company of Ghana electrical distribution system. Isaac Owusu-Nyarko, Mensah-Ananoo Eugine. Abstract. No Abstract. Keywords: database, classification of fault, power, distribution system, SCADA, ECG. Full Text: EMAIL FULL TEXT ...

  8. Determination of a radioactive waste classification system

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, J.J.; King, W.C.

    1978-03-01

    Several classification systems for radioactive wastes are reviewed and a system is developed that provides guidance on disposition of the waste. The system has three classes: high-level waste (HLW), which requires complete isolation from the biosphere for extended time periods; low-level waste (LLW), which requires containment for shorter periods; and innocuous waste (essentially nonradioactive), which may be disposed of by conventional means. The LLW/innocuous waste interface was not defined in this study. Reasonably conservative analytical scenarios were used to calculate that HLW/LLW interface level which would ensure compliance with the radiological exposure guidelines of 0.5 rem/y maximum exposure for a few isolated individuals and 0.005 rem/y for large population groups. The recommended HLW/LLW interface level for /sup 239/Pu or mixed transuranic waste is 1.0 ..mu..Ci/cm/sup 3/ of waste. Levels for other radionuclides are based upon a risk equivalent to this level. A cost-benefit analysis in accordance with as low as reasonably achievable (ALARA) and National Environmental Protection Act (NEPA) guidance indicates that further reduction of this HLW/LLL interface level would entail marginal costs greater than $10/sup 8/ per man-rem of dose avoided. The environmental effects considered were limited to those involving human exposure to radioactivity.

  9. Determination of a radioactive waste classification system

    International Nuclear Information System (INIS)

    Cohen, J.J.; King, W.C.

    1978-03-01

    Several classification systems for radioactive wastes are reviewed and a system is developed that provides guidance on disposition of the waste. The system has three classes: high-level waste (HLW), which requires complete isolation from the biosphere for extended time periods; low-level waste (LLW), which requires containment for shorter periods; and innocuous waste (essentially nonradioactive), which may be disposed of by conventional means. The LLW/innocuous waste interface was not defined in this study. Reasonably conservative analytical scenarios were used to calculate that HLW/LLW interface level which would ensure compliance with the radiological exposure guidelines of 0.5 rem/y maximum exposure for a few isolated individuals and 0.005 rem/y for large population groups. The recommended HLW/LLW interface level for 239 Pu or mixed transuranic waste is 1.0 μCi/cm 3 of waste. Levels for other radionuclides are based upon a risk equivalent to this level. A cost-benefit analysis in accordance with as low as reasonably achievable (ALARA) and National Environmental Protection Act (NEPA) guidance indicates that further reduction of this HLW/LLL interface level would entail marginal costs greater than $10 8 per man-rem of dose avoided. The environmental effects considered were limited to those involving human exposure to radioactivity

  10. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

    International Nuclear Information System (INIS)

    Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

    2010-01-01

    Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ('model signatures') constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer. Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways. We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that

  11. The classification of osteonecrosis in patients with cancer: validation of a new radiological classification system

    International Nuclear Information System (INIS)

    Niinimäki, T.; Niinimäki, J.; Halonen, J.; Hänninen, P.; Harila-Saari, A.; Niinimäki, R.

    2015-01-01

    Aim: To validate a new, non-joint-specific radiological classification system that is suitable regardless of the site of the osteonecrosis (ON) in patients with cancer. Material and methods: Critical deficiencies in the existing ON classification systems were identified and a new, non-joint-specific radiological classification system was developed. Seventy-two magnetic resonance imaging (MRI) images of patients with cancer and ON lesions were graded, and the validation of the new system was performed by assessing inter- and intra-observer reliability. Results: Intra-observer reliability of ON grading was good or very good, with kappa values of 0.79–0.86. Interobserver agreement was lower but still good, with kappa values of 0.62–0.77. Ninety-eight percent of all intra- or interobserver differences were within one grade. Interobserver reliability of assessing the location of ON was very good, with kappa values of 0.93–0.98. Conclusion: All the available radiological ON classification systems are joint specific. This limitation has spurred the development of multiple systems, which has led to the insufficient use of classifications in ON studies among patients with cancer. The introduced radiological classification system overcomes the problem of joint-specificity, was found to be reliable, and can be used to classify all ON lesions regardless of the affected site. - Highlights: • Patients with cancer may have osteonecrosis lesions at multiple sites. • There is no non-joint-specific osteonecrosis classification available. • We introduced a new non-joint-specific osteonecrosis classification. • The validation was performed by assessing inter- and intra-observer reliability. • The classification was reliable and could be used regardless of the affected site.

  12. Review of international classification systems for uranium resources

    International Nuclear Information System (INIS)

    Wang Wenyou

    2007-01-01

    The two primary classification systems for uranium resources in common use in the whole world are described. These uranium resource classification systems were developed under two distinct philosophies, it implies two very different processes, criteria, terms and definitions from which the systems evolved and were implemented. However, the two primary systems are all based on two considerations: the degree of geological confidence and the degree of economic attractiveness based on cost of producing the resource. The uranium resource classification methods currently used in most major uranium producing countries have all a bearing on the two aforesaid classification systems. The disparity exists only in the way or practice of classifying and estimating the uranium resources for reasons of different political and economical systems in various countries. The harmonization of these resource classification systems for uranium can be realized with the economic integration on a global scale. (authors)

  13. Risk-based classification system of nanomaterials

    International Nuclear Information System (INIS)

    Tervonen, Tommi; Linkov, Igor; Figueira, Jose Rui; Steevens, Jeffery; Chappell, Mark; Merad, Myriam

    2009-01-01

    Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes.

  14. Risk-based classification system of nanomaterials

    Energy Technology Data Exchange (ETDEWEB)

    Tervonen, Tommi, E-mail: t.p.tervonen@rug.n [University of Groningen, Faculty of Economics and Business (Netherlands); Linkov, Igor, E-mail: igor.linkov@usace.army.mi [US Army Research and Development Center (United States); Figueira, Jose Rui, E-mail: figueira@ist.utl.p [Technical University of Lisbon, CEG-IST, Centre for Management Studies, Instituto Superior Tecnico (Portugal); Steevens, Jeffery, E-mail: jeffery.a.steevens@usace.army.mil; Chappell, Mark, E-mail: mark.a.chappell@usace.army.mi [US Army Research and Development Center (United States); Merad, Myriam, E-mail: myriam.merad@ineris.f [INERIS BP 2, Societal Management of Risks Unit/Accidental Risks Division (France)

    2009-05-15

    Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes.

  15. Optimization of Classification Strategies of Acetowhite Temporal Patterns towards Improving Diagnostic Performance of Colposcopy

    Directory of Open Access Journals (Sweden)

    Karina Gutiérrez-Fragoso

    2017-01-01

    Full Text Available Efforts have been being made to improve the diagnostic performance of colposcopy, trying to help better diagnose cervical cancer, particularly in developing countries. However, improvements in a number of areas are still necessary, such as the time it takes to process the full digital image of the cervix, the performance of the computing systems used to identify different kinds of tissues, and biopsy sampling. In this paper, we explore three different, well-known automatic classification methods (k-Nearest Neighbors, Naïve Bayes, and C4.5, in addition to different data models that take full advantage of this information and improve the diagnostic performance of colposcopy based on acetowhite temporal patterns. Based on the ROC and PRC area scores, the k-Nearest Neighbors and discrete PLA representation performed better than other methods. The values of sensitivity, specificity, and accuracy reached using this method were 60% (95% CI 50–70, 79% (95% CI 71–86, and 70% (95% CI 60–80, respectively. The acetowhitening phenomenon is not exclusive to high-grade lesions, and we have found acetowhite temporal patterns of epithelial changes that are not precancerous lesions but that are similar to positive ones. These findings need to be considered when developing more robust computing systems in the future.

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

    Science.gov (United States)

    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.

  17. Ahmad's NPRT System: A Practical Innovation for Documenting Male Pattern Baldness

    OpenAIRE

    Ahmad, Muhammad

    2016-01-01

    Various classifications for male pattern baldness are mentioned in the literature. The 'Norwood's classification is the most commonly used but it has certain limitations. The new system has included 'three' extra features which were not mentioned in any other classification. It provides an opportunity to document the full and correct picture while documenting male pattern baldness. It also aids in assessing the treatment for various degrees of baldness.

  18. Ahmad's NPRT system: A practical innovation for documenting male pattern baldness

    Directory of Open Access Journals (Sweden)

    Muhammad Ahmad

    2016-01-01

    Full Text Available Various classifications for male pattern baldness are mentioned in the literature. The 'Norwood's classification is the most commonly used but it has certain limitations. The new system has included 'three' extra features which were not mentioned in any other classification. It provides an opportunity to document the full and correct picture while documenting male pattern baldness. It also aids in assessing the treatment for various degrees of baldness.

  19. 42 CFR 412.513 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ... LTC-DRG classification system provides a LTC-DRG, and an appropriate weighting factor, for those cases... intermediary decides that a different LTC-DRG should be assigned, the case will be reviewed by the appropriate... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412...

  20. Classification process in a text document recommender system

    Directory of Open Access Journals (Sweden)

    Dan MUNTEANU

    2005-12-01

    Full Text Available This paper presents the classification process in a recommender system used for textual documents taken especially from web. The system uses in the classification process a combination of content filters, event filters and collaborative filters and it uses implicit and explicit feedback for evaluating documents.

  1. A novel classification system for aging theories

    Directory of Open Access Journals (Sweden)

    Lucas Siqueira Trindade

    2013-03-01

    Full Text Available Theories of lifespan evolution are a source of confusion amongst aging researchers. After a century of aging research the dispute over whether the aging process is active or passive persists and a comprehensive and universally accepted theoretical model remains elusive. Evolutionary aging theories primarily dispute whether the aging process is exclusively adapted to favor the kin or exclusively non-adapted to favor the individual. Interestingly, contradictory data and theories supporting both exclusively programmed and exclusively non-programmed theories continue to grow. However, this is a false dichotomy; natural selection favors traits resulting in efficient reproduction whether they benefit the individual or the kin. Thus, to understand the evolution of aging, first we must understand the environment-dependent balance between the advantages and disadvantages of extended lifespan in the process of spreading genes. As described by distinct theories, different niches and environmental conditions confer on extended lifespan a range of fitness values varying from highly beneficial to highly detrimental. Here, we considered the range of fitness values for extended lifespan and develop a fitness-based framework for categorizing existing theories. We show that all theories can be classified into four basic types: secondary (beneficial, maladaptive (neutral, assisted death (detrimental and senemorphic aging (varying between beneficial to detrimental. We anticipate that this classification system will assist with understanding and interpreting aging/death by providing a way of considering theories as members of one of these classes rather than consideration of their individual details.

  2. Safety classification of nuclear power plant systems, structures and components

    International Nuclear Information System (INIS)

    1992-01-01

    The Safety Classification principles used for the systems, structures and components of a nuclear power plant are detailed in the guide. For classification, the nuclear power plant is divided into structural and operational units called systems. Every structure and component under control is included into some system. The Safety Classes are 1, 2 and 3 and the Class EYT (non-nuclear). Instructions how to assign each system, structure and component to an appropriate safety class are given in the guide. The guide applies to new nuclear power plants and to the safety classification of systems, structures and components designed for the refitting of old nuclear power plants. The classification principles and procedures applying to the classification document are also given

  3. Qualitative pattern classification of shear wave elastography for breast masses: how it correlates to quantitative measurements.

    Science.gov (United States)

    Yoon, Jung Hyun; Ko, Kyung Hee; Jung, Hae Kyoung; Lee, Jong Tae

    2013-12-01

    To determine the correlation of qualitative shear wave elastography (SWE) pattern classification to quantitative SWE measurements and whether it is representative of quantitative SWE values with similar performances. From October 2012 to January 2013, 267 breast masses of 236 women (mean age: 45.12 ± 10.54 years, range: 21-88 years) who had undergone ultrasonography (US), SWE, and subsequent biopsy were included. US BI-RADS final assessment and qualitative and quantitative SWE measurements were recorded. Correlation between pattern classification and mean elasticity, maximum elasticity, elasticity ratio and standard deviation were evaluated. Diagnostic performances of grayscale US, SWE parameters, and US combined to SWE values were calculated and compared. Of the 267 breast masses, 208 (77.9%) were benign and 59 (22.1%) were malignant. Pattern classifications significantly correlated with all quantitative SWE measurements, showing highest correlation with maximum elasticity, r = 0.721 (P0.05). Pattern classification shows high correlation to maximum stiffness and may be representative of quantitative SWE values. When combined to grayscale US, SWE improves specificity of US. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  4. Qualitative pattern classification of shear wave elastography for breast masses: How it correlates to quantitative measurements

    International Nuclear Information System (INIS)

    Yoon, Jung Hyun; Ko, Kyung Hee; Jung, Hae Kyoung; Lee, Jong Tae

    2013-01-01

    Objective: To determine the correlation of qualitative shear wave elastography (SWE) pattern classification to quantitative SWE measurements and whether it is representative of quantitative SWE values with similar performances. Methods: From October 2012 to January 2013, 267 breast masses of 236 women (mean age: 45.12 ± 10.54 years, range: 21–88 years) who had undergone ultrasonography (US), SWE, and subsequent biopsy were included. US BI-RADS final assessment and qualitative and quantitative SWE measurements were recorded. Correlation between pattern classification and mean elasticity, maximum elasticity, elasticity ratio and standard deviation were evaluated. Diagnostic performances of grayscale US, SWE parameters, and US combined to SWE values were calculated and compared. Results: Of the 267 breast masses, 208 (77.9%) were benign and 59 (22.1%) were malignant. Pattern classifications significantly correlated with all quantitative SWE measurements, showing highest correlation with maximum elasticity, r = 0.721 (P < 0.001). Sensitivity was significantly decreased in US combined to SWE measurements to grayscale US: 69.5–89.8% to 100.0%, while specificity was significantly improved: 62.5–81.7% to 13.9% (P < 0.001). Area under the ROC curve (A z ) did not show significant differences between grayscale US to US combined to SWE (P > 0.05). Conclusion: Pattern classification shows high correlation to maximum stiffness and may be representative of quantitative SWE values. When combined to grayscale US, SWE improves specificity of US

  5. Qualitative pattern classification of shear wave elastography for breast masses: How it correlates to quantitative measurements

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Jung Hyun, E-mail: lvjenny0417@gmail.com [Department of Radiology, CHA Bundang Medical Center, CHA University, School of Medicine (Korea, Republic of); Department of Radiology, Research Institute of Radiological Science, Yonsei University, College of Medicine (Korea, Republic of); Ko, Kyung Hee, E-mail: yourheeya@cha.ac.kr [Department of Radiology, CHA Bundang Medical Center, CHA University, School of Medicine (Korea, Republic of); Jung, Hae Kyoung, E-mail: AA40501@cha.ac.kr [Department of Radiology, CHA Bundang Medical Center, CHA University, School of Medicine (Korea, Republic of); Lee, Jong Tae, E-mail: jtlee@cha.ac.kr [Department of Radiology, CHA Bundang Medical Center, CHA University, School of Medicine (Korea, Republic of)

    2013-12-01

    Objective: To determine the correlation of qualitative shear wave elastography (SWE) pattern classification to quantitative SWE measurements and whether it is representative of quantitative SWE values with similar performances. Methods: From October 2012 to January 2013, 267 breast masses of 236 women (mean age: 45.12 ± 10.54 years, range: 21–88 years) who had undergone ultrasonography (US), SWE, and subsequent biopsy were included. US BI-RADS final assessment and qualitative and quantitative SWE measurements were recorded. Correlation between pattern classification and mean elasticity, maximum elasticity, elasticity ratio and standard deviation were evaluated. Diagnostic performances of grayscale US, SWE parameters, and US combined to SWE values were calculated and compared. Results: Of the 267 breast masses, 208 (77.9%) were benign and 59 (22.1%) were malignant. Pattern classifications significantly correlated with all quantitative SWE measurements, showing highest correlation with maximum elasticity, r = 0.721 (P < 0.001). Sensitivity was significantly decreased in US combined to SWE measurements to grayscale US: 69.5–89.8% to 100.0%, while specificity was significantly improved: 62.5–81.7% to 13.9% (P < 0.001). Area under the ROC curve (A{sub z}) did not show significant differences between grayscale US to US combined to SWE (P > 0.05). Conclusion: Pattern classification shows high correlation to maximum stiffness and may be representative of quantitative SWE values. When combined to grayscale US, SWE improves specificity of US.

  6. Update of the LIPID MAPS comprehensive classification system for lipids

    NARCIS (Netherlands)

    Fahy, E.; Subramaniam, S.; Murphy, R.C.; Nishijima, M.; Raetz, C.R.H.; Shimizu, T.; Spener, F.; van Meer, G.|info:eu-repo/dai/nl/068570368; Wakelam, M.J.O.; Dennis, E.A.

    2009-01-01

    In 2005, the International Lipid Classification and Nomenclature Committee under the sponsorship of the LIPID MAPS Consortium developed and established a “Comprehensive Classification System for Lipids” based on well-defined chemical and biochemical principles and using an ontology that is

  7. Calibration of a Plastic Classification System with the Ccw Model

    International Nuclear Information System (INIS)

    Barcala Riveira, J. M.; Fernandez Marron, J. L.; Alberdi Primicia, J.; Navarrete Marin, J. J.; Oller Gonzalez, J. C.

    2003-01-01

    This document describes the calibration of a plastic Classification system with the Ccw model (Classification by Quantum's built with Wavelet Coefficients). The method is applied to spectra of plastics usually present in domestic wastes. Obtained results are showed. (Author) 16 refs

  8. BIOCAT: a pattern recognition platform for customizable biological image classification and annotation.

    Science.gov (United States)

    Zhou, Jie; Lamichhane, Santosh; Sterne, Gabriella; Ye, Bing; Peng, Hanchuan

    2013-10-04

    Pattern recognition algorithms are useful in bioimage informatics applications such as quantifying cellular and subcellular objects, annotating gene expressions, and classifying phenotypes. To provide effective and efficient image classification and annotation for the ever-increasing microscopic images, it is desirable to have tools that can combine and compare various algorithms, and build customizable solution for different biological problems. However, current tools often offer a limited solution in generating user-friendly and extensible tools for annotating higher dimensional images that correspond to multiple complicated categories. We develop the BIOimage Classification and Annotation Tool (BIOCAT). It is able to apply pattern recognition algorithms to two- and three-dimensional biological image sets as well as regions of interest (ROIs) in individual images for automatic classification and annotation. We also propose a 3D anisotropic wavelet feature extractor for extracting textural features from 3D images with xy-z resolution disparity. The extractor is one of the about 20 built-in algorithms of feature extractors, selectors and classifiers in BIOCAT. The algorithms are modularized so that they can be "chained" in a customizable way to form adaptive solution for various problems, and the plugin-based extensibility gives the tool an open architecture to incorporate future algorithms. We have applied BIOCAT to classification and annotation of images and ROIs of different properties with applications in cell biology and neuroscience. BIOCAT provides a user-friendly, portable platform for pattern recognition based biological image classification of two- and three- dimensional images and ROIs. We show, via diverse case studies, that different algorithms and their combinations have different suitability for various problems. The customizability of BIOCAT is thus expected to be useful for providing effective and efficient solutions for a variety of biological

  9. Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

    Directory of Open Access Journals (Sweden)

    Junbao Zheng

    2012-03-01

    Full Text Available Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor as well as its parallel channels (inner factor. The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

  10. Similarity-dissimilarity plot for visualization of high dimensional data in biomedical pattern classification.

    Science.gov (United States)

    Arif, Muhammad

    2012-06-01

    In pattern classification problems, feature extraction is an important step. Quality of features in discriminating different classes plays an important role in pattern classification problems. In real life, pattern classification may require high dimensional feature space and it is impossible to visualize the feature space if the dimension of feature space is greater than four. In this paper, we have proposed a Similarity-Dissimilarity plot which can project high dimensional space to a two dimensional space while retaining important characteristics required to assess the discrimination quality of the features. Similarity-dissimilarity plot can reveal information about the amount of overlap of features of different classes. Separable data points of different classes will also be visible on the plot which can be classified correctly using appropriate classifier. Hence, approximate classification accuracy can be predicted. Moreover, it is possible to know about whom class the misclassified data points will be confused by the classifier. Outlier data points can also be located on the similarity-dissimilarity plot. Various examples of synthetic data are used to highlight important characteristics of the proposed plot. Some real life examples from biomedical data are also used for the analysis. The proposed plot is independent of number of dimensions of the feature space.

  11. New classification of geometric ventricular patterns in severe aortic stenosis: Could it be clinically useful?

    Science.gov (United States)

    Di Nora, Concetta; Cervesato, Eugenio; Cosei, Iulian; Ravasel, Andreea; Popescu, Bogdan A; Zito, Concetta; Carerj, Scipione; Antonini-Canterin, Francesco; Popescu, Andreea C

    2018-04-16

    In severe aortic stenosis, different left ventricle (LV) remodeling patterns as a response to pressure overload have distinct hemodynamic profiles, cardiac function, and outcomes. The most common classification considers LV relative wall thickness and LV mass index to create 4 different groups. A new classification including also end-diastolic volume index has been recently proposed. To describe the prevalence of the newly identified remodeling patterns in patients with severe aortic stenosis and to evaluate their clinical relevance according to symptoms. We analyzed 286 consecutive patients with isolated severe aortic stenosis. Current guidelines were used for echocardiographic evaluation. Symptoms were defined as the presence of angina, syncope, or NYHA class III-IV. The mean age was 75 ± 9 years, 156 patients (54%) were men, while 158 (55%) were symptomatic. According to the new classification, the most frequent remodeling pattern was concentric hypertrophy (57.3%), followed by mixed (18.9%) and dilated hypertrophy (8.4%). There were no patients with eccentric remodeling; only 4 patients had a normalLV geometry. Symptomatic patients showed significantly more mixed hypertrophy (P < .05), while the difference regarding the prevalence of the other patterns was not statistically significant. When we analyzed the distribution of the classic 4 patterns stratified by the presence of symptoms, however, we did not find a significant difference (P = .157). The new classification had refined the description of different cardiac geometric phenotypes that develop as a response to pressure overload. It might be superior to the classic 4 patterns in terms of association with symptoms. © 2018 Wiley Periodicals, Inc.

  12. Filter Bank Regularized Common Spatial Pattern Ensemble for Small Sample Motor Imagery Classification.

    Science.gov (United States)

    Park, Sang-Hoon; Lee, David; Lee, Sang-Goog

    2018-02-01

    For the last few years, many feature extraction methods have been proposed based on biological signals. Among these, the brain signals have the advantage that they can be obtained, even by people with peripheral nervous system damage. Motor imagery electroencephalograms (EEG) are inexpensive to measure, offer a high temporal resolution, and are intuitive. Therefore, these have received a significant amount of attention in various fields, including signal processing, cognitive science, and medicine. The common spatial pattern (CSP) algorithm is a useful method for feature extraction from motor imagery EEG. However, performance degradation occurs in a small-sample setting (SSS), because the CSP depends on sample-based covariance. Since the active frequency range is different for each subject, it is also inconvenient to set the frequency range to be different every time. In this paper, we propose the feature extraction method based on a filter bank to solve these problems. The proposed method consists of five steps. First, motor imagery EEG is divided by a using filter bank. Second, the regularized CSP (R-CSP) is applied to the divided EEG. Third, we select the features according to mutual information based on the individual feature algorithm. Fourth, parameter sets are selected for the ensemble. Finally, we classify using ensemble based on features. The brain-computer interface competition III data set IVa is used to evaluate the performance of the proposed method. The proposed method improves the mean classification accuracy by 12.34%, 11.57%, 9%, 4.95%, and 4.47% compared with CSP, SR-CSP, R-CSP, filter bank CSP (FBCSP), and SR-FBCSP. Compared with the filter bank R-CSP ( , ), which is a parameter selection version of the proposed method, the classification accuracy is improved by 3.49%. In particular, the proposed method shows a large improvement in performance in the SSS.

  13. The theory and practice of the Dewey Decimal Classification system

    CERN Document Server

    Satija, M P

    2013-01-01

    The Dewey Decimal Classification system (DDC) is the world's most popular library classification system. The 23rd edition of the DDC was published in 2011. This second edition of The Theory and Practice of the Dewey Decimal Classification System examines the history, management and technical aspects of the DDC up to its latest edition. The book places emphasis on explaining the structure and number building techniques in the DDC and reviews all aspects of subject analysis and number building by the most recent version of the DDC. A history of, and introduction to, the DDC is followed by subjec

  14. Development of a classification system for cup anemometers - CLASSCUP

    DEFF Research Database (Denmark)

    Friis Pedersen, Troels

    2003-01-01

    the objectives to quantify the errors associated with the use of cup anemometers, and to determine the requirements for an optimum design of a cup anemometer, and to develop a classification system forquantification of systematic errors of cup anemometers. The present report describes this proposed...... classification system. A classification method for cup anemometers has been developed, which proposes general external operational ranges to be used. Anormal category range connected to ideal sites of the IEC power performance standard was made, and another extended category range for complex terrain...... was proposed. General classification indices were proposed for all types of cup anemometers. As a resultof the classification, the cup anemometer will be assigned to a certain class: 0.5, 1, 2, 3 or 5 with corresponding intrinsic errors (%) as a vector instrument (3D) or as a horizontal instrument (2D...

  15. Reliability of a treatment-based classification system for subgrouping people with low back pain.

    Science.gov (United States)

    Henry, Sharon M; Fritz, Julie M; Trombley, Andrea R; Bunn, Janice Y

    2012-09-01

    Observational, cross-sectional reliability study. To examine the interrater reliability of novice raters in their use of the treatment-based classification (TBC) system for low back pain and to explore the patterns of disagreement in classification errors. Although the interrater reliability of individual test items in the TBC system is moderate to good, some error persists in classification decision making. Understanding which classification errors are common could direct further refinement of the TBC system. Using previously recorded patient data (n = 24), 12 novice raters classified patients according to the TBC schema. These classification results were combined with those of 7 other raters, allowing examination of the overall agreement using the kappa statistic, as well as agreement/disagreement among pairwise comparisons in classification assignments. A chi-square test examined differences in percent agreement between the novice and more experienced raters and differences in classification distributions between these 2 groups of raters. Among 12 novice raters, there was 80.9% agreement in the pairs of classification (κ = 0.62; 95% confidence interval: 0.59, 0.65) and an overall 75.5% agreement (κ = 0.57; 95% confidence interval: 0.55, 0.69) for the combined data set. Raters were least likely to agree on a classification of stabilization (77.5% agreement). The overall percentage of pairwise classification judgments that disagreed was 24.5%, with the most common disagreement being between manipulation and stabilization (11.0%), followed by a mismatch between stabilization and specific exercise (8.2%). Additional refinement is needed to reduce rater disagreement that persists in the TBC decision-making algorithm, particularly in the stabilization category. J Orthop Sports Phys Ther 2012;42(9):797-805, Epub 7 June 2012. doi:10.2519/jospt.2012.4078.

  16. Walking pattern classification and walking distance estimation algorithms using gait phase information.

    Science.gov (United States)

    Wang, Jeen-Shing; Lin, Che-Wei; Yang, Ya-Ting C; Ho, Yu-Jen

    2012-10-01

    This paper presents a walking pattern classification and a walking distance estimation algorithm using gait phase information. A gait phase information retrieval algorithm was developed to analyze the duration of the phases in a gait cycle (i.e., stance, push-off, swing, and heel-strike phases). Based on the gait phase information, a decision tree based on the relations between gait phases was constructed for classifying three different walking patterns (level walking, walking upstairs, and walking downstairs). Gait phase information was also used for developing a walking distance estimation algorithm. The walking distance estimation algorithm consists of the processes of step count and step length estimation. The proposed walking pattern classification and walking distance estimation algorithm have been validated by a series of experiments. The accuracy of the proposed walking pattern classification was 98.87%, 95.45%, and 95.00% for level walking, walking upstairs, and walking downstairs, respectively. The accuracy of the proposed walking distance estimation algorithm was 96.42% over a walking distance.

  17. Classification of Porcine Cranial Fracture Patterns Using a Fracture Printing Interface,.

    Science.gov (United States)

    Wei, Feng; Bucak, Serhat Selçuk; Vollner, Jennifer M; Fenton, Todd W; Jain, Anil K; Haut, Roger C

    2017-01-01

    Distinguishing between accidental and abusive head trauma in children can be difficult, as there is a lack of baseline data for pediatric cranial fracture patterns. A porcine head model has recently been developed and utilized in a series of studies to investigate the effects of impact energy level, surface type, and constraint condition on cranial fracture patterns. In the current study, an automated pattern recognition method, or a fracture printing interface (FPI), was developed to classify cranial fracture patterns that were associated with different impact scenarios documented in previous experiments. The FPI accurately predicted the energy level when the impact surface type was rigid. Additionally, the FPI was exceedingly successful in determining fractures caused by skulls being dropped with a high-level energy (97% accuracy). The FPI, currently developed on the porcine data, may in the future be transformed to the task of cranial fracture pattern classification for human infant skulls. © 2016 American Academy of Forensic Sciences.

  18. Cirse Quality Assurance Document and Standards for Classification of Complications: The Cirse Classification System.

    Science.gov (United States)

    Filippiadis, D K; Binkert, C; Pellerin, O; Hoffmann, R T; Krajina, A; Pereira, P L

    2017-08-01

    Interventional radiology provides a wide variety of vascular, nonvascular, musculoskeletal, and oncologic minimally invasive techniques aimed at therapy or palliation of a broad spectrum of pathologic conditions. Outcome data for these techniques are globally evaluated by hospitals, insurance companies, and government agencies targeting in a high-quality health care policy, including reimbursement strategies. To analyze effectively the outcome of a technique, accurate reporting of complications is necessary. Throughout the literature, numerous classification systems for complications grading and classification have been reported. Until now, there has been no method for uniform reporting of complications both in terms of definition and grading. The purpose of this CIRSE guideline is to provide a classification system of complications based on combining outcome and severity of sequelae. The ultimate challenge will be the adoption of this system by practitioners in different countries and health economies within the European Union and beyond.

  19. Unsupervised classification of neocortical activity patterns in neonatal and pre-juvenile rodents

    Directory of Open Access Journals (Sweden)

    Nicole eCichon

    2014-05-01

    Full Text Available Flexible communication within the brain, which relies on oscillatory activity, is not confined to adult neuronal networks. Experimental evidence has documented the presence of discontinuous patterns of oscillatory activity already during early development. Their highly variable spatial and time-frequency organization has been related to region specificity. However, it might be equally due to the absence of unitary criteria for classifying the early activity patterns, since they have been mainly characterized by visual inspection. Therefore, robust and unbiased methods for categorizing these discontinuous oscillations are needed for increasingly complex data sets from different labs. Here, we introduce an unsupervised detection and classification algorithm for the discontinuous activity patterns of rodents during early development. For this, firstly time windows with discontinuous oscillations vs. epochs of network silence were identified. In a second step, the major features of detected events were identified and processed by principal component analysis for deciding on their contribution to the classification of different oscillatory patterns. Finally, these patterns were categorized using an unsupervised cluster algorithm. The results were validated on manually characterized neonatal spindle bursts, which ubiquitously entrain neocortical areas of rats and mice, and prelimbic nested gamma spindle bursts. Moreover, the algorithm led to satisfactory results for oscillatory events that, due to increased similarity of their features, were more difficult to classify, e.g. during the pre-juvenile developmental period. Based on a linear classification, the optimal number of features to consider increased with the difficulty of detection. This algorithm allows the comparison of neonatal and pre-juvenile oscillatory patterns in their spatial and temporal organization. It might represent a first step for the unbiased elucidation of activity patterns

  20. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  1. Risk classification and uncertainty propagation for virtual water distribution systems

    International Nuclear Information System (INIS)

    Torres, Jacob M.; Brumbelow, Kelly; Guikema, Seth D.

    2009-01-01

    While the secrecy of real water distribution system data is crucial, it poses difficulty for research as results cannot be publicized. This data includes topological layouts of pipe networks, pump operation schedules, and water demands. Therefore, a library of virtual water distribution systems can be an important research tool for comparative development of analytical methods. A virtual city, 'Micropolis', has been developed, including a comprehensive water distribution system, as a first entry into such a library. This virtual city of 5000 residents is fully described in both geographic information systems (GIS) and EPANet hydraulic model frameworks. A risk classification scheme and Monte Carlo analysis are employed for an attempted water supply contamination attack. Model inputs to be considered include uncertainties in: daily water demand, seasonal demand, initial storage tank levels, the time of day a contamination event is initiated, duration of contamination event, and contaminant quantity. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. High uncertainties in exposure patterns lead to greater resources needed for more effective mitigation strategies.

  2. Should the South African red meat classification system be revised ...

    African Journals Online (AJOL)

    Soji, Zimkhitha

    2017-07-24

    Jul 24, 2017 ... standards used in the current South African classification system do not ..... South African beef is trimmed of visible fat, it compares favourably in terms of lipid ... structures, insufficient research on goat meat and technological ...

  3. Towards a regional beef carcass classification system for Southern ...

    African Journals Online (AJOL)

    Mapiye, C, Dr

    2017-05-15

    May 15, 2017 ... beef carcass grading and classification systems used in the region ..... between cattle breeds (genetic), pre-slaughter stress and growth- ..... Nguni cattle for example, owing to their adaptability (i.e. drought and heat tolerant,.

  4. A simplified classification system for partially edentulous spaces

    Directory of Open Access Journals (Sweden)

    Bhandari Aruna J, Bhandari Akshay J

    2014-04-01

    Full Text Available Background: There is no single universally employed classification system that will specify the exact edentulous situation. Several classification systems exist to group the situation and avoid confusion. Classifications based on edentulous areas, finished restored prostheses, type of direct retainers or fulcrum lines are there. Some are based depending on the placement of the implants. Widely accepted Kennedy Applegate classification does not give any idea about length, span or number of teeth missing. Rule 6 governing the application of Kennedy method states that additional edentulous areas are referred as modification number 1,2 etc. Rule 7 states that extent of the modification is not considered; only the number of edentulous areas is considered. Hence there is a need to modify the Kennedy –Applegate System. Aims: This new classification system is an attempt to modify Kennedy –Applegate System so as to give the exact idea about missing teeth, space, span, side and areas of partially edentulous arches. Methods and Material: This system will provide the information regarding Maxillary or Mandibular partially edentulous arches, Left or Right side, length of the edentulous space, number of teeth missing and whether there will be tooth borne or tooth – tissue borne prosthesis. Conclusions: This classification is easy for application, communication and will also help to design the removable cast partial denture in a better logical and systematic way. Also, this system will give the idea of the edentulous status and the number of missing teeth in fixed, hybrid or implant prosthesis.

  5. REAL-TIME INTELLIGENT MULTILAYER ATTACK CLASSIFICATION SYSTEM

    Directory of Open Access Journals (Sweden)

    T. Subbhulakshmi

    2014-01-01

    Full Text Available Intrusion Detection Systems (IDS takes the lion’s share of the current security infrastructure. Detection of intrusions is vital for initiating the defensive procedures. Intrusion detection was done by statistical and distance based methods. A threshold value is used in these methods to indicate the level of normalcy. When the network traffic crosses the level of normalcy then above which it is flagged as anomalous. When there are occurrences of new intrusion events which are increasingly a key part of system security, the statistical techniques cannot detect them. To overcome this issue, learning techniques are used which helps in identifying new intrusion activities in a computer system. The objective of the proposed system designed in this paper is to classify the intrusions using an Intelligent Multi Layered Attack Classification System (IMLACS which helps in detecting and classifying the intrusions with improved classification accuracy. The intelligent multi layered approach contains three intelligent layers. The first layer involves Binary Support Vector Machine classification for detecting the normal and attack. The second layer involves neural network classification to classify the attacks into classes of attacks. The third layer involves fuzzy inference system to classify the attacks into various subclasses. The proposed IMLACS can be able to detect an intrusion behavior of the networks since the system contains a three intelligent layer classification and better set of rules. Feature selection is also used to improve the time of detection. The experimental results show that the IMLACS achieves the Classification Rate of 97.31%.

  6. Validation of a new classification system for interprosthetic femoral fractures.

    Science.gov (United States)

    Pires, Robinson Esteves Santos; Silveira, Marcelo Peixoto Sena; Resende, Alessandra Regina da Silva; Junior, Egidio Oliveira Santana; Campos, Tulio Vinicius Oliveira; Santos, Leandro Emilio Nascimento; Balbachevsky, Daniel; Andrade, Marco Antônio Percope de

    2017-07-01

    Interprosthetic femoral fracture (IFF) incidence is gradually increasing as the population is progressively ageing. However, treatment remains challenging due to several contributing factors, such as poor bone quality, patient comorbidities, small interprosthetic fragment, and prostheses instability. An effective and specific classification system is essential to optimize treatment management, therefore diminishing complication rates. This study aims to validate a previously described classification system for interprosthetic femoral fractures. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Language of Czech Medical Reports and Classification Systems in Medicine

    Czech Academy of Sciences Publication Activity Database

    Přečková, Petra

    2010-01-01

    Roč. 6, č. 1 (2010), s. 58-65 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : terminology, * synonyms * classification systems * thesaurus * nomenclature * electronic health record * interoperability * semantic interoperability * cardiology * atherosclerosis Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/en/ejbi/article/53-en-language-of-czech-medical-reports- and -classification-systems-in-medicine.html

  8. Using Fractal and Local Binary Pattern Features for Classification of ECOG Motor Imagery Tasks Obtained from the Right Brain Hemisphere.

    Science.gov (United States)

    Xu, Fangzhou; Zhou, Weidong; Zhen, Yilin; Yuan, Qi; Wu, Qi

    2016-09-01

    The feature extraction and classification of brain signal is very significant in brain-computer interface (BCI). In this study, we describe an algorithm for motor imagery (MI) classification of electrocorticogram (ECoG)-based BCI. The proposed approach employs multi-resolution fractal measures and local binary pattern (LBP) operators to form a combined feature for characterizing an ECoG epoch recording from the right hemisphere of the brain. A classifier is trained by using the gradient boosting in conjunction with ordinary least squares (OLS) method. The fractal intercept, lacunarity and LBP features are extracted to classify imagined movements of either the left small finger or the tongue. Experimental results on dataset I of BCI competition III demonstrate the superior performance of our method. The cross-validation accuracy and accuracy is 90.6% and 95%, respectively. Furthermore, the low computational burden of this method makes it a promising candidate for real-time BCI systems.

  9. An intelligent condition monitoring system for on-line classification of machine tool wear

    Energy Technology Data Exchange (ETDEWEB)

    Pan, Fu; Hope, A D; Javed, M [Systems Engineering Faculty, Southampton Institute (United Kingdom)

    1998-12-31

    The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

  10. An intelligent condition monitoring system for on-line classification of machine tool wear

    Energy Technology Data Exchange (ETDEWEB)

    Fu Pan; Hope, A.D.; Javed, M. [Systems Engineering Faculty, Southampton Institute (United Kingdom)

    1997-12-31

    The development of intelligent tool condition monitoring systems is a necessary requirement for successful automation of manufacturing processes. This presentation introduces a tool wear monitoring system for milling operations. The system utilizes power, force, acoustic emission and vibration sensors to monitor tool condition comprehensively. Features relevant to tool wear are drawn from time and frequency domain signals and a fuzzy pattern recognition technique is applied to combine the multisensor information and provide reliable classification results of tool wear states. (orig.) 10 refs.

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

    Science.gov (United States)

    Matsubara, Takashi

    2017-01-01

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

  12. Investigating the Predictive Value of Functional MRI to Appetitive and Aversive Stimuli: A Pattern Classification Approach.

    Directory of Open Access Journals (Sweden)

    Ciara McCabe

    Full Text Available Dysfunctional neural responses to appetitive and aversive stimuli have been investigated as possible biomarkers for psychiatric disorders. However it is not clear to what degree these are separate processes across the brain or in fact overlapping systems. To help clarify this issue we used Gaussian process classifier (GPC analysis to examine appetitive and aversive processing in the brain.25 healthy controls underwent functional MRI whilst seeing pictures and receiving tastes of pleasant and unpleasant food. We applied GPCs to discriminate between the appetitive and aversive sights and tastes using functional activity patterns.The diagnostic accuracy of the GPC for the accuracy to discriminate appetitive taste from neutral condition was 86.5% (specificity = 81%, sensitivity = 92%, p = 0.001. If a participant experienced neutral taste stimuli the probability of correct classification was 92. The accuracy to discriminate aversive from neutral taste stimuli was 82.5% (specificity = 73%, sensitivity = 92%, p = 0.001 and appetitive from aversive taste stimuli was 73% (specificity = 77%, sensitivity = 69%, p = 0.001. In the sight modality, the accuracy to discriminate appetitive from neutral condition was 88.5% (specificity = 85%, sensitivity = 92%, p = 0.001, to discriminate aversive from neutral sight stimuli was 92% (specificity = 92%, sensitivity = 92%, p = 0.001, and to discriminate aversive from appetitive sight stimuli was 63.5% (specificity = 73%, sensitivity = 54%, p = 0.009.Our results demonstrate the predictive value of neurofunctional data in discriminating emotional and neutral networks of activity in the healthy human brain. It would be of interest to use pattern recognition techniques and fMRI to examine network dysfunction in the processing of appetitive, aversive and neutral stimuli in psychiatric disorders. Especially where problems with reward and punishment processing have been implicated in the pathophysiology of the disorder.

  13. Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people

    Science.gov (United States)

    Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Fengkui; Liu, Feixiang

    2017-09-01

    Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface (BCI) has shown its effectiveness for the control of rehabilitation devices designed for large body parts of the patients with neurologic impairments. In order to validate the feasibility of using EEG to decode the MI of a single index finger and constructing a BCI-enhanced finger rehabilitation system, we collected EEG data during right hand index finger MI and rest state for five healthy subjects and proposed a pattern recognition approach for classifying these two mental states. First, Fisher's linear discriminant criteria and power spectral density analysis were used to analyze the event-related desynchronization patterns. Second, both band power and approximate entropy were extracted as features. Third, aiming to eliminate the abnormal samples in the dictionary and improve the classification performance of the conventional sparse representation-based classification (SRC) method, we proposed a novel dictionary cleaned sparse representation-based classification (DCSRC) method for final classification. The experimental results show that the proposed DCSRC method gives better classification accuracies than SRC and an average classification accuracy of 81.32% is obtained for five subjects. Thus, it is demonstrated that single right hand index finger MI can be decoded from the sensorimotor rhythms, and the feature patterns of index finger MI and rest state can be well recognized for robotic exoskeleton initiation.

  14. A Classification Framework for Large-Scale Face Recognition Systems

    OpenAIRE

    Zhou, Ziheng; Deravi, Farzin

    2009-01-01

    This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an...

  15. Revised Soil Classification System for Coarse-Fine Mixtures

    KAUST Repository

    Park, Junghee; Santamarina, Carlos

    2017-01-01

    Soil classification systems worldwide capture great physical insight and enable geotechnical engineers to anticipate the properties and behavior of soils by grouping them into similar response categories based on their index properties. Yet gravimetric analysis and data trends summarized from published papers reveal critical limitations in soil group boundaries adopted in current systems. In particular, current classification systems fail to capture the dominant role of fines on the mechanical and hydraulic properties of soils. A revised soil classification system (RSCS) for coarse-fine mixtures is proposed herein. Definitions of classification boundaries use low and high void ratios that gravel, sand, and fines may attain. This research adopts emax and emin for gravels and sands, and three distinctive void ratio values for fines: soft eF|10  kPa and stiff eF|1  MPa for mechanical response (at effective stress 10 kPa and 1 MPa, respectively), and viscous λ⋅eF|LL for fluid flow control, where λ=2log(LL−25) and eF|LL is the void ratio at the liquid limit. For classification purposes, these void ratios can be estimated from index properties such as particle shape, the coefficient of uniformity, and the liquid limit. Analytically computed and data-adjusted boundaries are soil-specific, in contrast with the Unified Soil Classification System (USCS). Threshold fractions for mechanical control and for flow control are quite distinct in the proposed system. Therefore, the RSCS uses a two-name nomenclature whereby the first letters identify the component(s) that controls mechanical properties, followed by a letter (shown in parenthesis) that identifies the component that controls fluid flow. Sample charts in this paper and a Microsoft Excel facilitate the implementation of this revised classification system.

  16. Revised Soil Classification System for Coarse-Fine Mixtures

    KAUST Repository

    Park, Junghee

    2017-04-17

    Soil classification systems worldwide capture great physical insight and enable geotechnical engineers to anticipate the properties and behavior of soils by grouping them into similar response categories based on their index properties. Yet gravimetric analysis and data trends summarized from published papers reveal critical limitations in soil group boundaries adopted in current systems. In particular, current classification systems fail to capture the dominant role of fines on the mechanical and hydraulic properties of soils. A revised soil classification system (RSCS) for coarse-fine mixtures is proposed herein. Definitions of classification boundaries use low and high void ratios that gravel, sand, and fines may attain. This research adopts emax and emin for gravels and sands, and three distinctive void ratio values for fines: soft eF|10  kPa and stiff eF|1  MPa for mechanical response (at effective stress 10 kPa and 1 MPa, respectively), and viscous λ⋅eF|LL for fluid flow control, where λ=2log(LL−25) and eF|LL is the void ratio at the liquid limit. For classification purposes, these void ratios can be estimated from index properties such as particle shape, the coefficient of uniformity, and the liquid limit. Analytically computed and data-adjusted boundaries are soil-specific, in contrast with the Unified Soil Classification System (USCS). Threshold fractions for mechanical control and for flow control are quite distinct in the proposed system. Therefore, the RSCS uses a two-name nomenclature whereby the first letters identify the component(s) that controls mechanical properties, followed by a letter (shown in parenthesis) that identifies the component that controls fluid flow. Sample charts in this paper and a Microsoft Excel facilitate the implementation of this revised classification system.

  17. Classification system of the mineral reserves and resources of Ukraine

    International Nuclear Information System (INIS)

    Lovinyukov, V.I.

    1998-01-01

    This paper describes the system used to classify the resources and reserves of all minerals and fuels in Ukraine. The classification system is part of an official procedure determined by the Ukrainian State Commission on Reserves. Following preparation of resource estimates the results are registered with the State, which maintains an official inventory of all mineral resources. This paper compares the Ukrainian system to, and finds it compatible with the United Nations International Framework of resource classification. The UN system is based on economics of production and mineability. (author)

  18. Classification system of the mineral reserves and resources of Ukraine

    International Nuclear Information System (INIS)

    Lovyunikov, V.I.

    1997-01-01

    This paper describes the system used to classify the resources and reserves of all minerals and fuels in Ukraine. The classification system is part of an official procedures determined by the Ukrainian State Commission on Reserves. Following preparation of resource estimates the results are registered with the State, which maintains an official inventory of all mineral resources. This paper compares the Ukrainian system to, and finds it compatible with the United Nations International Framework of resources classification. The UN system is based on economics of production and mineability. (author). 1 tab

  19. Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification

    Science.gov (United States)

    Dai, Mengxi; Liu, Shucong; Zhang, Pengju

    2018-01-01

    Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods. PMID:29743934

  20. High-speed classification of coherent X-ray diffraction patterns on the K computer for high-resolution single biomolecule imaging

    Energy Technology Data Exchange (ETDEWEB)

    Tokuhisa, Atsushi [RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Arai, Junya [The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Joti, Yasumasa [JASRI, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); Ohno, Yoshiyuki; Kameyama, Toyohisa; Yamamoto, Keiji; Hatanaka, Masayuki; Gerofi, Balazs; Shimada, Akio; Kurokawa, Motoyoshi; Shoji, Fumiyoshi [RIKEN Advanced Institute for Computational Science, 7-1-26 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047 (Japan); Okada, Kensuke [RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Sugimoto, Takashi [JASRI, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan); Yamaga, Mitsuhiro; Tanaka, Ryotaro [RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Yokokawa, Mitsuo; Hori, Atsushi [RIKEN Advanced Institute for Computational Science, 7-1-26 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047 (Japan); Ishikawa, Yutaka, E-mail: ishikawa@is.s.u-tokyo.ac.jp [The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 (Japan); Hatsui, Takaki, E-mail: ishikawa@is.s.u-tokyo.ac.jp [RIKEN SPring-8 Center, 1-1-1 Kouto, Sayo-cho, Sayo-gun, Hyogo 679-5148 (Japan); Go, Nobuhiro [Japan Atomic Energy Agency, 8-1-7 Umemidai, Kizugawa, Kyoto 619-0215 (Japan)

    2013-11-01

    A code with an algorithm for high-speed classification of X-ray diffraction patterns has been developed. Results obtained for a set of 1 × 10{sup 6} simulated diffraction patterns are also reported. Single-particle coherent X-ray diffraction imaging using an X-ray free-electron laser has the potential to reveal the three-dimensional structure of a biological supra-molecule at sub-nanometer resolution. In order to realise this method, it is necessary to analyze as many as 1 × 10{sup 6} noisy X-ray diffraction patterns, each for an unknown random target orientation. To cope with the severe quantum noise, patterns need to be classified according to their similarities and average similar patterns to improve the signal-to-noise ratio. A high-speed scalable scheme has been developed to carry out classification on the K computer, a 10PFLOPS supercomputer at RIKEN Advanced Institute for Computational Science. It is designed to work on the real-time basis with the experimental diffraction pattern collection at the X-ray free-electron laser facility SACLA so that the result of classification can be feedback for optimizing experimental parameters during the experiment. The present status of our effort developing the system and also a result of application to a set of simulated diffraction patterns is reported. About 1 × 10{sup 6} diffraction patterns were successfully classificatied by running 255 separate 1 h jobs in 385-node mode.

  1. Development of an intelligent system for ultrasonic flaw classification in weldments

    International Nuclear Information System (INIS)

    Song, Sung-Jin; Kim, Hak-Joon; Cho, Hyeon

    2002-01-01

    Even though ultrasonic pattern recognition is considered as the most effective and promising approach to flaw classification in weldments, its application to the realistic field inspection is still very limited due to the crucial barriers in cost, time and reliability. To reduce such barriers, previously we have proposed an intelligent system approach that consisted of the following four ingredients: (1) a PC-based ultrasonic testing (PC-UT) system; (2) an effective invariant ultrasonic flaw classification algorithm; (3) an intelligent flaw classification software; and (4) a database with abundant experimental flaw signals. In the present work, for performing the ultrasonic flaw classification in weldments in a real-time fashion in many real word situations, we develop an intelligent system, which is called the 'Intelligent Ultrasonic Evaluation System (IUES)' by the integration of the above four ingredients into a single, unified system. In addition, for the improvement of classification accuracy of flaws, especially slag inclusions, we expand the feature set by adding new informative features, and demonstrate the enhanced performance of the IUES with flaw signals in the database constructed previously. And then, to take care of the increased redundancy in the feature set due to the addition of features, we also propose two efficient schemes for feature selection: the forward selection with trial and error, and the forward selection with criteria of the error probability and the linear correlation coefficients of individual features

  2. A support vector machine integrated system for the classification of operation anomalies in nuclear components and systems

    International Nuclear Information System (INIS)

    Rocco S, Claudio M.; Zio, Enrico

    2007-01-01

    A support vector machine (SVM) approach to the classification of transients in nuclear power plants is presented. SVM is a machine-learning algorithm that has been successfully used in pattern recognition for cluster analysis. In the present work, single- and multiclass SVM are combined into a hierarchical structure for distinguishing among transients in nuclear systems on the basis of measured data. An example of application of the approach is presented with respect to the classification of anomalies and malfunctions occurring in the feedwater system of a boiling water reactor. The data used in the example are provided by the HAMBO simulator of the Halden Reactor Project

  3. Towards a consensus on a hearing preservation classification system.

    Science.gov (United States)

    Skarzynski, Henryk; van de Heyning, P; Agrawal, S; Arauz, S L; Atlas, M; Baumgartner, W; Caversaccio, M; de Bodt, M; Gavilan, J; Godey, B; Green, K; Gstoettner, W; Hagen, R; Han, D M; Kameswaran, M; Karltorp, E; Kompis, M; Kuzovkov, V; Lassaletta, L; Levevre, F; Li, Y; Manikoth, M; Martin, J; Mlynski, R; Mueller, J; O'Driscoll, M; Parnes, L; Prentiss, S; Pulibalathingal, S; Raine, C H; Rajan, G; Rajeswaran, R; Rivas, J A; Rivas, A; Skarzynski, P H; Sprinzl, G; Staecker, H; Stephan, K; Usami, S; Yanov, Y; Zernotti, M E; Zimmermann, K; Lorens, A; Mertens, G

    2013-01-01

    The comprehensive Hearing Preservation classification system presented in this paper is suitable for use for all cochlear implant users with measurable pre-operative residual hearing. If adopted as a universal reporting standard, as it was designed to be, it should prove highly beneficial by enabling future studies to quickly and easily compare the results of previous studies and meta-analyze their data. To develop a comprehensive Hearing Preservation classification system suitable for use for all cochlear implant users with measurable pre-operative residual hearing. The HEARRING group discussed and reviewed a number of different propositions of a HP classification systems and reviewed critical appraisals to develop a qualitative system in accordance with the prerequisites. The Hearing Preservation Classification System proposed herein fulfills the following necessary criteria: 1) classification is independent from users' initial hearing, 2) it is appropriate for all cochlear implant users with measurable pre-operative residual hearing, 3) it covers the whole range of pure tone average from 0 to 120 dB; 4) it is easy to use and easy to understand.

  4. CLASSIFICATION OF THE MGR WASTE EMPLACEMENT/RETRIEVAL SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    2000-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) waste emplacement/retrieved system structures, systems and components (SSCs) performed by the MGR Preclosure Safety and Systems Engineering Section. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 2000). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, Quality Assurance Requirements and Description (QARD) (DOE 2000). This QA classification incorporates the current MGR design and the results of the ''Design Basis Event Frequency and Dose Calculation for Site Recommendation'' (CRWMS M andO 2000a). The content and technical approach of this analysis is in accordance with the development plan ''QA Classification of MGR Structures, Systems, and Components'' (CRWMS M andO 1999b)

  5. Comparison of models of automatic classification of textural patterns of mineral presents in Colombian coals

    International Nuclear Information System (INIS)

    Lopez Carvajal, Jaime; Branch Bedoya, John Willian

    2005-01-01

    The automatic classification of objects is a very interesting approach under several problem domains. This paper outlines some results obtained under different classification models to categorize textural patterns of minerals using real digital images. The data set used was characterized by a small size and noise presence. The implemented models were the Bayesian classifier, Neural Network (2-5-1), support vector machine, decision tree and 3-nearest neighbors. The results after applying crossed validation show that the Bayesian model (84%) proved better predictive capacity than the others, mainly due to its noise robustness behavior. The neuronal network (68%) and the SVM (67%) gave promising results, because they could be improved increasing the data amount used, while the decision tree (55%) and K-NN (54%) did not seem to be adequate for this problem, because of their sensibility to noise

  6. Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System.

    Science.gov (United States)

    de Moura, Karina de O A; Balbinot, Alexandre

    2018-05-01

    A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method

  7. Predicting decisions in human social interactions using real-time fMRI and pattern classification.

    Science.gov (United States)

    Hollmann, Maurice; Rieger, Jochem W; Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes

    2011-01-01

    Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

  8. Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

    Science.gov (United States)

    Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

    2018-04-01

    Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

  9. Predicting decisions in human social interactions using real-time fMRI and pattern classification.

    Directory of Open Access Journals (Sweden)

    Maurice Hollmann

    Full Text Available Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

  10. Multivariate Pattern Classification of Facial Expressions Based on Large-Scale Functional Connectivity.

    Science.gov (United States)

    Liang, Yin; Liu, Baolin; Li, Xianglin; Wang, Peiyuan

    2018-01-01

    It is an important question how human beings achieve efficient recognition of others' facial expressions in cognitive neuroscience, and it has been identified that specific cortical regions show preferential activation to facial expressions in previous studies. However, the potential contributions of the connectivity patterns in the processing of facial expressions remained unclear. The present functional magnetic resonance imaging (fMRI) study explored whether facial expressions could be decoded from the functional connectivity (FC) patterns using multivariate pattern analysis combined with machine learning algorithms (fcMVPA). We employed a block design experiment and collected neural activities while participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise). Both static and dynamic expression stimuli were included in our study. A behavioral experiment after scanning confirmed the validity of the facial stimuli presented during the fMRI experiment with classification accuracies and emotional intensities. We obtained whole-brain FC patterns for each facial expression and found that both static and dynamic facial expressions could be successfully decoded from the FC patterns. Moreover, we identified the expression-discriminative networks for the static and dynamic facial expressions, which span beyond the conventional face-selective areas. Overall, these results reveal that large-scale FC patterns may also contain rich expression information to accurately decode facial expressions, suggesting a novel mechanism, which includes general interactions between distributed brain regions, and that contributes to the human facial expression recognition.

  11. Prediction of pediatric unipolar depression using multiple neuromorphometric measurements: a pattern classification approach.

    Science.gov (United States)

    Wu, Mon-Ju; Wu, Hanjing Emily; Mwangi, Benson; Sanches, Marsal; Selvaraj, Sudhakar; Zunta-Soares, Giovana B; Soares, Jair C

    2015-03-01

    Diagnosis of pediatric neuropsychiatric disorders such as unipolar depression is largely based on clinical judgment - without objective biomarkers to guide diagnostic process and subsequent therapeutic interventions. Neuroimaging studies have previously reported average group-level neuroanatomical differences between patients with pediatric unipolar depression and healthy controls. In the present study, we investigated the utility of multiple neuromorphometric indices in distinguishing pediatric unipolar depression patients from healthy controls at an individual subject level. We acquired structural T1-weighted scans from 25 pediatric unipolar depression patients and 26 demographically matched healthy controls. Multiple neuromorphometric indices such as cortical thickness, volume, and cortical folding patterns were obtained. A support vector machine pattern classification model was 'trained' to distinguish individual subjects with pediatric unipolar depression from healthy controls based on multiple neuromorphometric indices and model predictive validity (sensitivity and specificity) calculated. The model correctly identified 40 out of 51 subjects translating to 78.4% accuracy, 76.0% sensitivity and 80.8% specificity, chi-square p-value = 0.000049. Volumetric and cortical folding abnormalities in the right thalamus and right temporal pole respectively were most central in distinguishing individual patients with pediatric unipolar depression from healthy controls. These findings provide evidence that a support vector machine pattern classification model using multiple neuromorphometric indices may qualify as diagnostic marker for pediatric unipolar depression. In addition, our results identified the most relevant neuromorphometric features in distinguishing PUD patients from healthy controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Towards a regional beef carcass classification system for Southern ...

    African Journals Online (AJOL)

    This is partly because the current beef carcass grading and classification systems used in the region value inappropriately carcasses from slow-maturing indigenous cattle breeds that are ideally suited to being marketed off natural pasture. The existing systems use carcass yield and quality attributes, but do not predict ...

  13. Application of Pattern Recognition Techniques to the Classification of Full-Term and Preterm Infant Cry.

    Science.gov (United States)

    Orlandi, Silvia; Reyes Garcia, Carlos Alberto; Bandini, Andrea; Donzelli, Gianpaolo; Manfredi, Claudia

    2016-11-01

    Scientific and clinical advances in perinatology and neonatology have enhanced the chances of survival of preterm and very low weight neonates. Infant cry analysis is a suitable noninvasive complementary tool to assess the neurologic state of infants particularly important in the case of preterm neonates. This article aims at exploiting differences between full-term and preterm infant cry with robust automatic acoustical analysis and data mining techniques. Twenty-two acoustical parameters are estimated in more than 3000 cry units from cry recordings of 28 full-term and 10 preterm newborns. Feature extraction is performed through the BioVoice dedicated software tool, developed at the Biomedical Engineering Lab, University of Firenze, Italy. Classification and pattern recognition is based on genetic algorithms for the selection of the best attributes. Training is performed comparing four classifiers: Logistic Curve, Multilayer Perceptron, Support Vector Machine, and Random Forest and three different testing options: full training set, 10-fold cross-validation, and 66% split. Results show that the best feature set is made up by 10 parameters capable to assess differences between preterm and full-term newborns with about 87% of accuracy. Best results are obtained with the Random Forest method (receiver operating characteristic area, 0.94). These 10 cry features might convey important additional information to assist the clinical specialist in the diagnosis and follow-up of possible delays or disorders in the neurologic development due to premature birth in this extremely vulnerable population of patients. The proposed approach is a first step toward an automatic infant cry recognition system for fast and proper identification of risk in preterm babies. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  14. Classification system for reporting events involving human malfunctions

    International Nuclear Information System (INIS)

    Rasmussen, J.; Pedersen, O.M.; Mancini, G.; Carnino, A.; Griffon, M.; Gagnolet, P.

    1981-03-01

    The report describes a set of categories for reporting industrial incidents and events involving human malfunction. The classification system aims at ensuring information adequate for improvement of human work situations and man-machine interface systems and for attempts to quantify ''human error'' rates. The classification system has a multifacetted non-hierarchial structure and its compatibility with Ispra's ERDS classification is described. The collection of the information in general and for quantification purposes are discussed. 24 categories, 12 of which being human factors oriented, are listed with their respective subcategories, and comments are given. Underlying models of human data processes and their typical malfunctions and of a human decision sequence are described. (author)

  15. Classification system for reporting events involving human malfunctions

    International Nuclear Information System (INIS)

    Rasmussen, J.; Pedersen, O.M.; Mancini, G.

    1981-01-01

    The report describes a set of categories for reporting industrial incidents and events involving human malfunction. The classification system aims at ensuring information adequate for improvement of human work situations and man-machine interface systems and for attempts to quantify ''human error'' rates. The classification system has a multifacetted non-hierarchical structure and its compatibility with Ispra's ERDS classification is described. The collection of the information in general and for quantification purposes are discussed. 24 categories, 12 of which being human factors-oriented, are listed with their respective subcategories, and comments are given. Underlying models of human data process and their typical malfuntions and of a human decision sequence are described. The work reported is a joint contribution to the CSNI Group of Experts on Human Error Data and Assessment

  16. Modified Mahalanobis Taguchi System for Imbalance Data Classification

    Directory of Open Access Journals (Sweden)

    Mahmoud El-Banna

    2017-01-01

    Full Text Available The Mahalanobis Taguchi System (MTS is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS. To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs, Naive Bayes (NB, Probabilistic Mahalanobis Taguchi Systems (PTM, Synthetic Minority Oversampling Technique (SMOTE, Adaptive Conformal Transformation (ACT, Kernel Boundary Alignment (KBA, Hidden Naive Bayes (HNB, and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA.

  17. Classification system for reporting events involving human malfunctions

    DEFF Research Database (Denmark)

    Rasmussen, Jens; Pedersen, O.M.; Mancini, G.

    1981-01-01

    The report describes a set of categories for reporting indus-trial incidents and events involving human malfunction. The classification system aims at ensuring information adequate for improvement of human work situations and man-machine interface systems and for attempts to quantify "human error......" rates. The classification system has a multifacetted non-hierarchical struc-ture and its compatibility with Isprals ERDS classification is described. The collection of the information in general and for quantification purposes are discussed. 24 categories, 12 of which being human factors oriented......, are listed with their respective subcategories, and comments are given. Underlying models of human data processes and their typical malfunc-tions and of a human decision sequence are described....

  18. A classification system for tableting behaviors of binary powder mixtures

    Directory of Open Access Journals (Sweden)

    Changquan Calvin Sun

    2016-08-01

    Full Text Available The ability to predict tableting properties of a powder mixture from individual components is of both fundamental and practical importance to the efficient formulation development of tablet products. A common tableting classification system (TCS of binary powder mixtures facilitates the systematic development of new knowledge in this direction. Based on the dependence of tablet tensile strength on weight fraction in a binary mixture, three main types of tableting behavior are identified. Each type is further divided to arrive at a total of 15 sub-classes. The proposed classification system lays a framework for a better understanding of powder interactions during compaction. Potential applications and limitations of this classification system are discussed.

  19. CLASSIFICATION OF THE MGR WASTE HANDLING BUILDING VENTILATION SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    2000-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) waste handling building ventilation system structures, systems and components (SSCs) performed by the MGR Preclosure Safety and Systems Engineering Section. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 2000). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 2000). This QA classification incorporates the current MGR design and the results of the ''Design Basis Event Frequency and Dose Calculation for Site Recommendation'' (CRWMS M andO 2000a) and ''Bounding Individual Category 1 Design Basis Event Dose Calculation to Support Quality Assurance Classification'' (Gwyn 2000)

  20. Modified Mahalanobis Taguchi System for Imbalance Data Classification

    Science.gov (United States)

    2017-01-01

    The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

  1. Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.

    Science.gov (United States)

    Mao, Keming; Deng, Zhuofu

    2016-01-01

    This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

  2. Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

    Directory of Open Access Journals (Sweden)

    Keming Mao

    2016-01-01

    Full Text Available This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier.

  3. A proposal of criteria for the classification of systemic sclerosis.

    Science.gov (United States)

    Nadashkevich, Oleg; Davis, Paul; Fritzler, Marvin J

    2004-11-01

    Sensitive and specific criteria for the classification of systemic sclerosis are required by clinicians and investigators to achieve higher quality clinical studies and approaches to therapy. A clinical study of systemic sclerosis patients in Europe and Canada led to a set of criteria that achieve high sensitivity and specificity. Both clinical and laboratory investigations of patients with systemic sclerosis, related conditions and diseases with clinical features that can be mistaken as part of the systemic sclerosis spectrum were undertaken. Laboratory investigations included the detection of autoantibodies to centromere proteins, Scl-70 (topoisomerase I), and fibrillarin (U3-RNP). Based on the investigation of 269 systemic sclerosis patients and 720 patients presenting with related and confounding conditions, the following set of criteria for the classification of systemic sclerosis was proposed: 1) autoantibodies to: centromere proteins, Scl-70 (topo I), fibrillarin; 2) bibasilar pulmonary fibrosis; 3) contractures of the digital joints or prayer sign; 4) dermal thickening proximal to the wrists; 5) calcinosis cutis; 6) Raynaud's phenomenon; 7) esophageal distal hypomotility or reflux-esophagitis; 8) sclerodactyly or non-pitting digital edema; 9) teleangiectasias. The classification of definite SSc requires at least three of the above criteria. Criteria for the classification of systemic sclerosis have been proposed. Preliminary testing has defined the sensitivity and specificity of these criteria as high as 99% and 100%, respectively. Testing and validation of the proposed criteria by other clinical centers is required.

  4. A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

    Science.gov (United States)

    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.

  5. Intelligent Decision Support System for Bank Loans Risk Classification

    Institute of Scientific and Technical Information of China (English)

    杨保安; 马云飞; 俞莲

    2001-01-01

    Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

  6. Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

    Directory of Open Access Journals (Sweden)

    Oguzhan Begik

    2017-07-01

    Full Text Available Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA, a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian compared to normal tissues. Using machine-learning techniques, we further defined specific subsets of APA events to efficiently classify cancer types. Furthermore, APA patterns were associated with altered protein levels in patients, revealed by antibody-based profiling data, suggesting functional significance. Overall, our study offers a computational approach for use of APA in novel gene discovery and classification in common tumor types, with important implications in basic research, biomarker discovery, and precision medicine approaches.

  7. Development and Validation of a Classification System to Identify High-Grade Dysplasia and Esophageal Adenocarcinoma in Barrett's Esophagus Using Narrow-Band Imaging

    NARCIS (Netherlands)

    Sharma, Prateek; Bergman, Jacques J. G. H. M.; Goda, Kenichi; Kato, Mototsugu; Messmann, Helmut; Alsop, Benjamin R.; Gupta, Neil; Vennalaganti, Prashanth; Hall, Matt; Konda, Vani; Koons, Ann; Penner, Olga; Goldblum, John R.; Waxman, Irving

    2016-01-01

    Although several classification systems have been proposed for characterization of Barrett's esophagus (BE) surface patterns based on narrow-band imaging (NBI), none have been widely accepted. The Barrett's International NBI Group (BING) aimed to develop and validate an NBI classification system for

  8. 78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

    Science.gov (United States)

    2013-03-26

    ...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... applicable sections. The Federal Prevailing Rate Advisory Committee, the national labor- management committee... proposing to amend 5 CFR part 532 as follows: PART 532--PREVAILING RATE SYSTEMS 0 1. The authority citation...

  9. CASAnova: a multiclass support vector machine model for the classification of human sperm motility patterns.

    Science.gov (United States)

    Goodson, Summer G; White, Sarah; Stevans, Alicia M; Bhat, Sanjana; Kao, Chia-Yu; Jaworski, Scott; Marlowe, Tamara R; Kohlmeier, Martin; McMillan, Leonard; Zeisel, Steven H; O'Brien, Deborah A

    2017-11-01

    The ability to accurately monitor alterations in sperm motility is paramount to understanding multiple genetic and biochemical perturbations impacting normal fertilization. Computer-aided sperm analysis (CASA) of human sperm typically reports motile percentage and kinematic parameters at the population level, and uses kinematic gating methods to identify subpopulations such as progressive or hyperactivated sperm. The goal of this study was to develop an automated method that classifies all patterns of human sperm motility during in vitro capacitation following the removal of seminal plasma. We visually classified CASA tracks of 2817 sperm from 18 individuals and used a support vector machine-based decision tree to compute four hyperplanes that separate five classes based on their kinematic parameters. We then developed a web-based program, CASAnova, which applies these equations sequentially to assign a single classification to each motile sperm. Vigorous sperm are classified as progressive, intermediate, or hyperactivated, and nonvigorous sperm as slow or weakly motile. This program correctly classifies sperm motility into one of five classes with an overall accuracy of 89.9%. Application of CASAnova to capacitating sperm populations showed a shift from predominantly linear patterns of motility at initial time points to more vigorous patterns, including hyperactivated motility, as capacitation proceeds. Both intermediate and hyperactivated motility patterns were largely eliminated when sperm were incubated in noncapacitating medium, demonstrating the sensitivity of this method. The five CASAnova classifications are distinctive and reflect kinetic parameters of washed human sperm, providing an accurate, quantitative, and high-throughput method for monitoring alterations in motility. © The Authors 2017. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. Intelligent feature selection techniques for pattern classification of Lamb wave signals

    International Nuclear Information System (INIS)

    Hinders, Mark K.; Miller, Corey A.

    2014-01-01

    Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy

  11. Quality assurance: The 10-Group Classification System (Robson classification), induction of labor, and cesarean delivery.

    LENUS (Irish Health Repository)

    Robson, Michael

    2015-10-01

    Quality assurance in labor and delivery is needed. The method must be simple and consistent, and be of universal value. It needs to be clinically relevant, robust, and prospective, and must incorporate epidemiological variables. The 10-Group Classification System (TGCS) is a simple method providing a common starting point for further detailed analysis within which all perinatal events and outcomes can be measured and compared. The system is demonstrated in the present paper using data for 2013 from the National Maternity Hospital in Dublin, Ireland. Interpretation of the classification can be easily taught. The standard table can provide much insight into the philosophy of care in the population of women studied and also provide information on data quality. With standardization of audit of events and outcomes, any differences in either sizes of groups, events or outcomes can be explained only by poor data collection, significant epidemiological variables, or differences in practice. In April 2015, WHO proposed that the TGCS (also known as the Robson classification) is used as a global standard for assessing, monitoring, and comparing cesarean delivery rates within and between healthcare facilities.

  12. Evolution and classification of the CRISPR-Cas systems

    Science.gov (United States)

    S. Makarova, Kira; H. Haft, Daniel; Barrangou, Rodolphe; J. J. Brouns, Stan; Charpentier, Emmanuelle; Horvath, Philippe; Moineau, Sylvain; J. M. Mojica, Francisco; I. Wolf, Yuri; Yakunin, Alexander F.; van der Oost, John; V. Koonin, Eugene

    2012-01-01

    The CRISPR–Cas (clustered regularly interspaced short palindromic repeats–CRISPR-associated proteins) modules are adaptive immunity systems that are present in many archaea and bacteria. These defence systems are encoded by operons that have an extraordinarily diverse architecture and a high rate of evolution for both the cas genes and the unique spacer content. Here, we provide an updated analysis of the evolutionary relationships between CRISPR–Cas systems and Cas proteins. Three major types of CRISPR–Cas system are delineated, with a further division into several subtypes and a few chimeric variants. Given the complexity of the genomic architectures and the extremely dynamic evolution of the CRISPR–Cas systems, a unified classification of these systems should be based on multiple criteria. Accordingly, we propose a `polythetic' classification that integrates the phylogenies of the most common cas genes, the sequence and organization of the CRISPR repeats and the architecture of the CRISPR–cas loci. PMID:21552286

  13. Classification system for acute and chronic radiation treatment sequelae

    International Nuclear Information System (INIS)

    Seegenschmiedt, M.H.; Sauer, R.

    1993-01-01

    A classification system in German language is proposed for scoring of acute and chronic treatment sequelae after radiotherapy. It includes all important organs and organ systems. The proposed grading corresponds to the four-scale-system of the WHO and UICC. The system is also compatible to the RTOG and EORTC acute and late radiation morbidity scoring criteria. This facilitates the data transfer for retrospective and prospective analysis of monomodal and multimodal radiotherapy treatment regimes. We recommend to use this scoring system in all German speaking countries for multicentric prospective studies. It is possible, that organ-specific sophistications of the toxicity grading will be developed in the future. These additions should conform with (inter)national standards and apply the same four-scale grading of this classification system. (orig.) [de

  14. Changing patient classification system for hospital reimbursement in Romania.

    Science.gov (United States)

    Radu, Ciprian-Paul; Chiriac, Delia Nona; Vladescu, Cristian

    2010-06-01

    To evaluate the effects of the change in the diagnosis-related group (DRG) system on patient morbidity and hospital financial performance in the Romanian public health care system. Three variables were assessed before and after the classification switch in July 2007: clinical outcomes, the case mix index, and hospital budgets, using the database of the National School of Public Health and Health Services Management, which contains data regularly received from hospitals reimbursed through the Romanian DRG scheme (291 in 2009). The lack of a Romanian system for the calculation of cost-weights imposed the necessity to use an imported system, which was criticized by some clinicians for not accurately reflecting resource consumption in Romanian hospitals. The new DRG classification system allowed a more accurate clinical classification. However, it also exposed a lack of physicians' knowledge on diagnosing and coding procedures, which led to incorrect coding. Consequently, the reported hospital morbidity changed after the DRG switch, reflecting an increase in the national case-mix index of 25% in 2009 (compared with 2007). Since hospitals received the same reimbursement over the first two years after the classification switch, the new DRG system led them sometimes to change patients' diagnoses in order to receive more funding. Lack of oversight of hospital coding and reporting to the national reimbursement scheme allowed the increase in the case-mix index. The complexity of the new classification system requires more resources (human and financial), better monitoring and evaluation, and improved legislation in order to achieve better hospital resource allocation and more efficient patient care.

  15. The classification of frontal sinus pneumatization patterns by CT-based volumetry.

    Science.gov (United States)

    Yüksel Aslier, Nesibe Gül; Karabay, Nuri; Zeybek, Gülşah; Keskinoğlu, Pembe; Kiray, Amaç; Sütay, Semih; Ecevit, Mustafa Cenk

    2016-10-01

    We aimed to define the classification of frontal sinus pneumatization patterns according to three-dimensional volume measurements. Datasets of 148 sides of 74 dry skulls were generated by the computerized tomography-based volumetry to measure frontal sinus volumes. The cutoff points for frontal sinus hypoplasia and hyperplasia were tested by ROC curve analysis and the validity of the diagnostic points was measured. The overall frequencies were 4.1, 14.2, 37.2 and 44.5 % for frontal sinus aplasia, hypoplasia, medium size and hyperplasia, respectively. The aplasia was bilateral in all three skulls. Hypoplasia was seen 76 % at the right side and hyperplasia was seen 56 % at the left side. The cutoff points for diagnosing frontal sinus hypoplasia and hyperplasia were '1131.25 mm(3)' (95.2 % sensitivity and 100 % specificity) and '3328.50 mm(3)' (88 % sensitivity and 86 % specificity), respectively. The findings provided in the present study, which define frontal sinus pneumatization patterns by CT-based volumetry, proved that two opposite sides of the frontal sinuses are asymmetric and three-dimensional classification should be developed by CT-based volumetry, because two-dimensional evaluations lack depth measurement.

  16. Hotel Classification Systems: A Comparison of International Case Studies

    Directory of Open Access Journals (Sweden)

    Roberta Minazzi,

    2010-12-01

    Full Text Available Over the last few decades we have witnessed an increasing interest of scholars andespecially operators in service quality in the lodging business. Firstly, it is important to observe thatthe diverseness of the hospitality industry also affects the classification of hotel quality. We canactually find many programmes, classifications and seals of quality promoted by public authoritiesand private companies that create confusion in the consumer perceptions of hotel quality. Moreover,new electronic distribution channels and their ratings are becoming a new way to gather informationabout a hotel and its quality. Secondly, a point that can cause complications is that different countriesand regions can choose differing approaches depending on the features of the classification (numberof levels, symbols used, etc. and the nature of the programme (public, private. Considering theseassumptions and the recent changes in the Italian hotel classification system, this paper aims toanalyse the situation in Italy, underlining both its positive and negative aspects and comparing it withother European and North American cases. Based on a review of literature and tourism laws as wellas personal interviews with public authorities and exponents of the private sectors, we were able toidentify critical issues and trends in hotel classification systems. The comparison of case studiesshows a heterogeneous situation. Points in common are the scale and the symbol used but, if weanalyse the requirements of each category, we discover very different circumstances, also sometimesin the same country. A future European classification system could be possible only after astandardization of minimum requirements and criteria at a national level. In this situation brands andonline consumers’ feedbacks become even more considered by the customers in the hospitalityindustry.

  17. Air Traffic Security: Aircraft Classification Using ADS-B Message’s Phase-Pattern

    Directory of Open Access Journals (Sweden)

    Mauro Leonardi

    2017-10-01

    Full Text Available Automatic Dependent Surveillance-Broadcast (ADS-B is a surveillance system used in Air Traffic Control. With this system, the aircraft transmits their own information (identity, position, velocity, etc. to any equipped listener for surveillance scope. The ADS-B is based on a very simple protocol and does not provide any kind of authentication and encryption, making it vulnerable to many types of cyber-attacks. In the paper, the use of the airplane/transmitter carrier phase is proposed as a feature to perform a classification of the aircraft and, therefore, distinguish legitimate messages from fake ones. The feature extraction process is described and a classification method is selected. Finally, a complete intruder detection algorithm is proposed and evaluated with real data.

  18. Developing a consensus classification system for acute renal failure

    NARCIS (Netherlands)

    Kellum, John A.; Levin, Nathan; Bouman, Catherine; Lameire, Norbert

    2002-01-01

    A biochemical definition and classification system for acute renal dysfunction is long overdue. Its absence has impeded progress in clinical and even basic research concerning a syndrome associated with mortality rates of 30 to 80%. No definition of acute renal dysfunction will be perfect, but the

  19. Classification of $E_{0}$-semigroups by product systems

    CERN Document Server

    Skeide, Michael

    2016-01-01

    In these notes the author presents a complete theory of classification of E_0-semigroups by product systems of correspondences. As an application of his theory, he answers the fundamental question if a Markov semigroup admits a dilation by a cocycle perturbations of noise: It does if and only if it is spatial.

  20. The Spinal Cord Injury-Interventions Classification System

    NARCIS (Netherlands)

    van Langeveld, A.H.B.

    2010-01-01

    Title: The Spinal Cord Injury-Interventions Classification System: development and evaluation of a documentation tool to record therapy to improve mobility and self-care in people with spinal cord injury. Background: Many rehabilitation researchers have emphasized the need to examine the actual

  1. Awareness and use of Gross Motor Function Classification System ...

    African Journals Online (AJOL)

    Introduction The degree of disability in children with Cerebral Palsy (CP) can be evaluated with the Gross Motor Function Classification System (GMFCS), a valid tool which was designed for such purposes. However, there appears to be paucity of data on the awareness and use of the GMFCS particularly in the ...

  2. A Classification System for Recurrent Ameloblastoma of the Jaws ...

    African Journals Online (AJOL)

    This paper reviewed the clinicopathologic presentation of recurrent ameloblastoma in 30 Nigerian patients at three tertiary referral centers with the sole objective of developing a classification system. Most recurrences occurred in patients in their 3rd decade of life (20-29years) and males were more frequently affected than ...

  3. Performance of classification confidence measures in dynamic classifier systems

    Czech Academy of Sciences Publication Activity Database

    Štefka, D.; Holeňa, Martin

    2013-01-01

    Roč. 23, č. 4 (2013), s. 299-319 ISSN 1210-0552 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : classifier combining * dynamic classifier systems * classification confidence Subject RIV: IN - Informatics, Computer Science Impact factor: 0.412, year: 2013

  4. The development of a classification system for inland aquatic ...

    African Journals Online (AJOL)

    2015-10-05

    Oct 5, 2015 ... 6Department of Plant Sciences, University of the Free State, Qwaqwa Campus, Private .... classification systems for wetlands and other inland aquatic ... of vegetation, soil, inundation and landform features that are ... nised as the fundamental drivers that determine the existence ...... Earth Obs. Remote Sens.

  5. Standard practice for classification of computed radiology systems

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2005-01-01

    1.1 This practice describes the evaluation and classification of a computed radiography (CR) system, a particular phosphor imaging plate (IP), system scanner and software, in combination with specified metal screens for industrial radiography. It is intended to ensure that the evaluation of image quality, as far as this is influenced by the scanner/IP system, meets the needs of users. 1.2 The practice defines system tests to be used to classify the systems of different suppliers and make them comparable for users. 1.3 The CR system performance is described by signal and noise parameters. For film systems, the signal is represented by gradient and the noise by granularity. The signal-to-noise ratio is normalized by the basic spatial resolution of the system and is part of classification. The normalization is given by the scanning aperture of 100 µm diameter for the micro-photometer, which is defined in Test Method E1815 for film system classification. This practice describes how the parameters shall be meas...

  6. A Classification System for Hospital-Based Infection Outbreaks

    Directory of Open Access Journals (Sweden)

    Paul S. Ganney

    2010-01-01

    Full Text Available Outbreaks of infection within semi-closed environments such as hospitals, whether inherent in the environment (such as Clostridium difficile (C.Diff or Methicillinresistant Staphylococcus aureus (MRSA or imported from the wider community (such as Norwalk-like viruses (NLVs, are difficult to manage. As part of our work on modelling such outbreaks, we have developed a classification system to describe the impact of a particular outbreak upon an organization. This classification system may then be used in comparing appropriate computer models to real outbreaks, as well as in comparing different real outbreaks in, for example, the comparison of differing management and containment techniques and strategies. Data from NLV outbreaks in the Hull and East Yorkshire Hospitals NHS Trust (the Trust over several previous years are analysed and classified, both for infection within staff (where the end of infection date may not be known and within patients (where it generally is known. A classification system consisting of seven elements is described, along with a goodness-of-fit method for comparing a new classification to previously known ones, for use in evaluating a simulation against history and thereby determining how ‘realistic’ (or otherwise it is.

  7. A classification system for hospital-based infection outbreaks.

    Science.gov (United States)

    Ganney, Paul S; Madeo, Maurice; Phillips, Roger

    2010-12-01

    Outbreaks of infection within semi-closed environments such as hospitals, whether inherent in the environment (such as Clostridium difficile (C.Diff) or Methicillin-resistant Staphylococcus aureus (MRSA) or imported from the wider community (such as Norwalk-like viruses (NLVs)), are difficult to manage. As part of our work on modelling such outbreaks, we have developed a classification system to describe the impact of a particular outbreak upon an organization. This classification system may then be used in comparing appropriate computer models to real outbreaks, as well as in comparing different real outbreaks in, for example, the comparison of differing management and containment techniques and strategies. Data from NLV outbreaks in the Hull and East Yorkshire Hospitals NHS Trust (the Trust) over several previous years are analysed and classified, both for infection within staff (where the end of infection date may not be known) and within patients (where it generally is known). A classification system consisting of seven elements is described, along with a goodness-of-fit method for comparing a new classification to previously known ones, for use in evaluating a simulation against history and thereby determining how 'realistic' (or otherwise) it is.

  8. 78 FR 58153 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

    Science.gov (United States)

    2013-09-23

    ... American Industry Classification System Based Federal Wage System Wage Surveys AGENCY: U.S. Office of... in Federal Wage System wage survey industry regulations with the 2012 NAICS revisions published by.... Applicability date: This rule applies for local wage surveys beginning on or after February 21, 2014. FOR...

  9. An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

    Science.gov (United States)

    Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

    2017-03-01

    Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

  10. Design and implementation based on the classification protection vulnerability scanning system

    International Nuclear Information System (INIS)

    Wang Chao; Lu Zhigang; Liu Baoxu

    2010-01-01

    With the application and spread of the classification protection, Network Security Vulnerability Scanning should consider the efficiency and the function expansion. It proposes a kind of a system vulnerability from classification protection, and elaborates the design and implementation of a vulnerability scanning system based on vulnerability classification plug-in technology and oriented classification protection. According to the experiment, the application of classification protection has good adaptability and salability with the system, and it also approves the efficiency of scanning. (authors)

  11. Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity.

    Directory of Open Access Journals (Sweden)

    Marc Breit

    2015-08-01

    Full Text Available The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS with the concept of stable isotope dilution (SID for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2, showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001. In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001, classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001. These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling

  12. Image-based fall detection and classification of a user with a walking support system

    Science.gov (United States)

    Taghvaei, Sajjad; Kosuge, Kazuhiro

    2017-10-01

    The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems.We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user's depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called "RT Walker") by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user's motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.

  13. Annotation and Classification of CRISPR-Cas Systems.

    Science.gov (United States)

    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.

  14. CLASSIFICATION OF THE MGR MAINTENANCE AND SUPPLY SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) maintenance and supply system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  15. A Chinese text classification system based on Naive Bayes algorithm

    Directory of Open Access Journals (Sweden)

    Cui Wei

    2016-01-01

    Full Text Available In this paper, aiming at the characteristics of Chinese text classification, using the ICTCLAS(Chinese lexical analysis system of Chinese academy of sciences for document segmentation, and for data cleaning and filtering the Stop words, using the information gain and document frequency feature selection algorithm to document feature selection. Based on this, based on the Naive Bayesian algorithm implemented text classifier , and use Chinese corpus of Fudan University has carried on the experiment and analysis on the system.

  16. CLASSIFICATION OF THE MGR SITE COMPRESSED AIR SYSTEM

    International Nuclear Information System (INIS)

    J.A. Ziegler

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) site compressed air system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  17. CLASSIFICATION OF THE MGR WASTE HANDLING BUILDING ELECTRICAL SYSTEM

    International Nuclear Information System (INIS)

    S.E. Salzman

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) waste handling building electrical system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  18. CLASSIFICATION OF THE MGR OPERATIONS MONITORING AND CONTROL SYSTEM

    International Nuclear Information System (INIS)

    R.J. Garrett

    1999-01-01

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) Operations Monitoring and Control System structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P7 ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998)

  19. Classification of building systems for concrete 3D printing

    OpenAIRE

    DUBALLET , Romain; BAVEREL , Olivier; Dirrenberger , Justin

    2017-01-01

    In the present paper, a study is conducted on building systems associated with concrete extrusion-based additive manufacturing techniques. Specific parameters are highlighted - concerning scale, environment, support, and assembly strategies - and a classification method is introduced. The objective is to explicitly characterise construction systems based on such printing processes. A cartography of the different approaches and subsequent robotic complexity is proposed. The state of the art ga...

  20. Annotation and Classification of CRISPR-Cas Systems

    Science.gov (United States)

    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

  1. A classification system for pressure vessel shell failures

    International Nuclear Information System (INIS)

    Harrop, L.P.

    1989-01-01

    A system for classifying failures of the shells of pressure vessels is presented. The classification system is based on the way a failure physically manifests itself and not on imputed economic or safety significance. It is believed the described way of classifying the failures is useful for transferring information from one situation to another. In assigning names to types of failure, the intention has been to adopt explicit definitions rather than supposed colloquial usage. (author)

  2. A new classification system for congenital laryngeal cysts.

    Science.gov (United States)

    Forte, Vito; Fuoco, Gabriel; James, Adrian

    2004-06-01

    A new classification system for congenital laryngeal cysts based on the extent of the cyst and on the embryologic tissue of origin is proposed. Retrospective chart review. The charts of 20 patients with either congenital or acquired laryngeal cysts that were treated surgically between 1987 and 2002 at the Hospital for Sick Children, Toronto were retrospectively reviewed. Clinical presentation, radiologic findings, surgical management, histopathology, and outcome were recorded. A new classification system is proposed to better appreciate the origin of these cysts and to guide in their successful surgical management. Fourteen of the supraglottic and subglottic simple mucous retention cysts posed no diagnostic or therapeutic challenge and were treated successfully by a single endoscopic excision or marsupialization. The remaining six patients with congenital cysts in the study were deemed more complex, and all required open surgical procedures for cure. On the basis of the analysis of the data of these patients, a new classification of congenital laryngeal cysts is proposed. Type I cysts are confined to the larynx, the cyst wall composed of endodermal elements only, and can be managed endoscopically. Type II cysts extend beyond the confines of the larynx and require an external approach. The Type II cysts are further subclassified histologically on the basis of the embryologic tissue of origin: IIa, composed of endoderm only and IIb, containing endodermal and mesodermal elements (epithelium and cartilage) in the wall of the cyst. A new classification system for congenital laryngeal cysts is proposed on the basis of the extent of the cyst and the embryologic tissue of origin. This classification can help guide the surgeon with initial management and help us better understand the origin of these cysts.

  3. Estimating local scaling properties for the classification of interstitial lung disease patterns

    Science.gov (United States)

    Huber, Markus B.; Nagarajan, Mahesh B.; Leinsinger, Gerda; Ray, Lawrence A.; Wismueller, Axel

    2011-03-01

    Local scaling properties of texture regions were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honeycombing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and the estimation of local scaling properties with Scaling Index Method (SIM). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions including the Bonferroni correction. The best classification results were obtained by the set of SIM features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers with the highest accuracy (94.1%, 93.7%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced texture features using local scaling properties can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

  4. Classification of Recommender Expertise in the Wikipedia Recommender System

    DEFF Research Database (Denmark)

    Jensen, Christian D.; Pilkauskas, Povilas; Lefévre, Thomas

    2011-01-01

    to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles which emphasizes...... an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System....... feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article...

  5. Classification of Recommender Expertise in the Wikipedia Recommender System

    DEFF Research Database (Denmark)

    Jensen, Christian D.; Pilkauskas, Povilas; Lefevre, Thomas

    2011-01-01

    to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles "which emphasizes...... an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System....... feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article...

  6. [Construction of biopharmaceutics classification system of Chinese materia medica].

    Science.gov (United States)

    Liu, Yang; Wei, Li; Dong, Ling; Zhu, Mei-Ling; Tang, Ming-Min; Zhang, Lei

    2014-12-01

    Based on the characteristics of multicomponent of traditional Chinese medicine and drawing lessons from the concepts, methods and techniques of biopharmaceutics classification system (BCS) in chemical field, this study comes up with the science framework of biopharmaceutics classification system of Chinese materia medica (CMMBCS). Using the different comparison method of multicomponent level and the CMMBCS method of overall traditional Chinese medicine, the study constructs the method process while setting forth academic thoughts and analyzing theory. The basic role of this system is clear to reveal the interaction and the related absorption mechanism of multicomponent in traditional Chinese medicine. It also provides new ideas and methods for improving the quality of Chinese materia medica and the development of new drug research.

  7. Novel classification system of rib fractures observed in infants.

    Science.gov (United States)

    Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Pinto, Deborrah C; Greeley, Christopher; Donaruma-Kwoh, Marcella; Bista, Bibek

    2013-03-01

    Rib fractures are considered highly suspicious for nonaccidental injury in the pediatric clinical literature; however, a rib fracture classification system has not been developed. As an aid and impetus for rib fracture research, we developed a concise schema for classifying rib fracture types and fracture location that is applicable to infants. The system defined four fracture types (sternal end, buckle, transverse, and oblique) and four regions of the rib (posterior, posterolateral, anterolateral, and anterior). It was applied to all rib fractures observed during 85 consecutive infant autopsies. Rib fractures were found in 24 (28%) of the cases. A total of 158 rib fractures were identified. The proposed schema was adequate to classify 153 (97%) of the observed fractures. The results indicate that the classification system is sufficiently robust to classify rib fractures typically observed in infants and should be used by researchers investigating infant rib fractures. © 2013 American Academy of Forensic Sciences.

  8. Classification of topographical pattern of spasticity in cerebral palsy: a registry perspective.

    Science.gov (United States)

    Reid, Susan M; Carlin, John B; Reddihough, Dinah S

    2011-01-01

    This study used data from a population-based cerebral palsy (CP) registry and systematic review to assess the amount of heterogeneity between registries in topographical patterns when dichotomised into unilateral (USCP) and bilateral spastic CP (BSCP), and whether the terms diplegia and quadriplegia provide useful additional epidemiological information. From the Victorian CP Register, 2956 individuals (1658 males, 1298 females), born 1970-2003, with spastic CP were identified. The proportions with each topographical pattern were analysed overall and by gestational age. Binary logistic regression analysis was used to assess temporal trends. For the review, data were systematically collected on topographical patterns from 27 registries. Estimates of heterogeneity were obtained, overall and by region, reporting period and definition of quadriplegia. Among individuals born <32 weeks, 48% had diplegia, whereas the proportion for children born ≥ 32 weeks was 24% (p < 0.001). Evidence was weak for a temporal trend in the relative proportions of USCP and BSCP (p = 0.038), but much clearer for an increase in the proportion of spastic diplegia relative to quadriplegia (p < 0.001). The review revealed wide variations across studies in the proportion of diplegia (range 34-90%) and BSCP (range 51-86%). These findings argue against a topographical classification based solely on laterality. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

    Science.gov (United States)

    Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

    2017-09-01

    With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

  10. Classifying Human Activity Patterns from Smartphone Collected GPS data: a Fuzzy Classification and Aggregation Approach.

    Science.gov (United States)

    Wan, Neng; Lin, Ge

    2016-12-01

    Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone-measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone-collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g., up to 96% in activity identification) with use of this method. Two examples were provided in the appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.

  11. A study on the development of a real-time intelligent system for ultrasonic flaw classification

    International Nuclear Information System (INIS)

    Song, Sung Jin; Kim, Hak Joon; Lee, Hyun; Lee, Seung Seok

    1998-01-01

    In spite of significant progress in research on ultrasonic pattern recognition it is not widely used in many practical field inspection in weldments. For the convenience of field application of this methodology, following four key issues have to be suitably addressed; 1) a software where the ultrasonic pattern recognition algorithm is efficiently implemented, 2) a real-time ultrasonic testing system which can capture the digitized ultrasonic flaw signal so the pattern recognition software can be applied in a real-time fashion, 3) database of ultrasonic flaw signals in weldments, which is served as a foundation of the ultrasonic pattern recognition algorithm, and finally, 4) ultrasonic features which should be invariant to operational variables of the ultrasonic test system. Presented here is the recent progress in the development of a real-time ultrasonic flaw classification by the novel combination of followings; an intelligent software for ultrasonic flaw classification in weldments, a computer-base real-time ultrasonic nondestructive evaluation system, database of ultrasonic flaw signals, and invariant ultrasonic features called 'normalized features.'

  12. Street-level classification of illicit heroin using inorganic elements coupled with pattern monitoring

    Directory of Open Access Journals (Sweden)

    Kar-Weng Chan

    2016-09-01

    Full Text Available A total of 96 illicit heroin samples seized in 2013–2014 were analyzed by inductively coupled plasma-mass spectrometry (ICP-MS to determine 16 inorganic elements at parts-per-billion (ppb level. Of eleven submissions, two or three samples with similar appearance were taken from the same seizure to form related samples. These samples were used to monitor the clustering outcome suggested by principal component analysis (PCA. They provided hints regarding the acceptance of within-seizure variability in-situ. The previously established data pretreatment method (N+4R did not function well with the present data probably due to the higher concentrations reported for the current samples. With the aid of the above-cited related samples for pattern monitoring, a better outcome was achieved when the pretreatment method was modified to employ solely standardization (S to optimize the necessary variability for sample classification.

  13. Rare idiopathic intestinal pneumonias (IIPs) and histologic patterns in new ATS/ERS multidisciplinary classification of the IIPs

    Energy Technology Data Exchange (ETDEWEB)

    Johkoh, Takeshi, E-mail: johkoht@aol.com [Department of Radiology, Kinki Central Hospital of Mutual Aid Association of Public School Teachers (Japan); Fukuoka, Junya, E-mail: fukuokaj@nagasaki-u.ac.jp [Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences (Japan); Tanaka, Tomonori, E-mail: yotsudukayama@yahoo.com [Department of Pathology, Nagasaki University Graduate School of Biomedical Sciences (Japan)

    2015-03-15

    Highlights: •The new (ATS/ERS) update to the multidisciplinary classification of idiopathic interstitial pneumonias (IIPs) defines both rare IIPs and rare histologic patterns of IIPs. •Rare IIPs; lymphoid interstitial pneumonia, pleuroparenchymal fibroelastosis. •Rare histologic pattern, acute fibrionous organizing pneumonia, bronchocentric pattern of interstitial pneumonia. -- Abstract: The new American Thoracic Society/European Respiratory Society (ATS/ERS) update to the multidisciplinary classification of idiopathic interstitial pneumonias (IIPs) defines both rare IIPs and rare histologic patterns of IIPs. Although these diseases are rare, each has some distinguishing imaging and pathologic characteristics. Common findings for IIPs in computed tomography (CT) include cysts in lymphoid interstitial pneumonia (LIP), upper lobe subpleural consolidation in pleuropulmonary fibroelastosis (PPFE), symmetrical consolidation in acute fibrinous organizing pneumonia (AFOP), and peribronchovascular consolidation or centrilobular nodules in bronchiolocentric pattern of interstitial pneumonia.

  14. Rare idiopathic intestinal pneumonias (IIPs) and histologic patterns in new ATS/ERS multidisciplinary classification of the IIPs

    International Nuclear Information System (INIS)

    Johkoh, Takeshi; Fukuoka, Junya; Tanaka, Tomonori

    2015-01-01

    Highlights: •The new (ATS/ERS) update to the multidisciplinary classification of idiopathic interstitial pneumonias (IIPs) defines both rare IIPs and rare histologic patterns of IIPs. •Rare IIPs; lymphoid interstitial pneumonia, pleuroparenchymal fibroelastosis. •Rare histologic pattern, acute fibrionous organizing pneumonia, bronchocentric pattern of interstitial pneumonia. -- Abstract: The new American Thoracic Society/European Respiratory Society (ATS/ERS) update to the multidisciplinary classification of idiopathic interstitial pneumonias (IIPs) defines both rare IIPs and rare histologic patterns of IIPs. Although these diseases are rare, each has some distinguishing imaging and pathologic characteristics. Common findings for IIPs in computed tomography (CT) include cysts in lymphoid interstitial pneumonia (LIP), upper lobe subpleural consolidation in pleuropulmonary fibroelastosis (PPFE), symmetrical consolidation in acute fibrinous organizing pneumonia (AFOP), and peribronchovascular consolidation or centrilobular nodules in bronchiolocentric pattern of interstitial pneumonia

  15. Categorization of intraoperative ureteroscopy complications using modified Satava classification system.

    Science.gov (United States)

    Tepeler, Abdulkadir; Resorlu, Berkan; Sahin, Tolga; Sarikaya, Selcuk; Bayindir, Mirze; Oguz, Ural; Armagan, Abdullah; Unsal, Ali

    2014-02-01

    To review our experience with ureteroscopy (URS) in the treatment of ureteral calculi and stratify intraoperative complications of URS according to the modified Satava classification system. We performed a retrospective analysis of 1,208 patients (672 males and 536 females), with a mean age of 43.1 years (range 1-78), who underwent ureteroscopic procedures for removal of ureteral stones. Intraoperative complications were recorded according to modified Satava classification system. Grade 1 complications included incidents without consequences for the patient; grade 2 complications, which are treated intraoperatively with endoscopic surgery (grade 2a) or required endoscopic re-treatment (grade 2b); and grade 3 complications included incidents requiring open or laparoscopic surgery. The stones were completely removed in 1,067 (88.3%) patients after primary procedure by either simple extraction or after fragmentation. The overall incidence of intraoperative complications was 12.6%. The most common complications were proximal stone migration (3.9%), mucosal injury (2.8%), bleeding (1.9%), inability to reach stone (1.8%), malfunctioning or breakage of instruments (0.8%), ureteral perforation (0.8%) and ureteral avulsion (0.16%). According to modified Satava classification system, there were 4.5% grade 1; 4.4% grade 2a; 3.2% grade 2b; and 0.57% grade 3 complications. We think that modified Satava classification is a quick and simple system for describing the severity of intraoperative URS complications and this grading system will facilitate a better comparison for the surgical outcomes obtained from different centers.

  16. Improvement of the Radiological system of emergency classification in Cuba

    International Nuclear Information System (INIS)

    Jerez Vegueria, Pablo F.; Yamil Lopez Forteza; Diaz Guerra, Pedro I.

    2003-01-01

    In 1998 the National Center of Nuclear Security (CNSN), on the base of the experience in the one handling of emergencies and the preparation aspects, planning and answer, it perfects and it modernizes, with the approval of the national bigger State of the Civil Defense, the approaches of the Scale of Radiological Events approved from 1992. Given the operational experience of the System of Answer to Emergency of the Ministry Of Science Technology And Environment in the year 2001 the CNSN develops, it perfects and it puts in vigor a more complete System of Classification of Emergency of unique use for all the entities that use sources of radiations ionizations and that it also includes those answer forces that are imbricate in the Plan of Measures Against Catastrophe for cases of Radiological Accidents. The setting in vigor of this Unique System of Classification of Emergencies at national level has allowed to secure the coordination, planning and answer in an effective, quick and effective way. Presently work is exposed the philosophy on which this System of Classification was elaborated, the approaches used to classify the events as much in radioactive facilities as in the practice of the transport of radioactive materials and the activation of the forces of answers in cases of radiological emergencies

  17. Compute raided classification of ventilation patterns inpatients with chronic obstructive pulmonary diseases at two-phase xenon-enhanced CT

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Son Ho; Goo, Jin Mo; Lee, Chang Hyun; Lee, You Kyung; Jin, Kwang Nam; Choo, Ji Yung; Lee, Nyoung Keun [Seoul National University College of Medicine, Seoul (Korea, Republic of); Jung, Julip; Hong, Helen [Dept. of Multimedia Engineering, Seoul Women' s University, Seoul (Korea, Republic of)

    2014-06-15

    To evaluate the technical feasibility, performance, and interobserver agreement of a computer-aided classification (CAC) system for regional ventilation at two-phase xenon-enhanced CT in patients with chronic obstructive pulmonary disease (COPD). Thirty-eight patients with COPD underwent two-phase xenon ventilation CT with resulting wash-in (WI) and wash-out (WO) xenon images. The regional ventilation in structural abnormalities was visually categorized into four patterns by consensus of two experienced radiologists who compared the xenon attenuation of structural abnormalities with that of adjacent normal parenchyma in the WI and WO images, and it served as the reference. Two series of image datasets of structural abnormalities were randomly extracted for optimization and validation. The proportion of agreement on a per-lesion basis and receiver operating characteristics on a per-pixel basis between CAC and reference were analyzed for optimization. Thereafter, six readers independently categorized the regional ventilation in structural abnormalities in the validation set without and with a CAC map. Interobserver agreement was also compared between assessments without and with CAC maps using multirater κ statistics. Computer-aided classification maps were successfully generated in 31 patients (81.5%). The proportion of agreement and the average area under the curve of optimized CAC maps were 94% (75/80) and 0.994, respectively. Multirater k value was improved from moderate (k=0.59: 95% confidence interval [CI], 0.56-0.62) at the initial assessment to excellent with the CAC map.

  18. Side effects of cancer therapies. International classification and documentation systems

    International Nuclear Information System (INIS)

    Seegenschmiedt, M.H.

    1998-01-01

    The publication presents and explains verified, international classification and documentation systems for side effects induced by cancer treatments, applicable in general and clinical practice and clinical research, and covers in a clearly arranged manner the whole range of treatments, including acute and chronic side effects of chemotherapy and radiotherapy, surgery, or combined therapies. The book fills a long-felt need in tumor documentation and is a major contribution to quality assurance in clinical oncology in German-speaking countries. As most parts of the book are bilingual, presenting German and English texts and terminology, it satisfies the principles of interdisciplinarity and internationality. The tabulated form chosen for presentation of classification systems and criteria facilitate the user's approach as well as application in daily work. (orig./CB) [de

  19. Pattern Classification of Tropical Cyclone Tracks over the Western North Pacific using a Fuzzy Clustering Method

    Science.gov (United States)

    Kim, H.; Ho, C.; Kim, J.

    2008-12-01

    This study presents the pattern classification of tropical cyclone (TC) tracks over the western North Pacific (WNP) basin during the typhoon season (June through October) for 1965-2006 (total 42 years) using a fuzzy clustering method. After the fuzzy c-mean clustering algorithm to the TC trajectory interpolated into 20 segments of equivalent length, we divided the whole tracks into 7 patterns. The optimal number of the fuzzy cluster is determined by several validity measures. The classified TC track patterns represent quite different features in the recurving latitudes, genesis locations, and geographical pathways: TCs mainly forming in east-northern part of the WNP and striking Korean and Japan (C1); mainly forming in west-southern part of the WNP, traveling long pathway, and partly striking Japan (C2); mainly striking Taiwan and East China (C3); traveling near the east coast of Japan (C4); traveling the distant ocean east of Japan (C5); moving toward South China and Vietnam straightly (C6); and forming in the South China Sea (C7). Atmospheric environments related to each cluster show physically consistent with each TC track patterns. The straight track pattern is closely linked to a developed anticyclonic circulation to the north of the TC. It implies that this ridge acts as a steering flow forcing TCs to move to the northwest with a more west-oriented track. By contrast, recurving patterns occur commonly under the influence of the strong anomalous westerlies over the TC pathway but there definitely exist characteristic anomalous circulations over the mid- latitudes by pattern. Some clusters are closely related to the well-known large-scale phenomena. The C1 and C2 are highly related to the ENSO phase: The TCs in the C1 (C2) is more active during La Niña (El Niño). The TC activity in the C3 is associated with the WNP summer monsoon. The TCs in the C4 is more (less) vigorous during the easterly (westerly) phase of the stratospheric quasi-biennial oscillation

  20. Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

    Science.gov (United States)

    Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

    2013-01-01

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many

  1. Automated classification of immunostaining patterns in breast tissue from the human protein Atlas

    Directory of Open Access Journals (Sweden)

    Issac Niwas Swamidoss

    2013-01-01

    Full Text Available Background: The Human Protein Atlas (HPA is an effort to map the location of all human proteins (http://www.proteinatlas.org/. It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. Materials and Methods: The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM features, complex wavelet co-occurrence matrix (CWCM features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM and linear discriminant analysis (LDA classifier. Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. Results: We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Conclusions: Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for

  2. London 2012 Paralympic swimming: passive drag and the classification system.

    Science.gov (United States)

    Oh, Yim-Taek; Burkett, Brendan; Osborough, Conor; Formosa, Danielle; Payton, Carl

    2013-09-01

    The key difference between the Olympic and Paralympic Games is the use of classification systems within Paralympic sports to provide a fair competition for athletes with a range of physical disabilities. In 2009, the International Paralympic Committee mandated the development of new, evidence-based classification systems. This study aims to assess objectively the swimming classification system by determining the relationship between passive drag and level of swimming-specific impairment, as defined by the current swimming class. Data were collected on participants at the London 2012 Paralympic Games. The passive drag force of 113 swimmers (classes 3-14) was measured using an electro-mechanical towing device and load cell. Swimmers were towed on the surface of a swimming pool at 1.5 m/s while holding their most streamlined position. Passive drag ranged from 24.9 to 82.8 N; the normalised drag (drag/mass) ranged from 0.45 to 1.86 N/kg. Significant negative associations were found between drag and the swimming class (τ = -0.41, p < 0.01) and normalised drag and the swimming class (τ = -0.60, p < 0.01). The mean difference in drag between adjacent classes was inconsistent, ranging from 0 N (6 vs 7) to 11.9 N (5 vs 6). Reciprocal Ponderal Index (a measure of slenderness) correlated moderately with normalised drag (r(P) = -0.40, p < 0.01). Although swimmers with the lowest swimming class experienced the highest passive drag and vice versa, the inconsistent difference in mean passive drag between adjacent classes indicates that the current classification system does not always differentiate clearly between swimming groups.

  3. THE BIOPHARMACEUTICAL CLASSIFICATION SYSTEM (BCS): PRESENT STATUS AND FUTURE PROSPECTIVES

    OpenAIRE

    Budhwaar Vikaas; Nanda Arun

    2012-01-01

    The Biopharmaceutical classification system (BCS) was introduced By Amidon et al., (1995) as a method for classifying drug substances based on their dose/solubility ratio and intestinal permeability. It allows predicting the in vivo pharmacokinetic performance of drug products. The drug can be categorized into four classes of BCS, namely, High solubility high permeability, low solubility high permeability, High solubility low permeability and low solubility low permeability. An objective of B...

  4. BIOPHARMACEUTICS CLASSIFICATION SYSTEM: A STRATEGIC TOOL FOR CLASSIFYING DRUG SUBSTANCES

    OpenAIRE

    Rohilla Seema; Rohilla Ankur; Marwaha RK; Nanda Arun

    2011-01-01

    The biopharmaceutical classification system (BCS) is a scientific approach for classifying drug substances based on their dose/solubility ratio and intestinal permeability. The BCS has been developed to allow prediction of in vivo pharmacokinetic performance of drug products from measurements of permeability and solubility. Moreover, the drugs can be categorized into four classes of BCS on the basis of permeability and solubility namely; high permeability high solubility, high permeability lo...

  5. Classification of cognitive systems dedicated to data sharing

    Science.gov (United States)

    Ogiela, Lidia; Ogiela, Marek R.

    2017-08-01

    In this paper will be presented classification of new cognitive information systems dedicated to cryptographic data splitting and sharing processes. Cognitive processes of semantic data analysis and interpretation, will be used to describe new classes of intelligent information and vision systems. In addition, cryptographic data splitting algorithms and cryptographic threshold schemes will be used to improve processes of secure and efficient information management with application of such cognitive systems. The utility of the proposed cognitive sharing procedures and distributed data sharing algorithms will be also presented. A few possible application of cognitive approaches for visual information management and encryption will be also described.

  6. Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus

    DEFF Research Database (Denmark)

    Petri, Michelle; Orbai, Ana-Maria; Alarcón, Graciela S

    2012-01-01

    The Systemic Lupus International Collaborating Clinics (SLICC) group revised and validated the American College of Rheumatology (ACR) systemic lupus erythematosus (SLE) classification criteria in order to improve clinical relevance, meet stringent methodology requirements, and incorporate new...

  7. An alternative respiratory sounds classification system utilizing artificial neural networks

    Directory of Open Access Journals (Sweden)

    Rami J Oweis

    2015-04-01

    Full Text Available Background: 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. Methods: 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. Results: 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. Conclusions: 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.

  8. Stochastic change detection in uncertain nonlinear systems using reduced-order models: classification

    International Nuclear Information System (INIS)

    Yun, Hae-Bum; Masri, Sami F

    2009-01-01

    A reliable structural health monitoring methodology (SHM) is proposed to detect relatively small changes in uncertain nonlinear systems. A total of 4000 physical tests were performed using a complex nonlinear magneto-rheological (MR) damper. With the effective (or 'genuine') changes and uncertainties in the system characteristics of the semi-active MR damper, which were precisely controlled with known means and standard deviation of the input current, the tested MR damper was identified with the restoring force method (RFM), a non-parametric system identification method involving two-dimensional orthogonal polynomials. Using the identified RFM coefficients, both supervised and unsupervised pattern recognition techniques (including support vector classification and k-means clustering) were employed to detect system changes in the MR damper. The classification results showed that the identified coefficients with orthogonal basis function can be used as reliable indicators for detecting (small) changes, interpreting the physical meaning of the detected changes without a priori knowledge of the monitored system and quantifying the uncertainty bounds of the detected changes. The classification errors were analyzed using the standard detection theory to evaluate the performance of the developed SHM methodology. An optimal classifier design procedure was also proposed and evaluated to minimize type II (or 'missed') errors

  9. Morphological patterns of lip prints in Mangaloreans based on Suzuki and Tsuchihashi classification

    Science.gov (United States)

    Jeergal, Prabhakar A; Pandit, Siddharth; Desai, Dinkar; Surekha, R; Jeergal, Vasanti A

    2016-01-01

    Introduction: Cheiloscopy is the study of the furrows or grooves present on the red part or vermilion border of the human lips. The present study aims to classify the characteristics of lip prints and to know the most common morphological pattern specific to Mangalorean people of Southern India. For the first time, this study also assesses the association between gender and different lip segments within a population. Materials and Methods: A total of 200 residents of Mangalore (100 males and 100 females) were included of age ranging from 18 years to 60 years. Materials used to take the impression of lips included red lipstick, A4 size white bond paper and cellophane tape. The prints obtained were scanned using a Canon Image Scanner and stored in a folder on a personal computer. The images were cropped and inverted in gray scale using Adobe Photoshop software. Each lip print was divided into eight segments and was examined. Suzuki and Tsuchihashi's classification (1970) was used to classify the types of grooves, and the results were statistically analyzed. Six types of grooves were recorded in the Mangalorean's lips. Statistical Analysis: Association between gender and different lip segments was tested using Chi-square analysis in the given population. Results: In males, the groove Type I' was the highest recorded followed by Type III, Type II, Type I, Type IV and Type V in descending order. In females, Type I' was the highest recorded followed by Type II, Type III, Type IV, Type I and Type V in descending order. Conclusion: Males and females displayed statistically significant differences in lip print patterns for different lip sites: lower medial lip, as well as upper and lower lateral segments. Only the upper medial lip segment displayed no statistically significant difference in lip print pattern between males and females. This shows that the distribution of lip prints is generally dissimilar for males and females, with varying predominance according to lip

  10. Pattern classification approach to characterizing solitary pulmonary nodules imaged on high-resolution computed tomography

    Science.gov (United States)

    McNitt-Gray, Michael F.; Hart, Eric M.; Goldin, Jonathan G.; Yao, Chih-Wei; Aberle, Denise R.

    1996-04-01

    The purpose of our study was to characterize solitary pulmonary nodules (SPN) as benign or malignant based on pattern classification techniques using size, shape, density and texture features extracted from HRCT images. HRCT images of patients with a SPN are acquired, routed through a PACS and displayed on a thoracic radiology workstation. Using the original data, the SPN is semiautomatically contoured using a nodule/background threshold. The contour is used to calculate size and several shape parameters, including compactness and bending energy. Pixels within the interior of the contour are used to calculate several features including: (1) nodule density-related features, such as representative Hounsfield number and moment of inertia, and (2) texture measures based on the spatial gray level dependence matrix and fractal dimension. The true diagnosis of the SPN is established by histology from biopsy or, in the case of some benign nodules, extended follow-up. Multi-dimensional analyses of the features are then performed to determine which features can discriminate between benign and malignant nodules. When a sufficient number of cases are obtained two pattern classifiers, a linear discriminator and a neural network, are trained and tested using a select subset of features. Preliminary data from nine (9) nodule cases have been obtained and several features extracted. While the representative CT number is a reasonably good indicator, it is an inconclusive predictor of SPN diagnosis when considered by itself. Separation between benign and malignant nodules improves when other features, such as the distribution of density as measured by moment of inertia, are included in the analysis. Software has been developed and preliminary results have been obtained which show that individual features may not be sufficient to discriminate between benign and malignant nodules. However, combinations of these features may be able to discriminate between these two classes. With

  11. SENSING URBAN LAND-USE PATTERNS BY INTEGRATING GOOGLE TENSORFLOW AND SCENE-CLASSIFICATION MODELS

    Directory of Open Access Journals (Sweden)

    Y. Yao

    2017-09-01

    Full Text Available With the rapid progress of China’s urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model’s ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI. Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs. To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737 for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

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

    Science.gov (United States)

    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

  13. Eruptive pattern classification on Mount Etna (Sicily) and Piton de la Fournaise (La Réunion)

    Science.gov (United States)

    Falsaperla, Susanna; Langer, Horst; Ferrazzini, Valérie

    2016-04-01

    In the framework of the European MEDiterrranean Supersite Volcanoes (MED­SUV) project, Mt. Etna (Italy) and Piton de la Fournaise (La Réunion) were chosen as "European Supersite Demonstrator" and test site, respectively, to promote the transfer and implementation of efficient tools for the identification of impending volcanic activity. Both are "open-conduit volcanoes", forming ideal sites for the test and validation of innovative concepts, which can contribute to minimize volcanic hazard. One of the aims of the MED-SUV project was the development of software for machine learning applicable to data processing for early-warning purposes. Near-real time classification of continuous seismic data stream has been carried out in the control room of INGV Osservatorio Etneo since 2010. Subsequently, automatic alert procedures were activated. In the light of the excellent results for the 24/7 surveillance of Etna, we examine the portability of tools developed in the framework of the project when applied to seismic data recorded at Piton de la Fournaise. In the present application to data recorded at Piton de la Fournaise, the classifier aims at highlighting changes in the frequency content of the background seismic signal heralding the activation of the volcanic source and the imminent eruption. We describe the preliminary results of this test on a set of data of nearly two years starting on January 2014. This period follows three years of inactivity and deflation of the volcano and marks a renewal of the volcano activity with inflation, deep seismicity (-7km bsl) and five eruptions with fountains and lava flows that lasted from a few hours to more than two months. We discuss here the necessary tuning for the implementation of the software to the new dataset analyzed. We also propose a comparison with the results of pattern classification regarding recent eruptive activity at Etna.

  14. Classification of Headache Disorders: Extending to a Multiaxial System.

    Science.gov (United States)

    Martin, Paul R

    2016-11-01

    This article argues for extending the International Classification of Headache Disorders to include information that goes beyond diagnosis. The obvious model is a multiaxial system as has been developed for other taxonomies. An axis for recording disability and impact on functioning, and an axis for recording the triggers of headache/migraine, are perhaps the strongest contenders for adding to the system, but there are other possibilities such as lifestyle factors relevant to headache. Extensions such as these would contribute to headache management, provide clear targets for change, and encourage adoption of a biopsychosocial perspective. © 2016 American Headache Society.

  15. An optoelectronic system for fringe pattern analysis

    Science.gov (United States)

    Sciammarella, C. A.; Ahmadshahi, M.

    A system capable of retrieving and processing information recorded in fringe patterns is reported. The principal components are described as well as the architecture in which they are assembled. An example of application is given.

  16. Pattern classification of brain activation during emotional processing in subclinical depression : psychosis proneness as potential confounding factor

    NARCIS (Netherlands)

    Modinos, Gemma; Mechelli, Andrea; Pettersson-Yeo, William; Allen, Paul; McGuire, Philip; Aleman, Andre

    2013-01-01

    We used Support Vector Machine (SVM) to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II). Two groups

  17. Comparison of Pixel-Based and Object-Based Classification Using Parameters and Non-Parameters Approach for the Pattern Consistency of Multi Scale Landcover

    Science.gov (United States)

    Juniati, E.; Arrofiqoh, E. N.

    2017-09-01

    Information extraction from remote sensing data especially land cover can be obtained by digital classification. In practical some people are more comfortable using visual interpretation to retrieve land cover information. However, it is highly influenced by subjectivity and knowledge of interpreter, also takes time in the process. Digital classification can be done in several ways, depend on the defined mapping approach and assumptions on data distribution. The study compared several classifiers method for some data type at the same location. The data used Landsat 8 satellite imagery, SPOT 6 and Orthophotos. In practical, the data used to produce land cover map in 1:50,000 map scale for Landsat, 1:25,000 map scale for SPOT and 1:5,000 map scale for Orthophotos, but using visual interpretation to retrieve information. Maximum likelihood Classifiers (MLC) which use pixel-based and parameters approach applied to such data, and also Artificial Neural Network classifiers which use pixel-based and non-parameters approach applied too. Moreover, this study applied object-based classifiers to the data. The classification system implemented is land cover classification on Indonesia topographic map. The classification applied to data source, which is expected to recognize the pattern and to assess consistency of the land cover map produced by each data. Furthermore, the study analyse benefits and limitations the use of methods.

  18. Neighborhood Hypergraph Based Classification Algorithm for Incomplete Information System

    Directory of Open Access Journals (Sweden)

    Feng Hu

    2015-01-01

    Full Text Available The problem of classification in incomplete information system is a hot issue in intelligent information processing. Hypergraph is a new intelligent method for machine learning. However, it is hard to process the incomplete information system by the traditional hypergraph, which is due to two reasons: (1 the hyperedges are generated randomly in traditional hypergraph model; (2 the existing methods are unsuitable to deal with incomplete information system, for the sake of missing values in incomplete information system. In this paper, we propose a novel classification algorithm for incomplete information system based on hypergraph model and rough set theory. Firstly, we initialize the hypergraph. Second, we classify the training set by neighborhood hypergraph. Third, under the guidance of rough set, we replace the poor hyperedges. After that, we can obtain a good classifier. The proposed approach is tested on 15 data sets from UCI machine learning repository. Furthermore, it is compared with some existing methods, such as C4.5, SVM, NavieBayes, and KNN. The experimental results show that the proposed algorithm has better performance via Precision, Recall, AUC, and F-measure.

  19. Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

    Science.gov (United States)

    Srimani, P. K.; Parimala, Y. G.

    2011-12-01

    A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.

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

    Science.gov (United States)

    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.

  1. The influence of spine surgeons' experience on the classification and intraobserver reliability of the novel AOSpine thoracolumbar spine injury classification system : an international study

    NARCIS (Netherlands)

    Sadiqi, Said; Oner, F. Cumhur; Dvorak, Marcel F.; Aarabi, Bizhan; Schroeder, Gregory D.; Vaccaro, Alexander R.

    2015-01-01

    Study Design. International validation study. Objective. To investigate the influence of the spine surgeons' level of experience on the intraobserver reliability of the novel AOSpine Thoracolumbar Spine Injury Classification system, and the appropriate classification according to this system.

  2. A system for learning statistical motion patterns.

    Science.gov (United States)

    Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

    2006-09-01

    Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

  3. 42 CFR 412.10 - Changes in the DRG classification system.

    Science.gov (United States)

    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... after the same date the payment rates are effective. (b) Basis for changes in the DRG classification...

  4. Planning pesticides usage for herbal and animal pests based on intelligent classification system with image processing and neural networks

    Directory of Open Access Journals (Sweden)

    Dimililer Kamil

    2018-01-01

    Full Text Available Pests are divided into two as herbal and animal pests in agriculture, and detection and use of minimum pesticides are quite challenging task. Last three decades, researchers have been improving their studies on these manners. Therefore, effective, efficient, and as well as intelligent systems are designed and modelled. In this paper, an intelligent classification system is designed for detecting pests as herbal or animal to use of proper pesticides accordingly. The designed system suggests two main stages. Firstly, images are processed using different image processing techniques that images have specific distinguishing geometric patterns. The second stage is neural network phase for classification. A backpropagation neural network is used for training and testing with processed images. System is tested, and experiment results show efficiency and effective classification rate. Autonomy and time efficiency within the pesticide usage are also discussed.

  5. Pattern fuel assembly loading system

    International Nuclear Information System (INIS)

    Ahmed, H.J.; Gerkey, K.S.; Miller, T.W.; Wylie, M.E.

    1986-01-01

    This patent describes an interactive system for facilitating preloading of fuel rods into magazines, which comprises: an operator work station adapted for positioning between a supply of fuel rods of predetermined types, and the magazine defining grid locations for a predetermined fuel assembly; display means associated with the work station; scanner means associated with the work station and adapted for reading predetermined information accompanying the fuel rods; a rectangular frame adapted for attachment to one end of the fuel assembly loading magazine; prompter/detector means associated with the frame for detecting insertion of a fuel rod into the magazine; and processing means responsive to the scanner means and the sensing means for prompting the operator via the display means to pre-load the fuel rods into desired grid locations in the magazine. An apparatus is described for facilitating pre-loading of fuel rods in predetermined grid locations of a fuel assembly loading magazine, comprising: a rectangular frame adapted for attachment to one end of the fuel assembly loading magazine; and means associated with the frame for detecting insertion of fuel rods into the magazine

  6. An artificial intelligence based improved classification of two-phase flow patterns with feature extracted from acquired images.

    Science.gov (United States)

    Shanthi, C; Pappa, N

    2017-05-01

    Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are recorded for a period and converted to 2D images for processing. The textural and shape features extracted using image processing are applied as inputs to various classification schemes namely fuzzy logic, SVM and SVM with PCA in order to identify the type of flow pattern. The results obtained are compared and it is observed that SVM with features reduced using PCA gives the better classification accuracy and computationally less intensive than other two existing schemes. This study results cover industrial application needs including oil and gas and any other gas-liquid two-phase flows. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Forecasting Changes in Stock Prices on the Basis of Patterns Identified with the Use of Data Classification Methods

    Directory of Open Access Journals (Sweden)

    Szanduła Jacek

    2014-06-01

    Full Text Available The paper develops the concept of harnessing data classification methods to recognize patterns in stock prices. The author defines a formation as a pattern vector describing the financial instrument. Elements of such a vector can be related to the stock price as well as sales volume and other characteristics of the financial instrument. The study uses data concerning selected companies listed on the stock exchange in New York. It takes into account a number of variables that describe the behavior of prices and volume, both in the short and long term. Partitioning around medoids method has been used for data classification (for pattern recognition. An evaluation of the possibility of using certain formations for practical purposes has also been presented.

  8. Movement imagery classification in EMOTIV cap based system by Naïve Bayes.

    Science.gov (United States)

    Stock, Vinicius N; Balbinot, Alexandre

    2016-08-01

    Brain-computer interfaces (BCI) provide means of communications and control, in assistive technology, which do not require motor activity from the user. The goal of this study is to promote classification of two types of imaginary movements, left and right hands, in an EMOTIV cap based system, using the Naïve Bayes classifier. A preliminary analysis with respect to results obtained by other experiments in this field is also conducted. Processing of the electroencephalography (EEG) signals is done applying Common Spatial Pattern filters. The EPOC electrodes cap is used for EEG acquisition, in two test subjects, for two distinct trial formats. The channels picked are FC5, FC6, P7 and P8 of the 10-20 system, and a discussion about the differences of using C3, C4, P3 and P4 positions is proposed. Dataset 3 of the BCI Competition II is also analyzed using the implemented algorithms. The maximum classification results for the proposed experiment and for the BCI Competition dataset were, respectively, 79% and 85% The conclusion of this study is that the picked positions for electrodes may be applied for BCI systems with satisfactory classification rates.

  9. Patterns of hand preference for pairs of actions and the classification of handedness.

    Science.gov (United States)

    Annett, Marian

    2009-08-01

    Pairs of actions such as write x throw and throw x racquet were examined for items of the Annett hand preference questionnaire (AHPQ). Right (R) and left (L) responses were described for frequencies of RR, RL, LR, and LL pairings (write x throw etc.) in a large representative combined sample with the aim of discovering the distribution over the population as a whole. The frequencies of RL pairings varied significantly over the different item pairs but the frequencies of LR pairings were fairly constant. An important difference was found between primary actions (originally write, throw, racquet, match, toothbrush, hammer with the later addition of scissors for right-handers) and non-primary actions (needle and thread, broom, spade, dealing playing cards, and unscrewing the lid of a jar). For primary actions, there were similar numbers of right and left writers using the 'other' hand. For non-primary actions more right-handers used the left hand than for primary actions but more left-handers did not use the right hand. That is, different frequencies of response to primary versus non-primary actions were found for right-handers but not for left-handers. The pattern of findings was repeated for a corresponding analysis of left-handed throwing x AHPQ actions. The findings have implications for the classification of hand preferences and for analyses of the nature of hand skill.

  10. Auroral arc classification scheme based on the observed arc-associated electric field pattern

    International Nuclear Information System (INIS)

    Marklund, G.

    1983-06-01

    Radar and rocket electric field observations of auroral arcs have earlier been used to identify essentially four different arc types, namely anticorrelation and correlation arcs (with, respectively, decreased and increased arc-assocaited field) and asymmetric and reversal arcs. In this paper rocket double probe and supplementary observations from the literature, obtained under various geophysical conditions, are used to organize the different arc types on a physical rather than morphological basis. This classification is based on the relative influence on the arc electric field pattern from the two current continuity mechanisms, polarisation electric fields and Birkeland currents. In this context the tangential electric field plays an essential role and it is thus important that it can be obtained with both high accuracy and resolution. In situ observations by sounding rockets are shown to be better suited for this specific task than monostatic radar observations. Depending on the dominating mechanism, estimated quantitatively for a number of arc-crossings, the different arc types have been grouped into the following main categories: Polarisation arcs, Birkeland current arcs and combination arcs. Finally the high altitude potential distributions corresponding to some of the different arc types are presented. (author)

  11. Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

    Science.gov (United States)

    Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

    2016-01-01

    We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

  12. Fault Tolerant Neural Network for ECG Signal Classification Systems

    Directory of Open Access Journals (Sweden)

    MERAH, M.

    2011-08-01

    Full Text Available The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

  13. Classification analysis of organization factors related to system safety

    International Nuclear Information System (INIS)

    Liu Huizhen; Zhang Li; Zhang Yuling; Guan Shihua

    2009-01-01

    This paper analyzes the different types of organization factors which influence the system safety. The organization factor can be divided into the interior organization factor and exterior organization factor. The latter includes the factors of political, economical, technical, law, social culture and geographical, and the relationships among different interest groups. The former includes organization culture, communication, decision, training, process, supervision and management and organization structure. This paper focuses on the description of the organization factors. The classification analysis of the organization factors is the early work of quantitative analysis. (authors)

  14. A complete electrical hazard classification system and its application

    Energy Technology Data Exchange (ETDEWEB)

    Gordon, Lloyd B [Los Alamos National Laboratory; Cartelli, Laura [Los Alamos National Laboratory

    2009-01-01

    The Standard for Electrical Safety in the Workplace, NFPA 70E, and relevant OSHA electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. This leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. Examples include lasers, accelerators, capacitor banks, electroplating systems, induction and dielectric heating systems, etc. Although all such systems are fed by 50/60 Hz alternating current (ac) power, we find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50160 Hz power. Over the past 10 years there has been an effort to develop a method of classifying all of the electrical hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Initially, national electrical safety codes required the qualified worker only to know the source voltage to determine the shock hazard. Later, as arc flash hazards were understood, the fault current and clearing time were needed. These items are still insufficient to fully characterize all types of

  15. An intelligent temporal pattern classification system using fuzzy ...

    Indian Academy of Sciences (India)

    posed work. Section 5 analyses the comparative performance of our proposed algorithm with the other existing ..... Oldpeak: ST depression induced by exercise relative to rest. Slope: the slope of the ..... Academic Press. Gui H and Qiao J 2012 ...

  16. Participatory Classification in a System for Assessing Multimodal Transportation Patterns

    Science.gov (United States)

    2015-02-17

    corresponding databases on each side, and data flows through the database based on object state. We illustrate this with the example of the trip flow, and...offline in batch mode. The results of the offline processing are stored in the database for easy access by the webapp layer. We sketch the algorithms...ones that don’t. As we can see from Table 2, all methods that expose PII are HTTP POST methods, and require a JSON Web Token (JWT) for authenti- cation

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

    Science.gov (United States)

    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.

  18. Automated pattern recognition system for noise analysis

    International Nuclear Information System (INIS)

    Sides, W.H. Jr.; Piety, K.R.

    1980-01-01

    A pattern recognition system was developed at ORNL for on-line monitoring of noise signals from sensors in a nuclear power plant. The system continuousy measures the power spectral density (PSD) values of the signals and the statistical characteristics of the PSDs in unattended operation. Through statistical comparison of current with past PSDs (pattern recognition), the system detects changes in the noise signals. Because the noise signals contain information about the current operational condition of the plant, a change in these signals could indicate a change, either normal or abnormal, in the operational condition

  19. Improved pattern recognition systems by hybrid methods

    International Nuclear Information System (INIS)

    Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

    1978-12-01

    This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

  20. The reliability and validity of the Saliba Postural Classification System.

    Science.gov (United States)

    Collins, Cristiana Kahl; Johnson, Vicky Saliba; Godwin, Ellen M; Pappas, Evangelos

    2016-07-01

    To determine the reliability and validity of the Saliba Postural Classification System (SPCS). Two physical therapists classified pictures of 100 volunteer participants standing in their habitual posture for inter and intra-tester reliability. For validity, 54 participants stood on a force plate in a habitual and a corrected posture, while a vertical force was applied through the shoulders until the clinician felt a postural give. Data were extracted at the time the give was felt and at a time in the corrected posture that matched the peak vertical ground reaction force (VGRF) in the habitual posture. Inter-tester reliability demonstrated 75% agreement with a Kappa = 0.64 (95% CI = 0.524-0.756, SE = 0.059). Intra-tester reliability demonstrated 87% agreement with a Kappa = 0.8, (95% CI = 0.702-0.898, SE = 0.05) and 80% agreement with a Kappa = 0.706, (95% CI = 0.594-0818, SE = 0.057). The examiner applied a significantly higher (p < 0.001) peak vertical force in the corrected posture prior to a postural give when compared to the habitual posture. Within the corrected posture, the %VGRF was higher when the test was ongoing vs. when a postural give was felt (p < 0.001). The %VGRF was not different between the two postures when comparing the peaks (p = 0.214). The SPCS has substantial agreement for inter- and intra-tester reliability and is largely a valid postural classification system as determined by the larger vertical forces in the corrected postures. Further studies on the correlation between the SPCS and diagnostic classifications are indicated.

  1. Classification of the NPP core and fuel assembly states by the pattern recoguition method

    International Nuclear Information System (INIS)

    Egorov, Yu.A.; Ivanov, E.A.; Kazakov, S.V.; Tolstykh, V.D.

    1981-01-01

    The patern recognition methods used for solving the problems of analysis of radiohazard states of fuel assemblies (FA) and uranium-graphite reactor core as a whole are considered. The problem under consideration is formulated as the problem of studying the deformation of signal space for the system of fuel can tightness control on the background of fuel assembly character space as characteristics, reflecting the FA living conditions in a core power, coolant flow rate, coolant steam content and pipeline length up to the detector of the system of fuel can tightness control are chosen. The analysis of deformation of the fuel can tightness control system signal space is completed by its division into two spaces: the background signal space and the valid signal space. For solving the problem the method of basic components and variational approach have been used. The conclusion is drawn that as the extent of FA failure and valid signals of by-channel system of fuel can tightness control are in one-to-one correspondence it is advantageous to solve the problem of FA state classification in the space of valid signals [ru

  2. Automatic Classification of Station Quality by Image Based Pattern Recognition of Ppsd Plots

    Science.gov (United States)

    Weber, B.; Herrnkind, S.

    2017-12-01

    The number of seismic stations is growing and it became common practice to share station waveform data in real-time with the main data centers as IRIS, GEOFON, ORFEUS and RESIF. This made analyzing station performance of increasing importance for automatic real-time processing and station selection. The value of a station depends on different factors as quality and quantity of the data, location of the site and general station density in the surrounding area and finally the type of application it can be used for. The approach described by McNamara and Boaz (2006) became standard in the last decade. It incorporates a probability density function (PDF) to display the distribution of seismic power spectral density (PSD). The low noise model (LNM) and high noise model (HNM) introduced by Peterson (1993) are also displayed in the PPSD plots introduced by McNamara and Boaz allowing an estimation of the station quality. Here we describe how we established an automatic station quality classification module using image based pattern recognition on PPSD plots. The plots were split into 4 bands: short-period characteristics (0.1-0.8 s), body wave characteristics (0.8-5 s), microseismic characteristics (5-12 s) and long-period characteristics (12-100 s). The module sqeval connects to a SeedLink server, checks available stations, requests PPSD plots through the Mustang service from IRIS or PQLX/SQLX or from GIS (gempa Image Server), a module to generate different kind of images as trace plots, map plots, helicorder plots or PPSD plots. It compares the image based quality patterns for the different period bands with the retrieved PPSD plot. The quality of a station is divided into 5 classes for each of the 4 bands. Classes A, B, C, D define regular quality between LNM and HNM while the fifth class represents out of order stations with gain problems, missing data etc. Over all period bands about 100 different patterns are required to classify most of the stations available on the

  3. Light-water reactors reference system classification for the European reliability data system (ERDS)

    International Nuclear Information System (INIS)

    Melis, M.; Mancini, G.

    1982-01-01

    The reference system classification represents a basic stage in the organization of the European reliability data system (ERDS) for light-water reactors, a project actually in development at the Joint Research Centre, Ispra. This project is concerned with operational reliability data collection from the various ''national'' data banks, and centralization in a European reliability data system, so improving the significance of the resulting reliability evaluations. In the framework of the ERDS project, the reference system classification provides a LWR functional break-down and represents a plant-unique identification in the process of homogenization of event-data coming from the various ''national'' organizations. The report, after a brief description of the main objectives of the ERDS project, reviews the criteria followed in the elaboration of the reference system classification; then the detailed classification is presented. The nuclear power station is subdivided in about 180 systems. To each system a sheet is associated, containing: a comprehensive description of system-functions and boundaries; a descritpion of the plant operating mode, linked to the various system functions; a list of the main interface system; and finally, a list of the main components, including type and safety classification

  4. Changing tides: increasing evidence to embrace a patient classification system.

    Science.gov (United States)

    Malloch, Kathy

    2012-01-01

    The effective use of a patient classification system (PCS) in a way that provides value to all health care organizations has yet to be realized given the challenging developmental pathway of these systems. As the science and technology of workforce management emerges along with evidence to support the relationships between nurse work and patient care needs, it is no longer appropriate to rely on systems that provide aggregated and minimal data to address the need for safer patient care and retention of nurses. Specificity about patient care needs in a valid and reliable PCS is essential on our pathway to improved resource utilization, improved decision making, integration of nurse cognitive and knowledge work, and management of variances from planned resource use. Advancements with technology, the ability to create and monitor equitable nurse-patient assignments, conceptual clarity, evidence, regulatory requirements, and professional role development point to a new receptiveness for PCSs.

  5. DNA methylation-based classification of central nervous system tumours

    DEFF Research Database (Denmark)

    Capper, David; Jones, David T.W.; Sill, Martin

    2018-01-01

    Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variabil......Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter......-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show...

  6. A data-stream classification system for investigating terrorist threats

    Science.gov (United States)

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

    2016-05-01

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

  7. Gender and cultural issues in psychiatric nosological classification systems.

    Science.gov (United States)

    van de Water, Tanya; Suliman, Sharain; Seedat, Soraya

    2016-08-01

    Much has changed since the two dominant mental health nosological systems, the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual of Mental Disorders (DSM), were first published in 1900 and 1952, respectively. Despite numerous modifications to stay up to date with scientific and cultural changes (eg, exclusion of homosexuality as a disorder) and to improve the cultural sensitivity of psychiatric diagnoses, the ICD and DSM have only recently renewed attempts at harmonization. Previous nosological iterations demonstrate the oscillation in the importance placed on the biological focus, highlighting the tension between a gender- and culture-free nosology (solely biological) and a contextually relevant understanding of mental illness. In light of the release of the DSM 5, future nosological systems, such as the ICD 11, scheduled for release in 2017, and the Research Development Criteria (RDoC), can learn from history and apply critiques. This article aims to critically consider gender and culture in previous editions of the ICD and DSM to inform forthcoming classifications.

  8. Rapid hyperspectral image classification to enable autonomous search systems

    Directory of Open Access Journals (Sweden)

    Raj Bridgelal

    2016-11-01

    Full Text Available The emergence of lightweight full-frame hyperspectral cameras is destined to enable autonomous search vehicles in the air, on the ground and in water. Self-contained and long-endurance systems will yield important new applications, for example, in emergency response and the timely identification of environmental hazards. One missing capability is rapid classification of hyperspectral scenes so that search vehicles can immediately take actions to verify potential targets. Onsite verifications minimise false positives and preclude the expense of repeat missions. Verifications will require enhanced image quality, which is achievable by either moving closer to the potential target or by adjusting the optical system. Such a solution, however, is currently impractical for small mobile platforms with finite energy sources. Rapid classifications with current methods demand large computing capacity that will quickly deplete the on-board battery or fuel. To develop the missing capability, the authors propose a low-complexity hyperspectral image classifier that approaches the performance of prevalent classifiers. This research determines that the new method will require at least 19-fold less computing capacity than the prevalent classifier. To assess relative performances, the authors developed a benchmark that compares a statistic of library endmember separability in their respective feature spaces.

  9. Tangata whaiora/consumers perspectives on current psychiatric classification systems

    Directory of Open Access Journals (Sweden)

    Wells Debra

    2008-06-01

    Full Text Available Abstract Background A number of studies have been undertaken with the aim of considering the utility of mental health classification systems from the perspective of a variety of stakeholders. There is a lack of research on how useful consumers/tangata whaiora think these are in assisting them in their recovery. Methods Seventy service users were involved in seven focus groups in order to consider this question. Results and discussion While for clinicians diagnosing someone might be a discrete event and easily forgotten as a moment in a busy schedule, most people in this study remembered the occasion and aftermath very clearly. The overall consensus was that whether being 'diagnosed' was helpful or not, in large part, depended on how the process happened and what resulted from being 'labeled' in the person's life. Conclusion Overall, people thought that in terms of their recovery, the classification systems were tools and their utility depended on how they were used. They suggested that whatever tool was used it needed to help them make sense of their distress and provide them with a variety of supports, not just medication, to assist them to live lives that were meaningful to them.

  10. Weather Type classification over Chile; patterns, trends, and impact in precipitation and temperature

    Science.gov (United States)

    Frias, T.; Trigo, R. M.; Garreaud, R.

    2009-04-01

    The Andes Cordillera induces considerable disturbances on the structure and evolution of the pressure systems that influences South America. Different weather types for southern South America are derived from the daily maps of geopotential height at 850hPa corresponding to a 42 year period, spanning from 1958 to 2000. Here we have used the ECWMF ERA-40 reanalysis dataset to construct an automated version of the Lamb Weather type (WTs) classification scheme (Jones et al., 1993) developed for the UK. We have identified 8 basic WTs (Cyclonic, Anticyclonic and 6 main directional types) following a similar methodology to that previously adopted by Trigo and DaCamara, 2000 (for Iberia). This classification was applied to two regions of study (CLnorth and CLsouth) which differ 20° in latitude, so that the vast Chile territory could be covered. Then were assessed the impact of the occurrence of this weather types in precipitation in Chile, as well as in the distribution of precipitation and temperature fields (reanalysis data) in southern half of South America. The results allow to conclude that the precipitation in central region of Chile is largely linked with the class occurrence (concerning CLnorth) of cyclonic circulation and of West quadrant (SW, W and NW), despite of it's relatively low frequency. In CLsouth, for its part, it is verified that the most frequent circulation is from the west quadrant, although the associated amount of rainfall is lower than in CLnorth. There was also a general decrease of precipitation at local weather stations chosen in the considered period of study, particularly in austral winter.

  11. Image processing system for flow pattern measurements

    International Nuclear Information System (INIS)

    Ushijima, Satoru; Miyanaga, Yoichi; Takeda, Hirofumi

    1989-01-01

    This paper describes the development and application of an image processing system for measurements of flow patterns occuring in natural circulation water flows. In this method, the motions of particles scattered in the flow are visualized by a laser light slit and they are recorded on normal video tapes. These image data are converted to digital data with an image processor and then transfered to a large computer. The center points and pathlines of the particle images are numerically analized, and velocity vectors are obtained with these results. In this image processing system, velocity vectors in a vertical plane are measured simultaneously, so that the two dimensional behaviors of various eddies, with low velocity and complicated flow patterns usually observed in natural circulation flows, can be determined almost quantitatively. The measured flow patterns, which were obtained from natural circulation flow experiments, agreed with photographs of the particle movements, and the validity of this measuring system was confirmed in this study. (author)

  12. Identification system by eye retinal pattern

    International Nuclear Information System (INIS)

    Sunagawa, Takahisa; Shibata, Susumu

    1987-01-01

    Identification system by eye retinal pattern is introduced from the view-point of history of R and D, measurement, apparatus, evaluation tests, safety and application. According to our evaluation tests, enrolling time is approximately less than 1 min, verification time is a few seconds and false accept rate is 0 %. Evaluation tests at Sandia National Laboratories in USA show the comparison data of false accept rates such as 0 % for eye retinal pattern, 10.5 % for finger-print, 5.8 % for signature dynamics and 17.7 % for speaker voice. The identification system by eye retinal pattern has only three applications in Japan, but there has been a number of experience in USA. This fact suggests that the system will become an important means for physical protections not only in nuclear field but also in other industrial fields in Japan. (author)

  13. A Game Player Expertise Level Classification System Using Electroencephalography (EEG

    Directory of Open Access Journals (Sweden)

    Syed Muhammad Anwar

    2017-12-01

    Full Text Available The success and wider adaptability of smart phones has given a new dimension to the gaming industry. Due to the wide spectrum of video games, the success of a particular game depends on how efficiently it is able to capture the end users’ attention. This leads to the need to analyse the cognitive aspects of the end user, that is the game player, during game play. A direct window to see how an end user responds to a stimuli is to look at their brain activity. In this study, electroencephalography (EEG is used to record human brain activity during game play. A commercially available EEG headset is used for this purpose giving fourteen channels of recorded EEG brain activity. The aim is to classify a player as expert or novice using the brain activity as the player indulges in the game play. Three different machine learning classifiers have been used to train and test the system. Among the classifiers, naive Bayes has outperformed others with an accuracy of 88 % , when data from all fourteen EEG channels are used. Furthermore, the activity observed on electrodes is statistically analysed and mapped for brain visualizations. The analysis has shown that out of the available fourteen channels, only four channels in the frontal and occipital brain regions show significant activity. Features of these four channels are then used, and the performance parameters of the four-channel classification are compared to the results of the fourteen-channel classification. It has been observed that support vector machine and the naive Bayes give good classification accuracy and processing time, well suited for real-time applications.

  14. Food Classification Systems Based on Food Processing: Significance and Implications for Policies and Actions: A Systematic Literature Review and Assessment.

    Science.gov (United States)

    Moubarac, Jean-Claude; Parra, Diana C; Cannon, Geoffrey; Monteiro, Carlos A

    2014-06-01

    This paper is the first to make a systematic review and assessment of the literature that attempts methodically to incorporate food processing into classification of diets. The review identified 1276 papers, of which 110 were screened and 21 studied, derived from five classification systems. This paper analyses and assesses the five systems, one of which has been devised and developed by a research team that includes co-authors of this paper. The quality of the five systems is assessed and scored according to how specific, coherent, clear, comprehensive and workable they are. Their relevance to food, nutrition and health, and their use in various settings, is described. The paper shows that the significance of industrial food processing in shaping global food systems and supplies and thus dietary patterns worldwide, and its role in the pandemic of overweight and obesity, remains overlooked and underestimated. Once food processing is systematically incorporated into food classifications, they will be more useful in assessing and monitoring dietary patterns. Food classification systems that emphasize industrial food processing, and that define and distinguish relevant different types of processing, will improve understanding of how to prevent and control overweight, obesity and related chronic non-communicable diseases, and also malnutrition. They will also be a firmer basis for rational policies and effective actions designed to protect and improve public health at all levels from global to local.

  15. On safety classification of instrumentation and control systems and their components

    International Nuclear Information System (INIS)

    Yastrebenetskij, M.A.; Rozen, Yu.V.

    2004-01-01

    Safety classification of instrumentation and control systems (I and C) and their components (hardware, software, software-hardware complexes) is described: - evaluation of classification principles and criteria in Ukrainian standards and rules; comparison between Ukrainian and international principles and criteria; possibility and ways of coordination of Ukrainian and international standards related to (I and C) safety classification

  16. Analysis of the Carnegie Classification of Community Engagement: Patterns and Impact on Institutions

    Science.gov (United States)

    Driscoll, Amy

    2014-01-01

    This chapter describes the impact that participation in the Carnegie Classification for Community Engagement had on the institutions of higher learning that applied for the classification. This is described in terms of changes in direct community engagement, monitoring and reporting on community engagement, and levels of student and professor…

  17. Development of a comprehensive radioactive waste classification system

    International Nuclear Information System (INIS)

    Smith, C.F.; Cohen, J.J.

    1989-01-01

    Several previous studies have been conducted with the intent of developing a rational system for classification of radioactive wastes. Although none of the proposed systems has gained general acceptance, certain waste classes, specifically high-level waste and low-level waste suitable for shallow land burial have been essentially defined by regulation. Wastes which remain undefined include: those intermediate level wastes which require more restrictive controls than that provided by shallow land burial but not the high degree of isolation needed for high level wastes, and wastes below regulatory concern (BRC) which entail so low a radiological risk that they can be managed according to their nonradiological properties. This study has developed a framework within which the complete spectrum of radioactive wastes can be defined

  18. Added value of prone CT in the assessment of honeycombing and classification of usual interstitial pneumonia pattern.

    Science.gov (United States)

    Kim, Minjae; Lee, Sang Min; Song, Jae-Woo; Do, Kyung-Hyun; Lee, Hyun Joo; Lim, Soyeoun; Choe, Jooae; Park, Kye Jin; Park, Hyo Jung; Kim, Hwa Jung; Seo, Joon Beom

    2017-06-01

    To retrospectively investigate whether prone CT improves identification of honeycombing and classification of UIP patterns in terms of interobserver agreement and accuracy using pathological results as a reference standard. Institutional review board approval with waiver of patients' informed consent requirement was obtained. HRCTs of 86 patients with pathologically proven UIP, NSIP and chronic HP between January 2011 and April 2015 were evaluated by 8 observers. Observers were asked to review supine only set and supine and prone combined set and determine the presence of honeycombing and UIP classification (UIP, possible UIP, inconsistent with UIP). The diagnosis was regarded as correct when UIP pattern on CT corresponded to pathological UIP. Interobserver agreement of honeycombing identification among radiologists was only fair on the supine and combined set (weighted κ=0.31 and 0.34). Additional review of prone images demonstrated a significant improvement in interobserver agreement (weighted κ) of UIP classification from 0.25 to 0.33. Prone CT conferred a significant improvement in interobserver agreement of UIP classification for trainee radiologists (from 0.10 to 0.34) while no improvement was found for board-certified radiologists (from 0.35 to 0.31). There were no significant differences in the accuracy of UIP pattern with reference to pathological results between the supine and combined set (78.8% (145/184) and 81.3% (179/220), P=0.612). Additional review of prone CT can improve overall interobserver agreement of UIP classification among radiologists with variable experiences, particularly for less experienced radiologists, while no improvement was found in honeycombing identification. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project

    Directory of Open Access Journals (Sweden)

    Amel Benammar Elgaaied

    2016-01-01

    Full Text Available Antinuclear antibodies (ANAs are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of a CAD (Computer Aided Detection solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%, higher Patterns Accuracy (79,3% versus 48,0% and 66,2%, and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%.

  20. Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project.

    Science.gov (United States)

    Benammar Elgaaied, Amel; Cascio, Donato; Bruno, Salvatore; Ciaccio, Maria Cristina; Cipolla, Marco; Fauci, Alessandro; Morgante, Rossella; Taormina, Vincenzo; Gorgi, Yousr; Marrakchi Triki, Raja; Ben Ahmed, Melika; Louzir, Hechmi; Yalaoui, Sadok; Imene, Sfar; Issaoui, Yassine; Abidi, Ahmed; Ammar, Myriam; Bedhiafi, Walid; Ben Fraj, Oussama; Bouhaha, Rym; Hamdi, Khouloud; Soumaya, Koudhi; Neili, Bilel; Asma, Gati; Lucchese, Mariano; Catanzaro, Maria; Barbara, Vincenza; Brusca, Ignazio; Fregapane, Maria; Amato, Gaetano; Friscia, Giuseppe; Neila, Trai; Turkia, Souayeh; Youssra, Haouami; Rekik, Raja; Bouokez, Hayet; Vasile Simone, Maria; Fauci, Francesco; Raso, Giuseppe

    2016-01-01

    Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of a CAD (Computer Aided Detection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%).

  1. Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project

    Science.gov (United States)

    Benammar Elgaaied, Amel; Cascio, Donato; Bruno, Salvatore; Ciaccio, Maria Cristina; Cipolla, Marco; Fauci, Alessandro; Morgante, Rossella; Taormina, Vincenzo; Gorgi, Yousr; Marrakchi Triki, Raja; Ben Ahmed, Melika; Louzir, Hechmi; Yalaoui, Sadok; Imene, Sfar; Issaoui, Yassine; Abidi, Ahmed; Ammar, Myriam; Bedhiafi, Walid; Ben Fraj, Oussama; Bouhaha, Rym; Hamdi, Khouloud; Soumaya, Koudhi; Neili, Bilel; Asma, Gati; Lucchese, Mariano; Catanzaro, Maria; Barbara, Vincenza; Brusca, Ignazio; Fregapane, Maria; Amato, Gaetano; Friscia, Giuseppe; Neila, Trai; Turkia, Souayeh; Youssra, Haouami; Rekik, Raja; Bouokez, Hayet; Vasile Simone, Maria; Fauci, Francesco; Raso, Giuseppe

    2016-01-01

    Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of a CAD (Computer Aided Detection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%). PMID:27042658

  2. A space-based classification system for RF transients

    International Nuclear Information System (INIS)

    Moore, K.R.; Call, D.; Johnson, S.; Payne, T.; Ford, W.; Spencer, K.; Wilkerson, J.F.; Baumgart, C.

    1993-01-01

    The FORTE (Fast On-Orbit Recording of Transient Events) small satellite is scheduled for launch in mid 1995. The mission is to measure and classify VHF (30--300 MHz) electromagnetic pulses, primarily due to lightning, within a high noise environment dominated by continuous wave carriers such as TV and FM stations. The FORTE Event Classifier will use specialized hardware to implement signal processing and neural network algorithms that perform onboard classification of RF transients and carriers. Lightning events will also be characterized with optical data telemetered to the ground. A primary mission science goal is to develop a comprehensive understanding of the correlation between the optical flash and the VHF emissions from lightning. By combining FORTE measurements with ground measurements and/or active transmitters, other science issues can be addressed. Examples include the correlation of global precipitation rates with lightning flash rates and location, the effects of large scale structures within the ionosphere (such as traveling ionospheric disturbances and horizontal gradients in the total electron content) on the propagation of broad bandwidth RF signals, and various areas of lightning physics. Event classification is a key feature of the FORTE mission. Neural networks are promising candidates for this application. The authors describe the proposed FORTE Event Classifier flight system, which consists of a commercially available digital signal processing board and a custom board, and discuss work on signal processing and neural network algorithms

  3. Tomography patterns of lung disease in systemic sclerosis

    Energy Technology Data Exchange (ETDEWEB)

    Bastos, Andrea de Lima; Correa, Ricardo de Amorim; Ferreira, Gilda Aparecida, E-mail: andrealb@ufmg.br [Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG (Brazil). Faculdade de Medicina

    2016-09-15

    Currently, lung impairment is the leading factor responsible for the morbidity and mortality associated with systemic sclerosis. Therefore, the recognition of the various tomography patterns becomes decisive in the clinical management of these patients. In high-resolution computed tomography studies, the most common pattern is that of nonspecific interstitial pneumonia. However, there are other forms of lung involvement that must also be recognized. The aim of this study was to review the literature on the main changes resulting from pulmonary involvement in systemic sclerosis and the corresponding radiological findings, considering the current classification of interstitial diseases. We searched the Medline (PubMed), Lilacs, and SciELO databases in order to select articles related to pulmonary changes in systemic sclerosis and published in English between 2000 and 2015. The pulmonary changes seen on computed tomography in systemic sclerosis are varied and are divided into three main categories: interstitial, alveolar, and vascular. Interstitial changes constitute the most common type of pulmonary involvement in systemic sclerosis. However, alveolar and vascular manifestations must also be recognized and considered in the presence of atypical clinical presentations and inadequate treatment responses. (author)

  4. Tomography patterns of lung disease in systemic sclerosis

    International Nuclear Information System (INIS)

    Bastos, Andrea de Lima; Correa, Ricardo de Amorim; Ferreira, Gilda Aparecida

    2016-01-01

    Currently, lung impairment is the leading factor responsible for the morbidity and mortality associated with systemic sclerosis. Therefore, the recognition of the various tomography patterns becomes decisive in the clinical management of these patients. In high-resolution computed tomography studies, the most common pattern is that of nonspecific interstitial pneumonia. However, there are other forms of lung involvement that must also be recognized. The aim of this study was to review the literature on the main changes resulting from pulmonary involvement in systemic sclerosis and the corresponding radiological findings, considering the current classification of interstitial diseases. We searched the Medline (PubMed), Lilacs, and SciELO databases in order to select articles related to pulmonary changes in systemic sclerosis and published in English between 2000 and 2015. The pulmonary changes seen on computed tomography in systemic sclerosis are varied and are divided into three main categories: interstitial, alveolar, and vascular. Interstitial changes constitute the most common type of pulmonary involvement in systemic sclerosis. However, alveolar and vascular manifestations must also be recognized and considered in the presence of atypical clinical presentations and inadequate treatment responses. (author)

  5. Tomography patterns of lung disease in systemic sclerosis

    Directory of Open Access Journals (Sweden)

    Andréa de Lima Bastos

    Full Text Available Abstract Currently, lung impairment is the leading factor responsible for the morbidity and mortality associated with systemic sclerosis. Therefore, the recognition of the various tomography patterns becomes decisive in the clinical management of these patients. In high-resolution computed tomography studies, the most common pattern is that of nonspecific interstitial pneumonia. However, there are other forms of lung involvement that must also be recognized. The aim of this study was to review the literature on the main changes resulting from pulmonary involvement in systemic sclerosis and the corresponding radiological findings, considering the current classification of interstitial diseases. We searched the Medline (PubMed, Lilacs, and SciELO databases in order to select articles related to pulmonary changes in systemic sclerosis and published in English between 2000 and 2015. The pulmonary changes seen on computed tomography in systemic sclerosis are varied and are divided into three main categories: interstitial, alveolar, and vascular. Interstitial changes constitute the most common type of pulmonary involvement in systemic sclerosis. However, alveolar and vascular manifestations must also be recognized and considered in the presence of atypical clinical presentations and inadequate treatment responses.

  6. An embedded face-classification system for infrared images on an FPGA

    Science.gov (United States)

    Soto, Javier E.; Figueroa, Miguel

    2014-10-01

    We present a face-classification architecture for long-wave infrared (IR) images implemented on a Field Programmable Gate Array (FPGA). The circuit is fast, compact and low power, can recognize faces in real time and be embedded in a larger image-processing and computer vision system operating locally on an IR camera. The algorithm uses Local Binary Patterns (LBP) to perform feature extraction on each IR image. First, each pixel in the image is represented as an LBP pattern that encodes the similarity between the pixel and its neighbors. Uniform LBP codes are then used to reduce the number of patterns to 59 while preserving more than 90% of the information contained in the original LBP representation. Then, the image is divided into 64 non-overlapping regions, and each region is represented as a 59-bin histogram of patterns. Finally, the algorithm concatenates all 64 regions to create a 3,776-bin spatially enhanced histogram. We reduce the dimensionality of this histogram using Linear Discriminant Analysis (LDA), which improves clustering and enables us to store an entire database of 53 subjects on-chip. During classification, the circuit applies LBP and LDA to each incoming IR image in real time, and compares the resulting feature vector to each pattern stored in the local database using the Manhattan distance. We implemented the circuit on a Xilinx Artix-7 XC7A100T FPGA and tested it with the UCHThermalFace database, which consists of 28 81 x 150-pixel images of 53 subjects in indoor and outdoor conditions. The circuit achieves a 98.6% hit ratio, trained with 16 images and tested with 12 images of each subject in the database. Using a 100 MHz clock, the circuit classifies 8,230 images per second, and consumes only 309mW.

  7. [Analysis of dietary pattern and diabetes mellitus influencing factors identified by classification tree model in adults of Fujian].

    Science.gov (United States)

    Yu, F L; Ye, Y; Yan, Y S

    2017-05-10

    Objective: To find out the dietary patterns and explore the relationship between environmental factors (especially dietary patterns) and diabetes mellitus in the adults of Fujian. Methods: Multi-stage sampling method were used to survey residents aged ≥18 years by questionnaire, physical examination and laboratory detection in 10 disease surveillance points in Fujian. Factor analysis was used to identify the dietary patterns, while logistic regression model was applied to analyze relationship between dietary patterns and diabetes mellitus, and classification tree model was adopted to identify the influencing factors for diabetes mellitus. Results: There were four dietary patterns in the population, including meat, plant, high-quality protein, and fried food and beverages patterns. The result of logistic analysis showed that plant pattern, which has higher factor loading of fresh fruit-vegetables and cereal-tubers, was a protective factor for non-diabetes mellitus. The risk of diabetes mellitus in the population at T2 and T3 levels of factor score were 0.727 (95 %CI: 0.561-0.943) times and 0.736 (95 %CI : 0.573-0.944) times higher, respectively, than those whose factor score was in lowest quartile. Thirteen influencing factors and eleven group at high-risk for diabetes mellitus were identified by classification tree model. The influencing factors were dyslipidemia, age, family history of diabetes, hypertension, physical activity, career, sex, sedentary time, abdominal adiposity, BMI, marital status, sleep time and high-quality protein pattern. Conclusion: There is a close association between dietary patterns and diabetes mellitus. It is necessary to promote healthy and reasonable diet, strengthen the monitoring and control of blood lipids, blood pressure and body weight, and have good lifestyle for the prevention and control of diabetes mellitus.

  8. Pathohistological classification systems in gastric cancer: diagnostic relevance and prognostic value.

    Science.gov (United States)

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

    2014-05-21

    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.

  9. Analysis and Classification of Stride Patterns Associated with Children Development Using Gait Signal Dynamics Parameters and Ensemble Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Meihong Wu

    2016-01-01

    Full Text Available Measuring stride variability and dynamics in children is useful for the quantitative study of gait maturation and neuromotor development in childhood and adolescence. In this paper, we computed the sample entropy (SampEn and average stride interval (ASI parameters to quantify the stride series of 50 gender-matched children participants in three age groups. We also normalized the SampEn and ASI values by leg length and body mass for each participant, respectively. Results show that the original and normalized SampEn values consistently decrease over the significance level of the Mann-Whitney U test (p<0.01 in children of 3–14 years old, which indicates the stride irregularity has been significantly ameliorated with the body growth. The original and normalized ASI values are also significantly changing when comparing between any two groups of young (aged 3–5 years, middle (aged 6–8 years, and elder (aged 10–14 years children. Such results suggest that healthy children may better modulate their gait cadence rhythm with the development of their musculoskeletal and neurological systems. In addition, the AdaBoost.M2 and Bagging algorithms were used to effectively distinguish the children’s gait patterns. These ensemble learning algorithms both provided excellent gait classification results in terms of overall accuracy (≥90%, recall (≥0.8, and precision (≥0.8077.

  10. The First AO Classification System for Fractures of the Craniomaxillofacial Skeleton: Rationale, Methodological Background, Developmental Process, and Objectives.

    Science.gov (United States)

    Audigé, Laurent; Cornelius, Carl-Peter; Di Ieva, Antonio; Prein, Joachim

    2014-12-01

    Validated trauma classification systems are the sole means to provide the basis for reliable documentation and evaluation of patient care, which will open the gateway to evidence-based procedures and healthcare in the coming years. With the support of AO Investigation and Documentation, a classification group was established to develop and evaluate a comprehensive classification system for craniomaxillofacial (CMF) fractures. Blueprints for fracture classification in the major constituents of the human skull were drafted and then evaluated by a multispecialty group of experienced CMF surgeons and a radiologist in a structured process during iterative agreement sessions. At each session, surgeons independently classified the radiological imaging of up to 150 consecutive cases with CMF fractures. During subsequent review meetings, all discrepancies in the classification outcome were critically appraised for clarification and improvement until consensus was reached. The resulting CMF classification system is structured in a hierarchical fashion with three levels of increasing complexity. The most elementary level 1 simply distinguishes four fracture locations within the skull: mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). Levels 2 and 3 focus on further defining the fracture locations and for fracture morphology, achieving an almost individual mapping of the fracture pattern. This introductory article describes the rationale for the comprehensive AO CMF classification system, discusses the methodological framework, and provides insight into the experiences and interactions during the evaluation process within the core groups. The details of this system in terms of anatomy and levels are presented in a series of focused tutorials illustrated with case examples in this special issue of the Journal.

  11. Application of the Hess-Brezowsky classification to the identification of weather patterns causing heavy winter rainfall in Brittany (France

    Directory of Open Access Journals (Sweden)

    O. Planchon

    2009-07-01

    Full Text Available An accurate knowledge of the weather patterns causing winter rainfall over the Scorff watershed in western Brittany (W. France was developed prior to studies of the impact of the climate factor on land use management, and of the hydrological reponses to rain-producing weather patterns. These two studies are carried out in the context of the climate change. The identification of rainy air-circulation types was realized using the objective computational version of the 29-type Hess and Brezowsky Grosswetterlagen system of classifying European synoptic regimes, for the cold season (November-March of the 1958–2005 period at the reference weather station of Lorient, and 13 other stations located in western and southern Brittany, including a more detailed study for the wet 2000–2001 cold season for three reference stations of the Scorff watershed (Lorient, Plouay and Plouray. The precipitation proportion (including the days with rainfall ≥20 mm was calculated by major air-circulation type (GWT: see Appendix A and by individual air-circulation subtype (GWL: see Appendix A for the studied time-period. The most frequently occurrence of rainy days associated with westerly and southerly GWL confirmed well-known observations in western Europe and so justify the use of the Hess-Brezowsky classification in other areas outside Central Europe. The southern or south-western exposure of the watershed with a hilly inland area enhanced the heavy rainfall generated by the SW and S circulation types, and increased the difference between the rainfall amounts of coastal and inland stations during the wettest days.

  12. Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

    Directory of Open Access Journals (Sweden)

    Carlos T. Calafate

    2015-01-01

    Full Text Available Intelligent Transportation System (ITS technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

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

    Directory of Open Access Journals (Sweden)

    Kathie H Wang

    2014-05-01

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

  14. From fault classification to fault tolerance for multi-agent systems

    CERN Document Server

    Potiron, Katia; Taillibert, Patrick

    2013-01-01

    Faults are a concern for Multi-Agent Systems (MAS) designers, especially if the MAS are built for industrial or military use because there must be some guarantee of dependability. Some fault classification exists for classical systems, and is used to define faults. When dependability is at stake, such fault classification may be used from the beginning of the system's conception to define fault classes and specify which types of faults are expected. Thus, one may want to use fault classification for MAS; however, From Fault Classification to Fault Tolerance for Multi-Agent Systems argues that

  15. Classification Systems, their Digitization and Consequences for Data-Driven Decision Making

    DEFF Research Database (Denmark)

    Stein, Mari-Klara; Newell, Sue; Galliers, Robert D.

    2013-01-01

    Classification systems are foundational in many standardized software tools. This digitization of classification systems gives them a new ‘materiality’ that, jointly with the social practices of information producers/consumers, has significant consequences on the representational quality of such ...... and the foundational role of representational quality in understanding the success and consequences of data-driven decision-making.......-narration and meta-narration), and three different information production/consumption situations. We contribute to the relational theorization of representational quality and extend classification systems research by drawing explicit attention to the importance of ‘materialization’ of classification systems...

  16. Classification systems in nursing : Formalizing nursing knowledge and implications for nursing information systems

    NARCIS (Netherlands)

    Goossen, WTF; Epping, PJMM; Abraham, IL

    The development of nursing information systems (NIS) is often hampered by the fact that nursing lacks a unified nursing terminology and classification system. Currently there exist various initiatives in this area. We address the question as to how current initiatives in the development of nursing

  17. Refining Time-Activity Classification of Human Subjects Using the Global Positioning System.

    Science.gov (United States)

    Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun

    2016-01-01

    Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well

  18. New classification system-based visual outcome in Eales′ disease

    Directory of Open Access Journals (Sweden)

    Saxena Sandeep

    2007-01-01

    Full Text Available Purpose: A retrospective tertiary care center-based study was undertaken to evaluate the visual outcome in Eales′ disease, based on a new classification system, for the first time. Materials and Methods: One hundred and fifty-nine consecutive cases of Eales′ disease were included. All the eyes were staged according to the new classification: Stage 1: periphlebitis of small (1a and large (1b caliber vessels with superficial retinal hemorrhages; Stage 2a: capillary non-perfusion, 2b: neovascularization elsewhere/of the disc; Stage 3a: fibrovascular proliferation, 3b: vitreous hemorrhage; Stage 4a: traction/combined rhegmatogenous retinal detachment and 4b: rubeosis iridis, neovascular glaucoma, complicated cataract and optic atrophy. Visual acuity was graded as: Grade I 20/20 or better; Grade II 20/30 to 20/40; Grade III 20/60 to 20/120 and Grade IV 20/200 or worse. All the cases were managed by medical therapy, photocoagulation and/or vitreoretinal surgery. Visual acuity was converted into decimal scale, denoting 20/20=1 and 20/800=0.01. Paired t-test / Wilcoxon signed-rank tests were used for statistical analysis. Results: Vitreous hemorrhage was the commonest presenting feature (49.32%. Cases with Stages 1 to 3 and 4a and 4b achieved final visual acuity ranging from 20/15 to 20/40; 20/80 to 20/400 and 20/200 to 20/400, respectively. Statistically significant improvement in visual acuities was observed in all the stages of the disease except Stages 1a and 4b. Conclusion: Significant improvement in visual acuities was observed in the majority of stages of Eales′ disease following treatment. This study adds further to the little available evidences of treatment effects in literature and may have effect on patient care and health policy in Eales′ disease.

  19. Classification of robotic battery service systems for unmanned aerial vehicles

    Directory of Open Access Journals (Sweden)

    Ngo Tien

    2018-01-01

    Full Text Available Existing examples of prototypes of ground-based robotic platforms used as a landing site for unmanned aerial vehicles are considered. In some cases, they are equipped with a maintenance mechanism for the power supply module. The main requirements for robotic multi-copter battery maintenance systems depending on operating conditions, required processing speed, operator experience and other parameters are analyzed. The key issues remain questions of the autonomous landing of the unmanned aerial vehicles on the platform and approach to servicing battery. The existing prototypes of service robotic platforms are differed in the complexity of internal mechanisms, speed of service, algorithms of joint work of the platform and unmanned aerial vehicles during the landing and maintenance of the battery. The classification of robotic systems for servicing the power supply of multi-copter batteries criteria is presented using the following: the type of basing, the method of navigation during landing, the shape of the landing pad, the method of restoring the power supply module. The proposed algorithmic model of the operation of battery power maintenance system of the multi-copter on ground-based robotic platform during solving the target agrarian problem is described. Wireless methods of battery recovery are most promising, so further development and prototyping of a wireless charging station for multi-copter batteries will be developed.

  20. System diagnostics using qualitative analysis and component functional classification

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.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. 5 figures

  1. Potential risk for healthy siblings to develop schizophrenia: evidence from pattern classification with whole-brain connectivity.

    Science.gov (United States)

    Liu, Meijie; Zeng, Ling-Li; Shen, Hui; Liu, Zhening; Hu, Dewen

    2012-03-28

    Recent resting-state functional connectivity MRI studies using group-level statistical analysis have demonstrated the inheritable characters of schizophrenia. The objective of the present study was to use pattern classification as a means to investigate schizophrenia inheritance based on the whole-brain resting-state functional connectivity at the individual subject level. One-against-one pattern classifications were made amongst three groups (i.e. patients diagnosed with schizophrenia, healthy siblings, and healthy controls after preprocessing), resulting in an 80.4% separation between patients with schizophrenia and healthy controls, a 77.6% separation between schizophrenia patients and their healthy siblings, and a 78.7% separation between healthy siblings and healthy controls, respectively. These results suggest that the healthy siblings of schizophrenia patients have an altered resting-state functional connectivity pattern compared with healthy controls. Thus, healthy siblings may have a potential higher risk for developing schizophrenia compared with the general population. Moreover, this pattern differed from that of schizophrenia patients and may contribute to the normal behavior exhibition of healthy siblings in daily life.

  2. Portable bacterial identification system based on elastic light scatter patterns

    Directory of Open Access Journals (Sweden)

    Bae Euiwon

    2012-08-01

    Full Text Available Abstract Background Conventional diagnosis and identification of bacteria requires shipment of samples to a laboratory for genetic and biochemical analysis. This process can take days and imposes significant delay to action in situations where timely intervention can save lives and reduce associated costs. To enable faster response to an outbreak, a low-cost, small-footprint, portable microbial-identification instrument using forward scatterometry has been developed. Results This device, weighing 9 lb and measuring 12 × 6 × 10.5 in., utilizes elastic light scatter (ELS patterns to accurately capture bacterial colony characteristics and delivers the classification results via wireless access. The overall system consists of two CCD cameras, one rotational and one translational stage, and a 635-nm laser diode. Various software algorithms such as Hough transform, 2-D geometric moments, and the traveling salesman problem (TSP have been implemented to provide colony count and circularity, centering process, and minimized travel time among colonies. Conclusions Experiments were conducted with four bacteria genera using pure and mixed plate and as proof of principle a field test was conducted in four different locations where the average classification rate ranged between 95 and 100%.

  3. Pattern classification of brain activation during emotional processing in subclinical depression: psychosis proneness as potential confounding factor

    Directory of Open Access Journals (Sweden)

    Gemma Modinos

    2013-02-01

    Full Text Available We used Support Vector Machine (SVM to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II. Two groups were subsequently formed: (i subclinical (mild mood disturbance (n = 17 and (ii no mood disturbance (n = 17. Participants also completed a self-report questionnaire on subclinical psychotic symptoms, the Community Assessment of Psychic Experiences Questionnaire (CAPE positive subscale. The functional magnetic resonance imaging (fMRI paradigm entailed passive viewing of negative emotional and neutral scenes. The pattern of brain activity during emotional processing allowed correct group classification with an overall accuracy of 77% (p = 0.002, within a network of regions including the amygdala, insula, anterior cingulate cortex and medial prefrontal cortex. However, further analysis suggested that the classification accuracy could also be explained by subclinical psychotic symptom scores (correlation with SVM weights r = 0.459, p = 0.006. Psychosis proneness may thus be a confounding factor for neuroimaging studies in subclinical depression.

  4. Pattern classification of brain activation during emotional processing in subclinical depression: psychosis proneness as potential confounding factor.

    Science.gov (United States)

    Modinos, Gemma; Mechelli, Andrea; Pettersson-Yeo, William; Allen, Paul; McGuire, Philip; Aleman, Andre

    2013-01-01

    We used Support Vector Machine (SVM) to perform multivariate pattern classification based on brain activation during emotional processing in healthy participants with subclinical depressive symptoms. Six-hundred undergraduate students completed the Beck Depression Inventory II (BDI-II). Two groups were subsequently formed: (i) subclinical (mild) mood disturbance (n = 17) and (ii) no mood disturbance (n = 17). Participants also completed a self-report questionnaire on subclinical psychotic symptoms, the Community Assessment of Psychic Experiences Questionnaire (CAPE) positive subscale. The functional magnetic resonance imaging (fMRI) paradigm entailed passive viewing of negative emotional and neutral scenes. The pattern of brain activity during emotional processing allowed correct group classification with an overall accuracy of 77% (p = 0.002), within a network of regions including the amygdala, insula, anterior cingulate cortex and medial prefrontal cortex. However, further analysis suggested that the classification accuracy could also be explained by subclinical psychotic symptom scores (correlation with SVM weights r = 0.459, p = 0.006). Psychosis proneness may thus be a confounding factor for neuroimaging studies in subclinical depression.

  5. Dietary pattern classifications with nutrient intake and health-risk factors in Korean men.

    Science.gov (United States)

    Lee, Ji Eun; Kim, Jung-Hyun; Son, Say Jin; Ahn, Younjhin; Lee, Juyoung; Park, Chan; Lee, Lilha; Erickson, Kent L; Jung, In-Kyung

    2011-01-01

    This study was performed to identify dietary patterns in Korean men and to determine the associations among dietary patterns, nutrient intake, and health-risk factors. Using baseline data from the Korean Health and Genome Study, dietary patterns were identified using factor analysis of data from a validated food-frequency questionnaire, and associations between these dietary patterns and health-risk factors were analyzed. Three dietary patterns were identified: 1) the "animal-food" pattern (greater intake of meats, fish, and dairy products), 2) the "rice-vegetable" pattern (greater intake of rice, tofu, kimchi, soybean paste, vegetables, and seaweed), and 3) the "noodle-bread" pattern (greater intake of instant noodles, Chinese noodles, and bread). The animal-food pattern (preferred by younger people with higher income and education levels) had a positive correlation with obesity and hypercholesterolemia, whereas the rice-vegetable pattern (preferred by older people with lower income and educational levels) was positively associated with hypertension. The noodle-bread pattern (also preferred by younger people with higher income and education levels) had a positive association with abdominal obesity and hypercholesterolemia. This study identifies three unique dietary patterns in Korean men, which are independently associated with certain health-risk factors. The rice-vegetable dietary pattern, modified for a low sodium intake, might be a healthy dietary pattern for Korean men. Copyright © 2011 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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.

  7. An overview of some historical knowledge organisation systems and classifications with a special emphasy on monastery libraries’ classification

    Directory of Open Access Journals (Sweden)

    Sonja Svoljšak

    2005-01-01

    Full Text Available The article gives an overview of some most prominent historical turning – points in the field of knowledge organization an2d western European sistematization of science, based on Greek and christian philosophy. Some examples of earlier attempts to unify the systems of knowledge organization and science systematization are presented. Some specific systems of the most prominent European christian religious orders’ library contents arrangement and classification are described in this context.

  8. Perforator chimerism for the reconstruction of complex defects: A new chimeric free flap classification system.

    Science.gov (United States)

    Kim, Jeong Tae; Kim, Youn Hwan; Ghanem, Ali M

    2015-11-01

    Complex defects present structural and functional challenges to reconstructive surgeons. When compared to multiple free flaps or staged reconstruction, the use of chimeric flaps to reconstruct such defects have many advantages such as reduced number of operative procedures and donor site morbidity as well as preservation of recipient vessels. With increased popularity of perforator flaps, chimeric flaps' harvest and design has benefited from 'perforator concept' towards more versatile and better reconstruction solutions. This article discusses perforator based chimeric flaps and presents a practice based classification system that incorporates the perforator flap concept into "Perforator Chimerism". The authors analyzed a variety of chimeric patterns used in 31 consecutive cases to present illustrative case series and their new classification system. Accordingly, chimeric flaps are classified into four types. Type I: Classical Chimerism, Type II: Anastomotic Chimerism, Type III: Perforator Chimerism and Type IV Mixed Chimerism. Types I on specific source vessel anatomy whilst Type II requires microvascular anastomosis to create the chimeric reconstructive solution. Type III chimeric flaps utilizes the perforator concept to raise two components of tissues without microvascular anastomosis between them. Type IV chimeric flaps are mixed type flaps comprising any combination of Types I to III. Incorporation of the perforator concept in planning and designing chimeric flaps has allowed safe, effective and aesthetically superior reconstruction of complex defects. The new classification system aids reconstructive surgeons and trainees to understand chimeric flaps design, facilitating effective incorporation of this important reconstructive technique into the armamentarium of the reconstruction toolbox. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  9. Using a Classification of Occupations to Describe Age, Sex, and Time Differences in Employment Patterns. Report No. 223.

    Science.gov (United States)

    Gottfredson, Gary D.; Daiger, Denise C.

    Employment data from the 1960 and 1970 censuses were organized using the occupational classification system of John Holland to examine age, sex, and level differences in employment and to detect changes over the 10-year period. Data were organized by both kind and level of work in an attempt to answer the following questions: What are the relative…

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

    Science.gov (United States)

    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.

  11. Standard practice for verification and classification of extensometer systems

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2010-01-01

    1.1 This practice covers procedures for the verification and classification of extensometer systems, but it is not intended to be a complete purchase specification. The practice is applicable only to instruments that indicate or record values that are proportional to changes in length corresponding to either tensile or compressive strain. Extensometer systems are classified on the basis of the magnitude of their errors. 1.2 Because strain is a dimensionless quantity, this document can be used for extensometers based on either SI or US customary units of displacement. Note 1—Bonded resistance strain gauges directly bonded to a specimen cannot be calibrated or verified with the apparatus described in this practice for the verification of extensometers having definite gauge points. (See procedures as described in Test Methods E251.) 1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish app...

  12. USDA soil classification system dictates site surface management

    International Nuclear Information System (INIS)

    Bowmer, W.J.

    1985-01-01

    Success or failure of site surface management practices greatly affects long-term site stability. The US Department of Agriculture (USDA) soil classification system best documents those parameters which control the success of installed practices for managing both erosion and surface drainage. The USDA system concentrates on soil characteristics in the upper three meters of the surface that support the associated flora both physically and physiologically. The USDA soil survey first identifies soil series based on detailed characteristics that are related to production potential. Using the production potential, land use capability classes are developed. Capability classes reveal the highest and best agronomic use for the site. Lower number classes are considered arable while higher number classes are best suited for grazing agriculture. Application of ecological principles based on the USDA soil survey reveals the current state of the site relative to its ecological potential. To assure success, site management practices must be chosen that are compatible with both production capability and current state of the site

  13. DNA methylation-based classification of central nervous system tumours.

    Science.gov (United States)

    Capper, David; Jones, David T W; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E; Kratz, Annekathrin; Wefers, Annika K; Huang, Kristin; Pajtler, Kristian W; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W; Lindenberg, Kerstin; Harter, Patrick N; Braczynski, Anne K; Plate, Karl H; Dohmen, Hildegard; Garvalov, Boyan K; Coras, Roland; Hölsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Jürgen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brück, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Hänggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R; Kohlhof, Patricia; Kristensen, Bjarne W; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Mühleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G; Driever, Pablo Hernáiz; Kramm, Christof M; Müller, Hermann L; Rutkowski, Stefan; von Hoff, Katja; Frühwald, Michael C; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Blümcke, Ingmar; Bendszus, Martin; Debus, Jürgen; Huang, Annie; Jabado, Nada; Northcott, Paul A; Paulus, Werner; Gajjar, Amar; Robinson, Giles W; Taylor, Michael D; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schüller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M

    2018-03-22

    Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

  14. Drug-induced sedation endoscopy (DISE) classification systems: a systematic review and meta-analysis.

    Science.gov (United States)

    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.

  15. Fingerprint pattern classification approach based on the coordinate geometry of singularities

    CSIR Research Space (South Africa)

    Msiza, IS

    2009-10-01

    Full Text Available of fingerprint matching, it serves to reduce the duration of the query. The fingerprint classes discussed in this document are the Central Twins (CT), Tented Arch (TA), Left Loop (LL), Right Loop (RL) and the Plain Arch (PA). The classification rules employed...

  16. On the external relations of Purepecha : an investigation into classification, contact and patterns of word formation

    NARCIS (Netherlands)

    Bellamy, K.R.

    2018-01-01

    This thesis considers Purepecha from the perspectives of genealogy and contact, as well as offering insight into word formation processes. The genealogy study re-visits the most prominent classification proposals for Purepecha, concluding on the basis of a quantitative lexical comparison and

  17. Model sparsity and brain pattern interpretation of classification models in neuroimaging

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Madsen, Kristoffer Hougaard; Churchill, Nathan W

    2012-01-01

    Interest is increasing in applying discriminative multivariate analysis techniques to the analysis of functional neuroimaging data. Model interpretation is of great importance in the neuroimaging context, and is conventionally based on a ‘brain map’ derived from the classification model. In this ...

  18. Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning

    Directory of Open Access Journals (Sweden)

    Victoria Plaza-Leiva

    2017-03-01

    Full Text Available Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM, Gaussian processes (GP, and Gaussian mixture models (GMM. A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl. Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

  19. Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning.

    Science.gov (United States)

    Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

    2017-03-15

    Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

  20. Perceptual and Acoustic Reliability Estimates for the Speech Disorders Classification System (SDCS)

    Science.gov (United States)

    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

    A companion paper describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). The SDCS uses perceptual and acoustic data reduction methods to obtain information on a speaker's speech, prosody, and voice. The present paper provides reliability estimates for…

  1. 42 CFR 419.31 - Ambulatory payment classification (APC) system and payment weights.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 3 2010-10-01 2010-10-01 false Ambulatory payment classification (APC) system and... Outpatient Services § 419.31 Ambulatory payment classification (APC) system and payment weights. (a) APC... of resource use into APC groups. Except as specified in paragraph (a)(2) of this section, items and...

  2. Volunteer-Based System for classification of traffic in computer networks

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Balachandran, Kartheepan; Riaz, M. Tahir

    2011-01-01

    To overcome the drawbacks of existing methods for traffic classification (by ports, Deep Packet Inspection, statistical classification) a new system was developed, in which the data are collected from client machines. This paper presents design of the system, implementation, initial runs and obta...

  3. Application of the Safety Classification of Structures, Systems and Components in Nuclear Power Plants

    International Nuclear Information System (INIS)

    2016-04-01

    This publication describes how to complete tasks associated with every step of the classification methodology set out in IAEA Safety Standards Series No. SSG-30, Safety Classification of Structures, Systems and Components in Nuclear Power Plants. In particular, how to capture all the structures, systems and components (SSCs) of a nuclear power plant to be safety classified. Emphasis is placed on the SSCs that are necessary to limit radiological releases to the public and occupational doses to workers in operational conditions This publication provides information for organizations establishing a comprehensive safety classification of SSCs compliant with IAEA recommendations, and to support regulators in reviewing safety classification submitted by licensees

  4. Bifurcations and Patterns in Nonlinear Dissipative Systems

    Energy Technology Data Exchange (ETDEWEB)

    Guenter Ahlers

    2005-05-27

    This project consists of experimental investigations of heat transport, pattern formation, and bifurcation phenomena in non-linear non-equilibrium fluid-mechanical systems. These issues are studies in Rayleigh-B\\'enard convection, using both pure and multicomponent fluids. They are of fundamental scientific interest, but also play an important role in engineering, materials science, ecology, meteorology, geophysics, and astrophysics. For instance, various forms of convection are important in such diverse phenomena as crystal growth from a melt with or without impurities, energy production in solar ponds, flow in the earth's mantle and outer core, geo-thermal stratifications, and various oceanographic and atmospheric phenomena. Our work utilizes computer-enhanced shadowgraph imaging of flow patterns, sophisticated digital image analysis, and high-resolution heat transport measurements.

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

    Science.gov (United States)

    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.

  6. Intelligence system based classification approach for medical disease diagnosis

    Science.gov (United States)

    Sagir, Abdu Masanawa; Sathasivam, Saratha

    2017-08-01

    The prediction of breast cancer in women who have no signs or symptoms of the disease as well as survivability after undergone certain surgery has been a challenging problem for medical researchers. The decision about presence or absence of diseases depends on the physician's intuition, experience and skill for comparing current indicators with previous one than on knowledge rich data hidden in a database. This measure is a very crucial and challenging task. The goal is to predict patient condition by using an adaptive neuro fuzzy inference system (ANFIS) pre-processed by grid partitioning. To achieve an accurate diagnosis at this complex stage of symptom analysis, the physician may need efficient diagnosis system. A framework describes methodology for designing and evaluation of classification performances of two discrete ANFIS systems of hybrid learning algorithms least square estimates with Modified Levenberg-Marquardt and Gradient descent algorithms that can be used by physicians to accelerate diagnosis process. The proposed method's performance was evaluated based on training and test datasets with mammographic mass and Haberman's survival Datasets obtained from benchmarked datasets of University of California at Irvine's (UCI) machine learning repository. The robustness of the performance measuring total accuracy, sensitivity and specificity is examined. In comparison, the proposed method achieves superior performance when compared to conventional ANFIS based gradient descent algorithm and some related existing methods. The software used for the implementation is MATLAB R2014a (version 8.3) and executed in PC Intel Pentium IV E7400 processor with 2.80 GHz speed and 2.0 GB of RAM.

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

    Directory of Open Access Journals (Sweden)

    Hosseinpour-Feizi H

    2011-12-01

    Full Text Available Hojjat Hosseinpour-Feizi, Jafar Soleimanpour, Jafar Ganjpour Sales, Ali ArzroumchilarDepartment of Orthopedics, Shohada Hospital, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, IranPurpose: The aim of this study was to investigate the interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis, and to compare the results of surgery performed based on classification of the scoliosis according to each of these classification systems.Methods: The study was conducted in Shohada Hospital in Tabriz, Iran, between 2009 and 2010. First, a reliability assessment was undertaken to assess interobserver agreement of the Lenke and King classifications for adolescent idiopathic scoliosis. Second, postoperative efficacy and safety of surgery performed based on the Lenke and King classifications were compared. Kappa coefficients of agreement were calculated to assess the agreement. Outcomes were compared using bivariate tests and repeated measures analysis of variance.Results: A low to moderate interobserver agreement was observed for the King classification; the Lenke classification yielded mostly high agreement coefficients. The outcome of surgery was not found to be substantially different between the two systems.Conclusion: Based on the results, the Lenke classification method seems advantageous. This takes into consideration the Lenke classification’s priority in providing details of curvatures in different anatomical surfaces to explain precise intensity of scoliosis, that it has higher interobserver agreement scores, and also that it leads to noninferior postoperative results compared with the King classification method.Keywords: test reliability, scoliosis classification, postoperative efficacy, adolescents

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

    Science.gov (United States)

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

    2011-01-01

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

  9. Multiphase patterns in periodically forced oscillatory systems

    International Nuclear Information System (INIS)

    Elphick, C.; Hagberg, A.; Meron, E.

    1999-01-01

    Periodic forcing of an oscillatory system produces frequency locking bands within which the system frequency is rationally related to the forcing frequency. We study extended oscillatory systems that respond to uniform periodic forcing at one quarter of the forcing frequency (the 4:1 resonance). These systems possess four coexisting stable states, corresponding to uniform oscillations with successive phase shifts of π/2. Using an amplitude equation approach near a Hopf bifurcation to uniform oscillations, we study front solutions connecting different phase states. These solutions divide into two groups: π fronts separating states with a phase shift of π and π/2 fronts separating states with a phase shift of π/2. We find a type of front instability where a stationary π front 'decomposes' into a pair of traveling π/2 fronts as the forcing strength is decreased. The instability is degenerate for an amplitude equation with cubic nonlinearities. At the instability point a continuous family of pair solutions exists, consisting of π/2 fronts separated by distances ranging from zero to infinity. Quintic nonlinearities lift the degeneracy at the instability point but do not change the basic nature of the instability. We conjecture the existence of similar instabilities in higher 2n:1 resonances (n=3,4,hor-ellipsis) where stationary π fronts decompose into n traveling π/n fronts. The instabilities designate transitions from stationary two-phase patterns to traveling 2n-phase patterns. As an example, we demonstrate with a numerical solution the collapse of a four-phase spiral wave into a stationary two-phase pattern as the forcing strength within the 4:1 resonance is increased. copyright 1999 The American Physical Society

  10. Biopharmaceutics classification system: importance and inclusion in biowaiver guidance

    Directory of Open Access Journals (Sweden)

    Lorena Barbosa Arrunátegui

    2015-03-01

    Full Text Available Pharmacological therapy is essential in many diseases treatment and it is important that the medicine policy is intended to offering safe and effective treatment with affordable price to the population. One way to achieve this is through biowaiver, defined as the replacement of in vivo bioequivalence studies by in vitro studies. For biowaiver of new immediate release solid oral dosage forms, data such as intestinal permeability and solubility of the drug are required, as well as the product dissolution. The Biopharmaceutics Classification System (BCS is a scientific scheme that divides drugs according to their solubility and permeability and has been used by various guides as a criterion for biowaiver. This paper evaluates biowaiver application, addressing the general concepts and parameters used by BCS, making a historical account of its use, the requirements pertaining to the current legislation, the benefits and risks associated with this decision. The results revealed that the use of BCS as a biowaiver criterion greatly expands the therapeutics options, contributing to greater therapy access of the general population with drug efficacy and safety guaranteed associated to low cost.

  11. Classification System for Individualized Treatment of Adult Buried Penis Syndrome.

    Science.gov (United States)

    Tausch, Timothy J; Tachibana, Isamu; Siegel, Jordan A; Hoxworth, Ronald; Scott, Jeremy M; Morey, Allen F

    2016-09-01

    The authors present their experience with reconstructive strategies for men with various manifestations of adult buried penis syndrome, and propose a comprehensive anatomical classification system and treatment algorithm based on pathologic changes in the penile skin and involvement of neighboring abdominal and/or scrotal components. The authors reviewed all patients who underwent reconstruction of adult buried penis syndrome at their referral center between 2007 and 2015. Patients were stratified by location and severity of involved anatomical components. Procedures performed, demographics, comorbidities, and clinical outcomes were reviewed. Fifty-six patients underwent reconstruction of buried penis at the authors' center from 2007 to 2015. All procedures began with a ventral penile release. If the uncovered penile skin was determined to be viable, a phalloplasty was performed by anchoring penoscrotal skin to the proximal shaft, and the ventral shaft skin defect was closed with scrotal flaps. In more complex patients with circumferential nonviable penile skin, the penile skin was completely excised and replaced with a split-thickness skin graft. Complex patients with severe abdominal lipodystrophy required adjacent tissue transfer. For cases of genital lymphedema, the procedure involved complete excision of the lymphedematous tissue, and primary closure with or without a split-thickness skin graft, also often involving the scrotum. The authors' overall success rate was 88 percent (49 of 56), defined as resolution of symptoms without the need for additional procedures. Successful correction of adult buried penis often necessitates an interdisciplinary, multimodal approach. Therapeutic, IV.

  12. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries.

    Science.gov (United States)

    Wangensteen, Arnlaug; Tol, Johannes L; Roemer, Frank W; Bahr, Roald; Dijkstra, H Paul; Crema, Michel D; Farooq, Abdulaziz; Guermazi, Ali

    2017-04-01

    To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Male athletes (n=40) with clinical diagnosis of acute hamstring injury and MRI ≤5days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. We observed 'substantial' to 'almost perfect' intra- (κ range 0.65-1.00) and interrater reliability (κ range 0.77-1.00) with percentage agreement 83-100% and 88-100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range -0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated 'substantial' to 'almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Guidance on classification for reproductive toxicity under the globally harmonized system of classification and labelling of chemicals (GHS).

    Science.gov (United States)

    Moore, Nigel P; Boogaard, Peter J; Bremer, Susanne; Buesen, Roland; Edwards, James; Fraysse, Benoit; Hallmark, Nina; Hemming, Helena; Langrand-Lerche, Carole; McKee, Richard H; Meisters, Marie-Louise; Parsons, Paul; Politano, Valerie; Reader, Stuart; Ridgway, Peter; Hennes, Christa

    2013-11-01

    The Globally Harmonised System of Classification (GHS) is a framework within which the intrinsic hazards of substances may be determined and communicated. It is not a legislative instrument per se, but is enacted into national legislation with the appropriate legislative instruments. GHS covers many aspects of effects upon health and the environment, including adverse effects upon sexual function and fertility or on development. Classification for these effects is based upon observations in humans or from properly designed experiments in animals, although only the latter is covered herein. The decision to classify a substance based upon experimental data, and the category of classification ascribed, is determined by the level of evidence that is available for an adverse effect on sexual function and fertility or on development that does not arise as a secondary non-specific consequence of other toxic effect. This document offers guidance on the determination of level of concern as a measure of adversity, and the level of evidence to ascribe classification based on data from tests in laboratory animals.

  14. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  15. Toward a common classification approach for biorefinery systems

    NARCIS (Netherlands)

    Cherubini, F.; Jungmeier, G.; Wellisch, M.; Wilke, T.; Skiadas, I.; Ree, van R.; Jong, de E.

    2009-01-01

    This paper deals with a biorefinery classification approach developed within International Energy Agency (IEA) Bioenergy Task 42. Since production of transportation biofuels is seen as the driving force for future biorefinery developments, a selection of the most interesting transportation biofuels

  16. Mining vehicle classifications from the Columbus Metropolitan Freeway Management System.

    Science.gov (United States)

    2015-01-01

    Vehicle classification data are used in many transportation applications, including: pavement design, : environmental impact studies, traffic control, and traffic safety. Ohio has over 200 permanent count stations, : supplemented by many more short-t...

  17. Lie Group Classification of a Generalized Lane-Emden Type System in Two Dimensions

    Directory of Open Access Journals (Sweden)

    Motlatsi Molati

    2012-01-01

    Full Text Available The aim of this work is to perform a complete Lie symmetry classification of a generalized Lane-Emden type system in two dimensions which models many physical phenomena in biological and physical sciences. The classical approach of group classification is employed for classification. We show that several cases arise in classifying the arbitrary parameters, the forms of which include amongst others the power law nonlinearity, and exponential and quadratic forms.

  18. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries

    International Nuclear Information System (INIS)

    Wangensteen, Arnlaug; Tol, Johannes L.; Roemer, Frank W.; Bahr, Roald; Dijkstra, H. Paul; Crema, Michel D.; Farooq, Abdulaziz; Guermazi, Ali

    2017-01-01

    Highlights: • Three different MRI grading and classification systems for acute hamstring injuries are overall reliable. • Reliability for the subcategories within these MRI grading and classification systems remains, however, unclear. - Abstract: Objective: To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Methods: Male athletes (n = 40) with clinical diagnosis of acute hamstring injury and MRI ≤5 days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. Results: We observed ‘substantial’ to ‘almost perfect’ intra- (κ range 0.65–1.00) and interrater reliability (κ range 0.77–1.00) with percentage agreement 83–100% and 88–100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range −0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. Conclusions: The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated ‘substantial' to ‘almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear.

  19. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries

    Energy Technology Data Exchange (ETDEWEB)

    Wangensteen, Arnlaug, E-mail: arnlaug.wangensteen@nih.no [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo (Norway); Tol, Johannes L., E-mail: johannes.tol@aspetar.com [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Amsterdam Center for Evidence Sports Medicine, Academic Medical Center (Netherlands); The Sports Physician Group, OLVG, Amsterdam (Netherlands); Roemer, Frank W. [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States); Department of Radiology, University of Erlangen-Nuremberg, Erlangen (Germany); Bahr, Roald [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo (Norway); Dijkstra, H. Paul [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Crema, Michel D. [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States); Department of Radiology, Saint-Antoine Hospital, University Paris VI, Paris (France); Farooq, Abdulaziz [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Guermazi, Ali [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States)

    2017-04-15

    Highlights: • Three different MRI grading and classification systems for acute hamstring injuries are overall reliable. • Reliability for the subcategories within these MRI grading and classification systems remains, however, unclear. - Abstract: Objective: To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Methods: Male athletes (n = 40) with clinical diagnosis of acute hamstring injury and MRI ≤5 days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. Results: We observed ‘substantial’ to ‘almost perfect’ intra- (κ range 0.65–1.00) and interrater reliability (κ range 0.77–1.00) with percentage agreement 83–100% and 88–100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range −0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. Conclusions: The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated ‘substantial' to ‘almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear.

  20. Pattern formation and chaos in synergetic systems

    Energy Technology Data Exchange (ETDEWEB)

    Haken, H

    1985-01-01

    A general approach to the reduction of the equations of systems composed of many subsystems of equations for, in general, few order parameters at instability points is sketched. As special case generalized Ginzburg-Landau equations are obtained. Recent results based on these equations, showing pattern formation in the convection instability and flames, are presented. Bifurcations from tori to other tori are treated, and some general conclusions are drawn. Analogies between fluid dynamics and lasers which led to the prediction of laser light chaos by Haken (1975) are pointed out. Finally the suspension of a class of discrete one-dimensional maps is discussed and explicitly presented for a typical case. 21 references.

  1. Rhythmic EEG patterns in extremely preterm infants: Classification and association with brain injury and outcome.

    Science.gov (United States)

    Weeke, Lauren C; van Ooijen, Inge M; Groenendaal, Floris; van Huffelen, Alexander C; van Haastert, Ingrid C; van Stam, Carolien; Benders, Manon J; Toet, Mona C; Hellström-Westas, Lena; de Vries, Linda S

    2017-12-01

    Classify rhythmic EEG patterns in extremely preterm infants and relate these to brain injury and outcome. Retrospective analysis of 77 infants born Rhythmic patterns were observed in 62.3% (ictal 1.3%, PEDs 44%, other waveforms 86.3%) with multiple patterns in 36.4%. Ictal discharges were only observed in one and excluded from further analyses. The EEG location of the other waveforms (pRhythmic waveforms related to head position are likely artefacts. Rhythmic EEG patterns may have a different significance in extremely preterm infants. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  2. Study on a pattern classification method of soil quality based on simplified learning sample dataset

    Science.gov (United States)

    Zhang, Jiahua; Liu, S.; Hu, Y.; Tian, Y.

    2011-01-01

    Based on the massive soil information in current soil quality grade evaluation, this paper constructed an intelligent classification approach of soil quality grade depending on classical sampling techniques and disordered multiclassification Logistic regression model. As a case study to determine the learning sample capacity under certain confidence level and estimation accuracy, and use c-means algorithm to automatically extract the simplified learning sample dataset from the cultivated soil quality grade evaluation database for the study area, Long chuan county in Guangdong province, a disordered Logistic classifier model was then built and the calculation analysis steps of soil quality grade intelligent classification were given. The result indicated that the soil quality grade can be effectively learned and predicted by the extracted simplified dataset through this method, which changed the traditional method for soil quality grade evaluation. ?? 2011 IEEE.

  3. Classifications of Winter Euro-Atlantic Circulation Patterns: An Intercomparison of Five Atmospheric Reanalyses

    Czech Academy of Sciences Publication Activity Database

    Stryhal, J.; Huth, Radan

    2017-01-01

    Roč. 30, č. 19 (2017), s. 7847-7861 ISSN 0894-8755 Institutional support: RVO:68378289 Keywords : atmospheric circulation * classification * climate models * Europe * model evaluation/performance * reanalysis data Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 4.161, year: 2016 http:// journals .ametsoc.org/doi/abs/10.1175/JCLI-D-17-0059.1

  4. Synoptic-climatological evaluation of the classifications of atmospheric circulation patterns over Europe

    Czech Academy of Sciences Publication Activity Database

    Huth, Radan; Beck, Ch.; Kučerová, Monika

    2016-01-01

    Roč. 36, č. 7 (2016), s. 2710-2726 ISSN 0899-8418 R&D Projects: GA ČR(CZ) GPP209/12/P811; GA MŠk OC 115 Institutional support: RVO:68378289 Keywords : circulation types * classification * synoptic climatology * COST733 Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.760, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/joc.4546/full

  5. Gender classification from face images by using local binary pattern and gray-level co-occurrence matrix

    Science.gov (United States)

    Uzbaş, Betül; Arslan, Ahmet

    2018-04-01

    Gender is an important step for human computer interactive processes and identification. Human face image is one of the important sources to determine gender. In the present study, gender classification is performed automatically from facial images. In order to classify gender, we propose a combination of features that have been extracted face, eye and lip regions by using a hybrid method of Local Binary Pattern and Gray-Level Co-Occurrence Matrix. The features have been extracted from automatically obtained face, eye and lip regions. All of the extracted features have been combined and given as input parameters to classification methods (Support Vector Machine, Artificial Neural Networks, Naive Bayes and k-Nearest Neighbor methods) for gender classification. The Nottingham Scan face database that consists of the frontal face images of 100 people (50 male and 50 female) is used for this purpose. As the result of the experimental studies, the highest success rate has been achieved as 98% by using Support Vector Machine. The experimental results illustrate the efficacy of our proposed method.

  6. Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

    Science.gov (United States)

    Adi Putra, Januar

    2018-04-01

    In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

  7. Relevance of the formal red meat classification system to the South ...

    African Journals Online (AJOL)

    Relevance of the formal red meat classification system to the South African ... to market information make them less willing to sell their animals through the formal market. ... Keywords: Communal farmers, marketing system, meat industry ...

  8. 5 CFR 9901.231 - Conversion of positions and employees to NSPS classification system.

    Science.gov (United States)

    2010-01-01

    ... HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Transitional... employee's career group, pay schedule, and band upon conversion. (d) Grade retention prior to conversion...

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

    Science.gov (United States)

    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

  10. Oro-facial pain and temporomandibular disorders classification systems: A critical appraisal and future directions.

    Science.gov (United States)

    Klasser, G D; Manfredini, D; Goulet, J-P; De Laat, A

    2018-03-01

    It is a difficult undertaking to design a classification system for any disease entity, let alone for oro-facial pain (OFP) and more specifically for temporomandibular disorders (TMD). A further complication of this task is that both physical and psychosocial variables must be included. To augment this process, a two-step systematic review, adhering to PRISMA guidelines, of the classification systems published during the last 20 years for OFP and TMD was performed. The first search step identified 190 potential citations which ultimately resulted in only 17 articles being included for in-depth analysis and review. The second step resulted in only 5 articles being selected for inclusion in this review. Five additional articles and four classification guidelines/criteria were also included due to expansion of the search criteria. Thus, in total, 14 documents comprising articles and guidelines/criteria (8 proposals of classification systems for OFP; 6 for TMD) were selected for inclusion in the systematic review. For each, a discussion as to their advantages, strengths and limitations was provided. Suggestions regarding the future direction for improving the classification process with the use of ontological principles rather than taxonomy are discussed. Furthermore, the potential for expanding the scope of axes included in existing classification systems, to include genetic, epigenetic and neurobiological variables, is explored. It is therefore recommended that future classification system proposals be based on combined approaches aiming to provide archetypal treatment-oriented classifications. © 2017 John Wiley & Sons Ltd.

  11. Socializing the human factors analysis and classification system: incorporating social psychological phenomena into a human factors error classification system.

    Science.gov (United States)

    Paletz, Susannah B F; Bearman, Christopher; Orasanu, Judith; Holbrook, Jon

    2009-08-01

    The presence of social psychological pressures on pilot decision making was assessed using qualitative analyses of critical incident interviews. Social psychological phenomena have long been known to influence attitudes and behavior but have not been highlighted in accident investigation models. Using a critical incident method, 28 pilots who flew in Alaska were interviewed. The participants were asked to describe a situation involving weather when they were pilot in command and found their skills challenged. They were asked to describe the incident in detail but were not explicitly asked to identify social pressures. Pressures were extracted from transcripts in a bottom-up manner and then clustered into themes. Of the 28 pilots, 16 described social psychological pressures on their decision making, specifically, informational social influence, the foot-in-the-door persuasion technique, normalization of deviance, and impression management and self-consistency motives. We believe accident and incident investigations can benefit from explicit inclusion of common social psychological pressures. We recommend specific ways of incorporating these pressures into theHuman Factors Analysis and Classification System.

  12. Rhythmic EEG patterns in extremely preterm infants : Classification and association with brain injury and outcome

    NARCIS (Netherlands)

    Weeke, Lauren C; van Ooijen, Inge M; Groenendaal, Floris; van Huffelen, Alexander C.; van Haastert, Ingrid C; van Stam, Carolien; Benders, Manon J; Toet, Mona C; Hellström-Westas, Lena; de Vries, Linda S

    2017-01-01

    OBJECTIVE: Classify rhythmic EEG patterns in extremely preterm infants and relate these to brain injury and outcome. METHODS: Retrospective analysis of 77 infants born <28 weeks gestational age (GA) who had a 2-channel EEG during the first 72 h after birth. Patterns detected by the BrainZ seizure

  13. Classification of nutrient emission sources in the Vistula River system

    International Nuclear Information System (INIS)

    Kowalkowski, Tomasz

    2009-01-01

    Eutrophication of the Baltic sea still remains one of the biggest problems in the north-eastern area of Europe. Recognizing the sources of nutrient emission, classification of their importance and finding the way towards reduction of pollution are the most important tasks for scientists researching this area. This article presents the chemometric approach to the classification of nutrient emission with respect to the regionalisation of emission sources within the Vistula River basin (Poland). Modelled data for mean yearly emission of nitrogen and phosphorus in 1991-2000 has been used for the classification. Seventeen subcatchements in the Vistula basin have been classified according to cluster and factor analyses. The results of this analysis allowed determination of groups of areas with similar pollution characteristics and indicate the need for spatial differentiation of policies and strategies. Three major factors indicating urban, erosion and agricultural sources have been identified as major discriminants of the groups. - Two classification methods applied to evaluate the results of nutrient emission allow definition of major sources of the emissions and classification of catchments with similar pollution.

  14. Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classification

    Science.gov (United States)

    Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree; Sadhu, Anup; Arif, Wasim

    2018-02-01

    In this paper, Curvelet based local attributes, Curvelet-Local configuration pattern (C-LCP), is introduced for the characterization of mammographic masses as benign or malignant. Amid different anomalies such as micro- calcification, bilateral asymmetry, architectural distortion, and masses, the reason for targeting the mass lesions is due to their variation in shape, size, and margin which makes the diagnosis a challenging task. Being efficient in classification, multi-resolution property of the Curvelet transform is exploited and local information is extracted from the coefficients of each subband using Local configuration pattern (LCP). The microscopic measures in concatenation with the local textural information provide more discriminating capability than individual. The measures embody the magnitude information along with the pixel-wise relationships among the neighboring pixels. The performance analysis is conducted with 200 mammograms of the DDSM database containing 100 mass cases of each benign and malignant. The optimal set of features is acquired via stepwise logistic regression method and the classification is carried out with Fisher linear discriminant analysis. The best area under the receiver operating characteristic curve and accuracy of 0.95 and 87.55% are achieved with the proposed method, which is further compared with some of the state-of-the-art competing methods.

  15. Nuclear power plant systems, structures and components and their safety classification

    International Nuclear Information System (INIS)

    2000-01-01

    The assurance of a nuclear power plant's safety is based on the reliable functioning of the plant as well as on its appropriate maintenance and operation. To ensure the reliability of operation, special attention shall be paid to the design, manufacturing, commissioning and operation of the plant and its components. To control these functions the nuclear power plant is divided into structural and functional entities, i.e. systems. A systems safety class is determined by its safety significance. Safety class specifies the procedures to be employed in plant design, construction, monitoring and operation. The classification document contains all documentation related to the classification of the nuclear power plant. The principles of safety classification and the procedures pertaining to the classification document are presented in this guide. In the Appendix of the guide, examples of systems most typical of each safety class are given to clarify the safety classification principles

  16. Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

    Science.gov (United States)

    Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

    2012-01-01

    Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

  17. Initial steps towards an evidence-based classification system for golfers with a physical impairment

    NARCIS (Netherlands)

    Stoter, Inge K.; Hettinga, Florentina J.; Altmann, Viola; Eisma, Wim; Arendzen, Hans; Bennett, Tony; van der Woude, Lucas H.; Dekker, Rienk

    2017-01-01

    Purpose: The present narrative review aims to make a first step towards an evidence-based classification system in handigolf following the International Paralympic Committee (IPC). It intends to create a conceptual framework of classification for handigolf and an agenda for future research. Method:

  18. Classification of Metal-Deficient Dwarfs in the Vilnius Photometric System

    Directory of Open Access Journals (Sweden)

    Lazauskaitė R.

    2003-12-01

    Full Text Available Methods used for the quantitative classification of metal-deficient stars in the Vilnius photometric system are reviewed. We present a new calibration of absolute magnitudes for dwarfs and subdwarfs, based on Hipparcos parallaxes. The new classification scheme is applied to a sample of Population II visual binaries.

  19. An ecological classification system for the central hardwoods region: The Hoosier National Forest

    Science.gov (United States)

    James E. Van Kley; George R. Parker

    1993-01-01

    This study, a multifactor ecological classification system, using vegetation, soil characteristics, and physiography, was developed for the landscape of the Hoosier National Forest in Southern Indiana. Measurements of ground flora, saplings, and canopy trees from selected stands older than 80 years were subjected to TWINSPAN classification and DECORANA ordination....

  20. Pattern Recognition and Classification of Fatal Traffic Accidents in Israel A Neural Network Approach

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Gitelman, Victoria; Bekhor, Shlomo

    2011-01-01

    on 1,793 fatal traffic accidents occurred during the period between 2003 and 2006 and applies Kohonen and feed-forward back-propagation neural networks with the objective of extracting from the data typical patterns and relevant factors. Kohonen neural networks reveal five compelling accident patterns....... Feed-forward back-propagation neural networks indicate that sociodemographic characteristics of drivers and victims, accident location, and period of the day are extremely relevant factors. Accident patterns suggest that countermeasures are necessary for identified problems concerning mainly vulnerable...

  1. Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea

    International Nuclear Information System (INIS)

    Palit, Mousumi; Tudu, Bipan; Bhattacharyya, Nabarun; Dutta, Ankur; Dutta, Pallab Kumar; Jana, Arun; Bandyopadhyay, Rajib; Chatterjee, Anutosh

    2010-01-01

    In an electronic tongue, preprocessing on raw data precedes pattern analysis and choice of the appropriate preprocessing technique is crucial for the performance of the pattern classifier. While attempting to classify different grades of black tea using a voltammetric electronic tongue, different preprocessing techniques have been explored and a comparison of their performances is presented in this paper. The preprocessing techniques are compared first by a quantitative measurement of separability followed by principle component analysis; and then two different supervised pattern recognition models based on neural networks are used to evaluate the performance of the preprocessing techniques.

  2. Statistical Discriminability Estimation for Pattern Classification Based on Neural Incremental Attribute Learning

    DEFF Research Database (Denmark)

    Wang, Ting; Guan, Sheng-Uei; Puthusserypady, Sadasivan

    2014-01-01

    Feature ordering is a significant data preprocessing method in Incremental Attribute Learning (IAL), a novel machine learning approach which gradually trains features according to a given order. Previous research has shown that, similar to feature selection, feature ordering is also important based...... estimation. Moreover, a criterion that summarizes all the produced values of AD is employed with a GA (Genetic Algorithm)-based approach to obtain the optimum feature ordering for classification problems based on neural networks by means of IAL. Compared with the feature ordering obtained by other approaches...

  3. Classification of rhythmic locomotor patterns in electromyographic signals using fuzzy sets

    Directory of Open Access Journals (Sweden)

    Thrasher Timothy A

    2011-12-01

    Full Text Available Abstract Background Locomotor control is accomplished by a complex integration of neural mechanisms including a central pattern generator, spinal reflexes and supraspinal control centres. Patterns of muscle activation during walking exhibit an underlying structure in which groups of muscles seem to activate in united bursts. Presented here is a statistical approach for analyzing Surface Electromyography (SEMG data with the goal of classifying rhythmic "burst" patterns that are consistent with a central pattern generator model of locomotor control. Methods A fuzzy model of rhythmic locomotor patterns was optimized and evaluated using SEMG data from a convenience sample of four able-bodied individuals. As well, two subjects with pathological gait participated: one with Parkinson's Disease, and one with incomplete spinal cord injury. Subjects walked overground and on a treadmill while SEMG was recorded from major muscles of the lower extremities. The model was fit to half of the recorded data using non-linear optimization and validated against the other half of the data. The coefficient of determination, R2, was used to interpret the model's goodness of fit. Results Using four fuzzy burst patterns, the model was able to explain approximately 70-83% of the variance in muscle activation during treadmill gait and 74% during overground gait. When five burst functions were used, one function was found to be redundant. The model explained 81-83% of the variance in the Parkinsonian gait, and only 46-59% of the variance in spinal cord injured gait. Conclusions The analytical approach proposed in this article is a novel way to interpret multichannel SEMG signals by reducing the data into basic rhythmic patterns. This can help us better understand the role of rhythmic patterns in locomotor control.

  4. A novel approach for SEMG signal classification with adaptive local binary patterns.

    Science.gov (United States)

    Ertuğrul, Ömer Faruk; Kaya, Yılmaz; Tekin, Ramazan

    2016-07-01

    Feature extraction plays a major role in the pattern recognition process, and this paper presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is built on the local binary pattern (LBP), which is an image processing method, and one-dimensional local binary pattern (1D-LBP). In LBP, each pixel is compared with its neighbors. Similarly, in 1D-LBP, each data in the raw is judged against its neighbors. 1D-LBP extracts feature based on local changes in the signal. Therefore, it has high a potential to be employed in medical purposes. Since, each action or abnormality, which is recorded in SEMG signals, has its own pattern, and via the 1D-LBP these (hidden) patterns may be detected. But, the positions of the neighbors in 1D-LBP are constant depending on the position of the data in the raw. Also, both LBP and 1D-LBP are very sensitive to noise. Therefore, its capacity in detecting hidden patterns is limited. To overcome these drawbacks, aLBP was proposed. In aLBP, the positions of the neighbors and their values can be assigned adaptively via the down-sampling and the smoothing coefficients. Therefore, the potential to detect (hidden) patterns, which may express an illness or an action, is really increased. To validate the proposed feature extraction approach, two different datasets were employed. Achieved accuracies by the proposed approach were higher than obtained results by employed popular feature extraction approaches and the reported results in the literature. Obtained accuracy results were brought out that the proposed method can be employed to investigate SEMG signals. In summary, this work attempts to develop an adaptive feature extraction scheme that can be utilized for extracting features from local changes in different categories of time-varying signals.

  5. Automatic classification of canine PRG neuronal discharge patterns using K-means clustering.

    Science.gov (United States)

    Zuperku, Edward J; Prkic, Ivana; Stucke, Astrid G; Miller, Justin R; Hopp, Francis A; Stuth, Eckehard A

    2015-02-01

    Respiratory-related neurons in the parabrachial-Kölliker-Fuse (PB-KF) region of the pons play a key role in the control of breathing. The neuronal activities of these pontine respiratory group (PRG) neurons exhibit a variety of inspiratory (I), expiratory (E), phase spanning and non-respiratory related (NRM) discharge patterns. Due to the variety of patterns, it can be difficult to classify them into distinct subgroups according to their discharge contours. This report presents a method that automatically classifies neurons according to their discharge patterns and derives an average subgroup contour of each class. It is based on the K-means clustering technique and it is implemented via SigmaPlot User-Defined transform scripts. The discharge patterns of 135 canine PRG neurons were classified into seven distinct subgroups. Additional methods for choosing the optimal number of clusters are described. Analysis of the results suggests that the K-means clustering method offers a robust objective means of both automatically categorizing neuron patterns and establishing the underlying archetypical contours of subtypes based on the discharge patterns of group of neurons. Published by Elsevier B.V.

  6. Pattern transition between periodic Liesegang pattern and crystal growth regime in reaction-diffusion systems

    Science.gov (United States)

    Lagzi, István; Ueyama, Daishin

    2009-01-01

    The pattern transition between periodic precipitation pattern formation (Liesegang phenomenon) and pure crystal growth regimes is investigated in silver nitrate and potassium dichromate system in mixed agarose-gelatin gel. Morphologically different patterns were found depending on the quality of the gel, and transition between these typical patterns can be controlled by the concentration of gelatin in mixed gel. Effect of temperature and hydrodynamic force on precipitation pattern structure was also investigated.

  7. How to Diagnose and Classify Tattoo Complications in the Clinic: A System of Distinctive Patterns.

    Science.gov (United States)

    Serup, Jørgen

    2017-01-01

    Tattoo complications represent a broad spectrum of clinical entities and disease mechanisms. Infections are known, but chronic inflammatory reactions have hitherto been inconsistently reported and given many interpretations and terms. A clinical classification system of distinct patterns with emphasis on inflammatory tattoo reactions is introduced. Allergic reactions prevalent in red tattoos and often associated with azo pigments are manifested as the 'plaque elevation', 'excessive hyperkeratosis', and 'ulceronecrotic' patterns. The allergen is a hapten. Nonallergic reactions prevalent in black tattoos and associated with carbon black are manifested as the 'papulonodular' pattern. Carbon black nanoparticles agglomerate in the dermis over time forming foreign bodies that elicit reactions. Many black tattoos even develop sarcoid granuloma, and the 'papulonodular' pattern is strongly associated with sarcoidosis affecting other organs. Tattoo complications include a large group of less frequent but nevertheless specific entities, i.e. irritant and toxic local events, photosensitivity, urticaria, eczematous rash due to soluble allergen, neurosensitivity and pain syndrome, lymphopathies, pigment diffusion or fan, scars, and other sequels of tattooing or tattoo removal. Keratoacanthoma occurs in tattoos. Carcinoma and melanoma are rare and occur by coincidence only. Different tattoo complications require different therapeutic approaches, and precise diagnosis is thus important as a key to therapy. The proposed new classification with characteristic patterns relies on simple tools, namely patient history, objective findings, and supplementary punch biopsy. By virtue of simplicity and broad access, these methods make the proposed classification widely applicable in clinics and hospitals. The system is reported to the 11th revision of the WHO diagnosis classification used as international standard. © 2017 S. Karger AG, Basel.

  8. The infant disorganised attachment classification: "Patterning within the disturbance of coherence".

    Science.gov (United States)

    Reijman, Sophie; Foster, Sarah; Duschinsky, Robbie

    2018-03-01

    Since its introduction by Main and Solomon in 1990, the infant disorganised attachment classification has functioned as a predictor of mental health in developmental psychology research. It has also been used by practitioners as an indicator of inadequate parenting and developmental risk, at times with greater confidence than research would support. Although attachment disorganisation takes many forms, it is generally understood to reflect a child's experience of being repeatedly alarmed by their parent's behaviour. In this paper we analyse how the infant disorganised attachment classification has been stabilised and interpreted, reporting results from archival study, ethnographic observations at four training institutes for coding disorganised attachment, interviews with researchers, certified coders and clinicians, and focus groups with child welfare practitioners. Our analysis points to the role of power/knowledge disjunctures in hindering communication between key groups: Main and Solomon and their readers; the oral culture of coders and the written culture of published papers; the research community and practitioners. We highlight how understandings of disorganised attachment have been magnetised by a simplified image of a child fearful of his or her own parent. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  9. Common Patterns of Congenital Lower Extremity Shortening: Diagnosis, Classification, and Follow-up.

    Science.gov (United States)

    Bedoya, Maria A; Chauvin, Nancy A; Jaramillo, Diego; Davidson, Richard; Horn, B David; Ho-Fung, Victor

    2015-01-01

    Congenital lower limb shortening is a group of relatively rare, heterogeneous disorders. Proximal focal femoral deficiency (PFFD) and fibular hemimelia (FH) are the most common pathologic entities in this disease spectrum. PFFD is characterized by variable degrees of shortening or absence of the femoral head, with associated dysplasia of the acetabulum and femoral shaft. FH ranges from mild hypoplasia to complete absence of the fibula with variable shortening of the tibia. The development of the lower limb requires complex and precise gene interactions. Although the etiologies of PFFD and FH remain unknown, there is a strong association between the two disorders. Associated congenital defects in the lower extremity are found in more than 50% of patients with PFFD, ipsilateral FH being the most common. FH also has a strong association with shortening and bowing of the tibia and with foot deformities such as absence of the lateral rays of the foot. Early diagnosis and radiologic classification of these abnormalities are imperative for appropriate management and surgical planning. Plain radiography remains the main diagnostic imaging modality for both PFFD and FH, and appropriate description of the osseous abnormalities seen on radiographs allows accurate classification, prognostic evaluation, and surgical planning. Minor malformations may commonly be misdiagnosed. ©RSNA, 2015.

  10. Toward a common classification approach for biorefinery systems

    DEFF Research Database (Denmark)

    Cherubini, Francesco; Jungmeier, Gerfried; Wellisch, Maria

    2009-01-01

    until 2020 is based on their characteristics to be mixed with gasoline, diesel and natural gas, reflecting the main advantage of using the already-existing infrastructure for easier market introduction. This classification approach relies on four main features: (1) platforms; (2) products; (3) feedstock...

  11. 42 CFR 412.620 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ...-mix group classifications and weighting factors. We may periodically adjust the case-mix groups and... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix... assessments under § 412.610(c)(1) are used to classify a Medicare patient into an appropriate case-mix group...

  12. Meta-language for land use classification systems

    CSIR Research Space (South Africa)

    Cooper, Antony K

    2014-04-01

    Full Text Available This presentation provides an overview of a meta-language for land use classification. It also explains why land use can’t always be determined from imagery, and why land use is not the same as land cover, zoning or planning - though...

  13. Generating Clustered Journal Maps : An Automated System for Hierarchical Classification

    NARCIS (Netherlands)

    Leydesdorff, L.; Bornmann, L.; Wagner, C.S.

    2017-01-01

    Journal maps and classifications for 11,359 journals listed in the combined Journal Citation Reports 2015 of the Science and Social Sciences Citation Indexes are provided at https://leydesdorff.github.io/journals/ and http://www.leydesdorff.net/jcr15. A routine using VOSviewer for integrating the

  14. Evaluation of the utility of a glycemic pattern identification system.

    Science.gov (United States)

    Otto, Erik A; Tannan, Vinay

    2014-07-01

    With the increasing prevalence of systems allowing automated, real-time transmission of blood glucose data there is a need for pattern recognition techniques that can inform of deleterious patterns in glycemic control when people test. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes. To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows. Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The system was also significantly more predictive of deleterious events than other pattern identification methods evaluated, and was persistently predictive up to 3 months after pattern identification. The system identified patterns that are significantly predictive of deleterious glycemic events, and more so relative to many pattern identification methods used in diabetes management today. Further study will inform how improved pattern identification can lead to improved glycemic control. © 2014 Diabetes Technology Society.

  15. An objective daily Weather Type classification for Iberia since 1850; patterns, trends, variability and impact in precipitation

    Science.gov (United States)

    Ramos, A. M.; Trigo, R. M.; Lorenzo, M. N.; Vaquero, J. M.; Gallego, M. C.; Valente, M. A.; Gimeno, L.

    2009-04-01

    In recent years a large number of automated classifications of atmospheric circulation patterns have been published covering the entire European continent or specific sub-regions (Huth et al., 2008). This generalized use of objective classifications results from their relatively straightforward computation but crucially from their capacity to provide simple description of typical synoptic conditions as well as their climatic and environmental impact. For this purpose, the vast majority of authors has employed the Reanalyses datasets, namely from either NCEP/NCAR or ECMWF projects. However, both these widely used datasets suffer from important caveats, namely their restricted temporal coverage, that is limited to the last six decades (NCEP/NCAR since 1948 and ECMWF since 1958). This limitation has been partially mitigated by the recent availability of continuous daily mean sea level pressure obtained within the European project EMULATE, that extended the historic records over the extra-tropical Atlantic and Europe (70°-25° N by 70° W-50° E), for the period 1850 to the present (Ansell, T. J. et al. 2006). Here we have used the extended EMULATE dataset to construct an automated version of the Lamb Weather type (WTs) classification scheme (Jones et al 1993) adapted for the center of the Iberian Peninsula. We have identified 10 basic WTs (Cyclonic, Anticyclonic and 8 directional types) following a similar methodology to that previously adopted by Trigo and DaCamara, 2000 (for Portugal) and Lorenzo et al. 2008 (for Galicia, northwestern Iberia). We have evaluated trends of monthly/seasonal frequency of each WT for the entire period and several shorter periods. Finally, we use the long-term precipitation time series from Lisbon (recently digitized) and Cadiz (southern Spain) to evaluate, the impact of each WT on the precipitation regime. It is shown that the Anticyclonic (A) type, although being the most frequent class in winter, gives a rather small contribution to

  16. Deep learning based classification of morphological patterns in RCM to guide noninvasive diagnosis of melanocytic lesions (Conference Presentation)

    Science.gov (United States)

    Kose, Kivanc; Bozkurt, Alican; Ariafar, Setareh; Alessi-Fox, Christi A.; Gill, Melissa; Dy, Jennifer G.; Brooks, Dana H.; Rajadhyaksha, Milind

    2017-02-01

    In this study we present a deep learning based classification algorithm for discriminating morphological patterns that appear in RCM mosaics of melanocytic lesions collected at the dermal epidermal junction (DEJ). These patterns are classified into 6 distinct types in the literature: background, meshwork, ring, clod, mixed, and aspecific. Clinicians typically identify these morphological patterns by examination of their textural appearance at 10X magnification. To mimic this process we divided mosaics into smaller regions, which we call tiles, and classify each tile in a deep learning framework. We used previously acquired DEJ mosaics of lesions deemed clinically suspicious, from 20 different patients, which were then labelled according to those 6 types by 2 expert users. We tried three different approaches for classification, all starting with a publicly available convolutional neural network (CNN) trained on natural image, consisting of a series of convolutional layers followed by a series of fully connected layers: (1) We fine-tuned this network using training data from the dataset. (2) Instead, we added an additional fully connected layer before the output layer network and then re-trained only last two layers, (3) We used only the CNN convolutional layers as a feature extractor, encoded the features using a bag of words model, and trained a support vector machine (SVM) classifier. Sensitivity and specificity were generally comparable across the three methods, and in the same ranges as our previous work using SURF features with SVM . Approach (3) was less computationally intensive to train but more sensitive to unbalanced representation of the 6 classes in the training data. However we expect CNN performance to improve as we add more training data because both the features and the classifier are learned jointly from the data. *First two authors share first authorship.

  17. CLASSIFICATION OF SYSTEMS FOR PASSIVE AFTERHEAT REMOVAL FROM REACTOR CONTAINMENT OF NUCLEAR POWER PLANT WITH WATER-COOLED POWER REACTOR

    Directory of Open Access Journals (Sweden)

    N. Khaled

    2014-01-01

    Full Text Available A classification on systems for passive afterheat removal from reactor containment has been developed in the paper.  The classification permits to make a detailed analysis of various concepts pertaining to systems for passive afterheat removal from reactor containment of new generation. The paper considers main classification features of the given systems.

  18. A review on fault classification methodologies in power transmission systems: Part-II

    Directory of Open Access Journals (Sweden)

    Avagaddi Prasad

    2018-05-01

    Full Text Available The countless extent of power systems and applications requires the improvement in suitable techniques for the fault classification in power transmission systems, to increase the efficiency of the systems and to avoid major damages. For this purpose, the technical literature proposes a large number of methods. The paper analyzes the technical literature, summarizing the most important methods that can be applied to fault classification methodologies in power transmission systems.The part 2 of the article is named “A review on fault classification methodologies in power transmission systems”. In this part 2 we discussed the advanced technologies developed by various researchers for fault classification in power transmission systems. Keywords: Transmission line protection, Protective relaying, Soft computing techniques

  19. Patterns of Weakness, Classification of Motor Neuron Disease, and Clinical Diagnosis of Sporadic Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Statland, Jeffrey M; Barohn, Richard J; McVey, April L; Katz, Jonathan S; Dimachkie, Mazen M

    2015-11-01

    When approaching a patient with suspected motor neuron disease (MND), the pattern of weakness on examination helps distinguish MND from other diseases of peripheral nerves, the neuromuscular junction, or muscle. MND is a clinical diagnosis supported by findings on electrodiagnostic testing. MNDs exist on a spectrum, from a pure lower motor neuron to mixed upper and lower motor neuron to a pure upper motor neuron variant. Amyotrophic lateral sclerosis (ALS) is a progressive mixed upper and lower motor neuron disorder, most commonly sporadic, which is invariably fatal. This article describes a pattern approach to identifying MND and clinical features of sporadic ALS. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. From Image Processing to Classification: 1. Modelling Disturbances of Isoelectric Focusing Patterns

    DEFF Research Database (Denmark)

    Jensen, Karsten; Søndergaard, I.; Skovgaard, I. M.

    1995-01-01

    In order to optimize the conditions for evaluation of isoelectric focusing (IEF) patterns by digital image processing, the sources of error in determination of the pi values were analyzed together with the influence of a varying background. The effects of band distortions, in the spectra...... of the individual lanes, were examined. In order to minimize the effect of these distortions, optimal conditions for handling IEF patterns by digital image processing were elucidated. The systematic part of the global deformation on the gels was investigated and an algorithm was developed by which it was possible...

  1. Overview of Four Functional Classification Systems Commonly Used in Cerebral Palsy

    Directory of Open Access Journals (Sweden)

    Andrea Paulson

    2017-04-01

    Full Text Available Cerebral palsy (CP is the most common physical disability in childhood. CP comprises a heterogeneous group of disorders that can result in spasticity, dystonia, muscle contractures, weakness and coordination difficulty that ultimately affects the ability to control movements. Traditionally, CP has been classified using a combination of the motor type and the topographical distribution, as well as subjective severity level. Imprecise terms such as these tell very little about what a person is able to do functionally and can impair clear communication between providers. More recently, classification systems have been created employing a simple ordinal grading system of functional performance. These systems allow a more precise discussion between providers, as well as better subject stratification for research. The goal of this review is to describe four common functional classification systems for cerebral palsy: the Gross Motor Function Classification System (GMFCS, the Manual Ability Classification System (MACS, the Communication Function Classification System (CFCS, and the Eating and Drinking Ability Classification System (EDACS. These measures are all standardized, reliable, and complementary to one another.

  2. 5 CFR 9701.231 - Conversion of positions and employees to the DHS classification system.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Conversion of positions and employees to... Provisions § 9701.231 Conversion of positions and employees to the DHS classification system. (a) This... from the GS system, a prevailing rate system, the SL/ST system, or the SES system, as provided in...

  3. A New Functional Classification of Glucuronoyl Esterases by Peptide Pattern Recognition

    DEFF Research Database (Denmark)

    Wittrup Agger, Jane; Busk, Peter Kamp; Pilgaard, Bo

    2017-01-01

    of characterized enzymes exist and the exact activity is still uncertain. Here peptide pattern recognition is used as a bioinformatic tool to identify and group new CE15 proteins that are likely to have glucuronoyl esterase activity. 1024 CE15-like sequences were drawn from GenBank and grouped into 24 groups...

  4. Classification of Topographical Pattern of Spasticity in Cerebral Palsy: A Registry Perspective

    Science.gov (United States)

    Reid, Susan M.; Carlin, John B.; Reddihough, Dinah S.

    2011-01-01

    This study used data from a population-based cerebral palsy (CP) registry and systematic review to assess the amount of heterogeneity between registries in topographical patterns when dichotomised into unilateral (USCP) and bilateral spastic CP (BSCP), and whether the terms diplegia and quadriplegia provide useful additional epidemiological…

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

    Science.gov (United States)

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

    2010-01-01

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

  6. Interplay of biopharmaceutics, biopharmaceutics drug disposition and salivary excretion classification systems

    Science.gov (United States)

    Idkaidek, Nasir M.

    2013-01-01

    The aim of this commentary is to investigate the interplay of Biopharmaceutics Classification System (BCS), Biopharmaceutics Drug Disposition Classification System (BDDCS) and Salivary Excretion Classification System (SECS). BCS first classified drugs based on permeability and solubility for the purpose of predicting oral drug absorption. Then BDDCS linked permeability with hepatic metabolism and classified drugs based on metabolism and solubility for the purpose of predicting oral drug disposition. On the other hand, SECS classified drugs based on permeability and protein binding for the purpose of predicting the salivary excretion of drugs. The role of metabolism, rather than permeability, on salivary excretion is investigated and the results are not in agreement with BDDCS. Conclusion The proposed Salivary Excretion Classification System (SECS) can be used as a guide for drug salivary excretion based on permeability (not metabolism) and protein binding. PMID:24493977

  7. An indigenous soil classification system for Bellona Island - a raised atoll in the Solomon Islands

    DEFF Research Database (Denmark)

    Elberling, Bo; Breuning-Madsen, Henrik; Bruun, Thilde Bech

    2010-01-01

    One of the challenges of evaluating existing traditional farming systems is to combine local knowledge and modern scientific methods and terminology. This requires an evaluation of indigenous soil classification in modern terms. This paper focuses on an indigenous soil classification system...... perceive the same four out of seven soil types as highly useful for cultivation and rank these soil types similarly according to their suitability for different crops such as yam, watermelon, cassava and sweet potato. It is concluded that the indigenous soil classification is in line with the soil...... production potential and useful for land evaluation on Bellona....

  8. Inattention in primary school is not good for your future school achievement-A pattern classification study.

    Science.gov (United States)

    Lundervold, Astri J; Bøe, Tormod; Lundervold, Arvid

    2017-01-01

    Inattention in childhood is associated with academic problems later in life. The contribution of specific aspects of inattentive behaviour is, however, less known. We investigated feature importance of primary school teachers' reports on nine aspects of inattentive behaviour, gender and age in predicting future academic achievement. Primary school teachers of n = 2491 children (7-9 years) rated nine items reflecting different aspects of inattentive behaviour in 2002. A mean academic achievement score from the previous semester in high school (2012) was available for each youth from an official school register. All scores were at a categorical level. Feature importances were assessed by using multinominal logistic regression, classification and regression trees analysis, and a random forest algorithm. Finally, a comprehensive pattern classification procedure using k-fold cross-validation was implemented. Overall, inattention was rated as more severe in boys, who also obtained lower academic achievement scores in high school than girls. Problems related to sustained attention and distractibility were together with age and gender defined as the most important features to predict future achievement scores. Using these four features as input to a collection of classifiers employing k-fold cross-validation for prediction of academic achievement level, we obtained classification accuracy, precision and recall that were clearly better than chance levels. Primary school teachers' reports of problems related to sustained attention and distractibility were identified as the two most important features of inattentive behaviour predicting academic achievement in high school. Identification and follow-up procedures of primary school children showing these characteristics should be prioritised to prevent future academic failure.

  9. Inattention in primary school is not good for your future school achievement-A pattern classification study.

    Directory of Open Access Journals (Sweden)

    Astri J Lundervold

    Full Text Available Inattention in childhood is associated with academic problems later in life. The contribution of specific aspects of inattentive behaviour is, however, less known. We investigated feature importance of primary school teachers' reports on nine aspects of inattentive behaviour, gender and age in predicting future academic achievement. Primary school teachers of n = 2491 children (7-9 years rated nine items reflecting different aspects of inattentive behaviour in 2002. A mean academic achievement score from the previous semester in high school (2012 was available for each youth from an official school register. All scores were at a categorical level. Feature importances were assessed by using multinominal logistic regression, classification and regression trees analysis, and a random forest algorithm. Finally, a comprehensive pattern classification procedure using k-fold cross-validation was implemented. Overall, inattention was rated as more severe in boys, who also obtained lower academic achievement scores in high school than girls. Problems related to sustained attention and distractibility were together with age and gender defined as the most important features to predict future achievement scores. Using these four features as input to a collection of classifiers employing k-fold cross-validation for prediction of academic achievement level, we obtained classification accuracy, precision and recall that were clearly better than chance levels. Primary school teachers' reports of problems related to sustained attention and distractibility were identified as the two most important features of inattentive behaviour predicting academic achievement in high school. Identification and follow-up procedures of primary school children showing these characteristics should be prioritised to prevent future academic failure.

  10. Solar ultraviolet and the occupational radiant exposure of Queensland school teachers: A comparative study between teaching classifications and behavior patterns.

    Science.gov (United States)

    Downs, Nathan J; Harrison, Simone L; Chavez, Daniel R Garzon; Parisi, Alfio V

    2016-05-01

    Classroom teachers located in Queensland, Australia are exposed to high levels of ambient solar ultraviolet as part of the occupational requirement to provide supervision of children during lunch and break times. We investigated the relationship between periods of outdoor occupational radiant exposure and available ambient solar radiation across different teaching classifications and schools relative to the daily occupational solar ultraviolet radiation (HICNIRP) protection standard of 30J/m(2). Self-reported daily sun exposure habits (n=480) and personal radiant exposures were monitored using calibrated polysulphone dosimeters (n=474) in 57 teaching staff from 6 different schools located in tropical north and southern Queensland. Daily radiant exposure patterns among teaching groups were compared to the ambient UV-Index. Personal sun exposures were stratified among teaching classifications, school location, school ownership (government vs non-government), and type (primary vs secondary). Median daily radiant exposures were 15J/m(2) and 5J/m(2)HICNIRP for schools located in northern and southern Queensland respectively. Of the 474 analyzed dosimeter-days, 23.0% were found to exceed the solar radiation protection standard, with the highest prevalence found among physical education teachers (57.4% dosimeter-days), followed by teacher aides (22.6% dosimeter-days) and classroom teachers (18.1% dosimeter-days). In Queensland, peak outdoor exposure times of teaching staff correspond with periods of extreme UV-Index. The daily occupational HICNIRP radiant exposure standard was exceeded in all schools and in all teaching classifications. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. A comparison of the Web of Science with publication-level classification systems of science

    Energy Technology Data Exchange (ETDEWEB)

    Perianes-Rodriguez, A.; Ruiz-Castillo, J.

    2016-07-01

    In this paper we propose a new criterion for choosing between a pair of classification systems of science that assign publications (or journals) to a set of scientific fields. Consider the standard normalization procedure in which field mean citations are used as normalization factors. We recommend system A over system B whenever the standard normalization procedure based on A performs better than the when it is based on B. Since the evaluation can be made in terms of either system, the performance assessment requires a double test. In addition, since the assessment of two normalization procedures would be generally biased in favor of the one based on the classification system used for evaluation purposes, ideally a pair of classification systems must be compared using a third, independent classification system for evaluation purposes. We illustrate this strategy by comparing a Web of Science journal-level classification system, consisting of 236 journal subject categories, with two publication-level algorithmically constructed classification systems consisting of 1,363 (G6) and 5,119 (G8) clusters. There are two main findings. (1) The G8 system is found to dominate the G6 system. Therefore, when we have a choice between two classification systems at different granularity levels, we should use the system at the higher level because it typically exhibits a better standard normalization performance. (2) The G8 system and the Web of Science (WoS) journal-level system are found to be non-comparable. Nevertheless, the G8-normalization procedure performs better using the WoS system for evaluation purposes than the WoS-normalization procedure using the G8 system for evaluation purposes. Furthermore, when we use the G6 system for evaluation purposes, the G8-normalization procedure performs better than the WoS-normalization procedure. We conclude that algorithmically constructed classification systems constitute a credible alternative to the WoS system and, by extension, to

  12. System of pattern analysis of PIXE spectra

    Energy Technology Data Exchange (ETDEWEB)

    Murozono, K; Iwasaki, S; Inoue, J; Ishii, K; Kitamura, M [Tohoku Univ., Sendai (Japan). Faculty of Engineering; Sera, K; Futatsugawa, S

    1996-07-01

    We have developed an analysis system based on the pattern analysis method. By testing the system, several difficulties of the present method have been identified. We found the following solutions for them: pre-selection of candidate elements in a sample and the use of a proper absorber. The pre-selection of the candidate elements will not be a serious drawback in the industrial PIXE, because it will be easy to pre-process the spectra for a few samples in the beginning of the mass processing of samples of the same kind. On the other hand, reduction of the efficiency due to the use of funny filter is significant only in the lower energy region, where we usually do not suffer from insufficient yields of lighter elements in common samples. The selection of the most suitable filter requires PIXE user to be deeply experienced. In particular, it is not easy to choose the best filter to suppress the yield of peak of an abundant element as the absorption edge filter. It will be important task to find a set of suitable combination of representative samples and corresponding filters. Furthermore, the peak profile model should be improved from the simple Gaussian approximation to more realistic ones with exponential tail, flat component below the peak and escape peaks, etc. It is also necessary to develop a theoretical approach for the background shape of the bremsstrahlung. (J.P.N.)

  13. Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine.

    Science.gov (United States)

    Deschamps, Kevin; Matricali, Giovanni Arnoldo; Desmet, Dirk; Roosen, Philip; Keijsers, Noel; Nobels, Frank; Bruyninckx, Herman; Staes, Filip

    2016-09-01

    The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

    Science.gov (United States)

    Dieckman, Eric Allen

    In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

  15. EULAR points to consider in the development of classification and diagnostic criteria in systemic vasculitis

    DEFF Research Database (Denmark)

    Basu, Neil; Watts, Richard; Bajema, Ingeborg

    2010-01-01

    The systemic vasculitides are multiorgan diseases where early diagnosis and treatment can significantly improve outcomes. Robust nomenclature reduces diagnostic delay. However, key aspects of current nomenclature are widely perceived to be out of date, these include disease definitions, classific......, classification and diagnostic criteria. Therefore, the aim of the present work was to identify deficiencies and provide contemporary points to consider for the development of future definitions and criteria in systemic vasculitis....

  16. A Preliminary Study on the Multiple Mapping Structure of Classification Systems for Heterogeneous Databases

    OpenAIRE

    Seok-Hyoung Lee; Hwan-Min Kim; Ho-Seop Choe

    2012-01-01

    While science and technology information service portals and heterogeneous databases produced in Korea and other countries are integrated, methods of connecting the unique classification systems applied to each database have been studied. Results of technologists' research, such as, journal articles, patent specifications, and research reports, are organically related to each other. In this case, if the most basic and meaningful classification systems are not connected, it is difficult to ach...

  17. Turing Patterns in a Reaction-Diffusion System

    International Nuclear Information System (INIS)

    Wu Yanning; Wang Pingjian; Hou Chunju; Liu Changsong; Zhu Zhengang

    2006-01-01

    We have further investigated Turing patterns in a reaction-diffusion system by theoretical analysis and numerical simulations. Simple Turing patterns and complex superlattice structures are observed. We find that the shape and type of Turing patterns depend on dynamical parameters and external periodic forcing, and is independent of effective diffusivity rate σ in the Lengyel-Epstein model. Our numerical results provide additional insight into understanding the mechanism of development of Turing patterns and predicting new pattern formations.

  18. Face recognition system and method using face pattern words and face pattern bytes

    Science.gov (United States)

    Zheng, Yufeng

    2014-12-23

    The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

  19. A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

    Science.gov (United States)

    Oliker, Nurit; Ostfeld, Avi

    2014-03-15

    This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Measurement of semantic similarity for land use and land cover classification systems

    Science.gov (United States)

    Deng, Dongpo

    2008-12-01

    Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between land cover categories. To understand the meaning and the use of terminology from different domains, the common ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three LULC classification systems: CORINE (European Environmental Agency), Oregon State, USA), and Taiwan. The semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then semantic properties and relations of categories in three LULC classification systems are mutually compared. The visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find out the semantic similar objects.

  1. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    Science.gov (United States)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  2. Classification of videocapsule endoscopy image patterns: comparative analysis between patients with celiac disease and normal individuals

    Directory of Open Access Journals (Sweden)

    Ciaccio Edward J

    2010-09-01

    Full Text Available Abstract Background Quantitative disease markers were developed to assess videocapsule images acquired from celiac disease patients with villous atrophy, and from control patients. Method Capsule endoscopy videoclip images (576 × 576 pixels were acquired at 2/second frame rate (11 celiacs, 10 controls at regions: 1. bulb, 2. duodenum, 3. jejunum, 4. ileum and 5. distal ileum. Each of 200 images per videoclip (= 100s were subdivided into 10 × 10 pixel subimages for which mean grayscale brightness level and its standard deviation (texture were calculated. Pooled subimage values were grouped into low, intermediate, and high texture bands, and mean brightness, texture, and number of subimages in each band (nine features in all were used for quantifying regions 1-5, and to determine the three best features for threshold and incremental learning classification. Classifiers were developed using 6 celiac and 5 control patients' data as exemplars, and tested on 5 celiacs and 5 controls. Results Pooled from all regions, the threshold classifier had 80% sensitivity and 96% specificity and the incremental classifier had 88% sensitivity and 80% specificity for predicting celiac versus control videoclips in the test set. Trends of increasing texture from regions 1 to 5 occurred in the low and high texture bands in celiacs, and the number of subimages in the low texture band diminished (r2 > 0.5. No trends occurred in controls. Conclusions Celiac videocapsule images have textural properties that vary linearly along the small intestine. Quantitative markers can assist in screening for celiac disease and localize extent and degree of pathology throughout the small intestine.

  3. Operating characteristics for the design and optimisation of classification systems

    NARCIS (Netherlands)

    Landgrebe, T.C.W.

    2007-01-01

    In statistical pattern recognition, problems involve distinguishing of various concepts or classes, based on the development of classifiers/discriminators. These exploit discriminatory information existing in measurements originating from objects. A trained classifier results in a partitioning in

  4. A radiographic classification system in juvenile rheumatoid arthritis applied to the knee

    International Nuclear Information System (INIS)

    Dale, K.; Paus, A.C.; Laires, K.

    1994-01-01

    A new radiographic grading system for evaluation of juvenile rheumatoid arthritis (JRA) for the knee is presented. The classification is based on known arthritic criteria in childhood. Joints with erosion are given a higher score than growth disturbances alone. Signs of osteoarthrosis including joint space narrowing were excluded from the classification. The femorotibial and patello-femoral joints are assessed together. Verbal definitions are used for the classification, but, regarding the erosions, standard reference films are used. The intra- and inter-observer variations of the method were low. (P < 0.01) (orig.)

  5. Artificial neural net system for interactive tissue classification with MR imaging and image segmentation

    International Nuclear Information System (INIS)

    Clarke, L.P.; Silbiger, M.; Naylor, C.; Brown, K.

    1990-01-01

    This paper reports on the development of interactive methods for MR tissue classification that permit mathematically rigorous methods for three-dimensional image segmentation and automatic organ/tumor contouring, as required for surgical and RTP planning. The authors investigate a number of image-intensity based tissue- classification methods that make no implicit assumptions on the MR parameters and hence are not limited by image data set. Similarly, we have trained artificial neural net (ANN) systems for both supervised and unsupervised tissue classification

  6. The grapevine kinome: annotation, classification and expression patterns in developmental processes and stress responses.

    Science.gov (United States)

    Zhu, Kaikai; Wang, Xiaolong; Liu, Jinyi; Tang, Jun; Cheng, Qunkang; Chen, Jin-Gui; Cheng, Zong-Ming Max

    2018-01-01

    Protein kinases (PKs) have evolved as the largest family of molecular switches that regulate protein activities associated with almost all essential cellular functions. Only a fraction of plant PKs, however, have been functionally characterized even in model plant species. In the present study, the entire grapevine kinome was identified and annotated using the most recent version of the grapevine genome. A total of 1168 PK-encoding genes were identified and classified into 20 groups and 121 families, with the RLK-Pelle group being the largest, with 872 members. The 1168 kinase genes were unevenly distributed over all 19 chromosomes, and both tandem and segmental duplications contributed to the expansion of the grapevine kinome, especially of the RLK-Pelle group. Ka/Ks values indicated that most of the tandem and segmental duplication events were under purifying selection. The grapevine kinome families exhibited different expression patterns during plant development and in response to various stress treatments, with many being coexpressed. The comprehensive annotation of grapevine kinase genes, their patterns of expression and coexpression, and the related information facilitate a more complete understanding of the roles of various grapevine kinases in growth and development, responses to abiotic stress, and evolutionary history.

  7. British athletics muscle injury classification: a reliability study for a new grading system

    International Nuclear Information System (INIS)

    Patel, A.; Chakraverty, J.; Pollock, N.; Chakraverty, R.; Suokas, A.K.; James, S.L.

    2015-01-01

    Aim: To implement and validate the newly proposed British athletics muscle injury classification in the assessment of hamstring injuries in track and field athletes and to analyse the nature and frequency of the discrepancies. Materials and methods: This was a retrospective study analysing hamstring injuries in elite British athletes using the proposed classification system. Classification of 65 hamstring injuries in 45 high-level athletes by two radiologists at two time points 4 months apart to determine interrater variability, intrarater variability, and feasibility of the classification system was undertaken. Results: Interrater Kappa values of 0.80 (95% confidence interval [CI]: 0.67–0.92; p<0.0001) for Round 1 and 0.88 (95% CI: 0.76–1.00; p<0.0001) for Round 2 of the review were observed. Percentages of agreement were 85% for Round 1 and 91% for Round 2. The intrarater Kappa value for the two reviewers were 0.76 (95% CI: 0.63–0.88; p<0.0001) and 0.65 (95% CI: 0.53–0.76; p<0.0001) and the average was 0.71 suggesting substantial overall agreement. The percentages of agreement were 82% and 72%, respectively. Conclusions: This classification system is straightforward to use and produces both reproducible and consistent results based on interrater and intrarater Kappa values with at least substantial agreement in all groups. Further work is ongoing to investigate whether individual grades within this classification system provide prognostic information and could guide clinical management. - Highlights: • This classification system is based on MRI parameters shown to have prognostic relevance. • It is simple to use, reproducible and clinically relevant which will enhance clinical practice. • Once clinicians are familiar with the classification inter & intrarater reliability will improve.

  8. Inter- and intrareader variability in the interpretation of two radiographic classification systems for juvenile rheumatoid arthritis

    International Nuclear Information System (INIS)

    Doria, Andrea S.; Castro, Claudio C. de; Sernik, Renato A.; Vitule, Luis F.; Arantes, Paula R.; Lucato, Leandro; Germano, Marco A.N.; Cerri, Giovanni G.; Kiss, Maria Helena B.; Silva, Carlos H.M.; Zerbini, Cristiano A.F.

    2003-01-01

    To evaluate the inter- and intrareader variability for interpretation of a modified Larsen's radiographic classification system for juvenile rheumatoid arthritis (JRA) focused on osteochondral lesions and a conventional Larsen's classification system, compared to a reference MR scoring system of corresponding images. Seventy-five radiographs of 60 children with JRA, performed within a short interval of time from the MR examinations, were independently evaluated by three experienced radiologists, three diagnostic imaging residents and three rheumatologists, in two separate sessions, according to the two different classification methods, blinded to the corresponding MR images. The inter- and intrareader concordance rates between the two radiographic classification systems and the MR-related radiographs were respectively poor and poor/moderate. The interobserver range of weighted kappa values for the conventional and the modified Larsen's system respectively was 0.25-0.37 vs 0.19-0.39 for radiologists, 0.25-0.37 vs 0.18-0.30 for residents and 0.19-0.51 vs 0.17-0.29 for rheumatologists. The intrareader rate ranged from 0.17-0.55 for radiologists, 0.2-0.56 for residents, and 0.14-0.59 for rheumatologists. Although the proposal of a new radiographic classification system for JRA focused on osteochondral abnormalities sounds promising, the low inter- and intrareader concordance rates with an MR-related radiographic system makes the clinical applicability of such a radiographic system less suitable. (orig.)

  9. A Preliminary Study on the Multiple Mapping Structure of Classification Systems for Heterogeneous Databases

    Directory of Open Access Journals (Sweden)

    Seok-Hyoung Lee

    2012-06-01

    Full Text Available While science and technology information service portals and heterogeneous databases produced in Korea and other countries are integrated, methods of connecting the unique classification systems applied to each database have been studied. Results of technologists' research, such as, journal articles, patent specifications, and research reports, are organically related to each other. In this case, if the most basic and meaningful classification systems are not connected, it is difficult to achieve interoperability of the information and thus not easy to implement meaningful science technology information services through information convergence. This study aims to address the aforementioned issue by analyzing mapping systems between classification systems in order to design a structure to connect a variety of classification systems used in the academic information database of the Korea Institute of Science and Technology Information, which provides science and technology information portal service. This study also aims to design a mapping system for the classification systems to be applied to actual science and technology information services and information management systems.

  10. Dynamic classification system in large-scale supervision of energy efficiency in buildings

    International Nuclear Information System (INIS)

    Kiluk, S.

    2014-01-01

    Highlights: • Rough set approximation of classification improves energy efficiency prediction. • Dynamic features of diagnostic classification allow for its precise prediction. • Indiscernibility in large population enhances identification of process features. • Diagnostic information can be refined by dynamic references to local neighbourhood. • We introduce data exploration validation based on system dynamics and uncertainty. - Abstract: Data mining and knowledge discovery applied to the billing data provide the diagnostic instruments for the evaluation of energy use in buildings connected to a district heating network. To ensure the validity of an algorithm-based classification system, the dynamic properties of a sequence of partitions for consecutive detected events were investigated. The information regarding the dynamic properties of the classification system refers to the similarities between the supervised objects and migrations that originate from the changes in the building energy use and loss similarity to their neighbourhood and thus represents the refinement of knowledge. In this study, we demonstrate that algorithm-based diagnostic knowledge has dynamic properties that can be exploited with a rough set predictor to evaluate whether the implementation of classification for supervision of energy use aligns with the dynamics of changes of district heating-supplied building properties. Moreover, we demonstrate the refinement of the current knowledge with the previous findings and we present the creation of predictive diagnostic systems based on knowledge dynamics with a satisfactory level of classification errors, even for non-stationary data

  11. Wavenumber locking and pattern formation in spatially forced systems

    International Nuclear Information System (INIS)

    Manor, Rotem; Meron, Ehud; Hagberg, Aric

    2009-01-01

    We study wavenumber locking and pattern formation resulting from weak spatially periodic one-dimensional forcing of two-dimensional systems. We consider systems that produce stationary or traveling stripe patterns when unforced and apply forcing aligned with the stripes. Forcing at close to twice the pattern wavenumber selects, stabilizes, or creates resonant stripes locked at half the forcing wavenumber. If the mismatch between the forcing and pattern wavenumber is high we find that the pattern still locks but develops a wave vector component perpendicular to the forcing direction and forms rectangular and oblique patterns. When the unforced system supports traveling waves, resonant rectangular patterns remain stationary but oblique patterns travel in a direction orthogonal to the traveling waves.

  12. Using pattern classification and nuclear forensic signatures to link UOC to source rocks and purification processes

    International Nuclear Information System (INIS)

    Marks, N.; Robel, M.; Borg, M.; Hutcheon, I.; Kristo, M.

    2014-01-01

    Nuclear forensics is a scientific discipline interfacing law enforcement, nuclear science and nonproliferation. Information on the history and on the potential origin of unknown nuclear material can be obtained through nuclear forensic analysis. Using commonly available techniques of mass spectrometry, microscopy and x-ray diffraction, we have gained insight into the processing and origin of a suite of uranium ore concentrate (UOC) samples. We have applied chemometric techniques to investigate the relationships between uranium ore deposits and UOC samples in order to identify chemical and isotopic signatures of nuclear forensic importance. We developed multivariate signatures based on elemental concentrations and isotope ratios using a database of characteristics of UOC originating throughout the world. By introducing detailed and specific information about the source rock geology for each sample, we improved our understanding of the preservation of forensic signatures in UOC. Improved characterization of sample processing and provenance allows us to begin to assess the statistical significance of different groupings of samples and identify underlying patterns. Initial results indicate the concentration of uranium in the ore body, the geochemical conditions associated with uranium emplacement, and host rock petrogenesis exert controlling influences on the impurities preserved in UOC. Specific ore processing techniques, particularly those related to In-Situ Recovery, are also reflected in UOC impurity signatures. Stable and radiogenic isotope geochemistry can be used in conjunction with rare earth element patterns and other characteristics to link UOCs to specific geologic deposits of origin. We will present a number of case studies illustrating the ways in which nuclear forensic analysis can provide insight into the ore geology and production and purification processes used to produce UOC. (author)

  13. Approaches to the classification of brands of professional football clubs in the system of sportive marketing

    OpenAIRE

    Romat, E.; Ostroverh, S.

    2014-01-01

    This article was told about methods of classification of professional football clubs in the system of sportive marketing in the total commercial conditions of the most popular kind sport, football. Also was told about importance of brand in the professional football club as an active method of increasing trade value multi-functional enterprise in the sport area, which works on business model. The criterions where proposed and also was told about essence of the classification, which is used to...

  14. Osteochondritis dissecans of the humeral capitellum: reliability of four classification systems using radiographs and computed tomography.

    Science.gov (United States)

    Claessen, Femke M A P; van den Ende, Kimberly I M; Doornberg, Job N; Guitton, Thierry G; Eygendaal, Denise; van den Bekerom, Michel P J

    2015-10-01

    The radiographic appearance of osteochondritis dissecans (OCD) of the humeral capitellum varies according to the stage of the lesion. It is important to evaluate the stage of OCD lesion carefully to guide treatment. We compared the interobserver reliability of currently used classification systems for OCD of the humeral capitellum to identify the most reliable classification system. Thirty-two musculoskeletal radiologists and orthopaedic surgeons specialized in elbow surgery from several countries evaluated anteroposterior and lateral radiographs and corresponding computed tomography (CT) scans of 22 patients to classify the stage of OCD of the humeral capitellum according to the classification systems developed by (1) Minami, (2) Berndt and Harty, (3) Ferkel and Sgaglione, and (4) Anderson on a Web-based study platform including a Digital Imaging and Communications in Medicine viewer. Magnetic resonance imaging was not evaluated as part of this study. We measured agreement among observers using the Siegel and Castellan multirater κ. All OCD classification systems, except for Berndt and Harty, which had poor agreement among observers (κ = 0.20), had fair interobserver agreement: κ was 0.27 for the Minami, 0.23 for Anderson, and 0.22 for Ferkel and Sgaglione classifications. The Minami Classification was significantly more reliable than the other classifications (P reliable for classifying different stages of OCD of the humeral capitellum. However, it is unclear whether radiographic evidence of OCD of the humeral capitellum, as categorized by the Minami Classification, guides treatment in clinical practice as a result of this fair agreement. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

  15. Terminology and classification aspects of the Bethesda System for Reporting Thyroid Cytopathology

    Directory of Open Access Journals (Sweden)

    G V Semkina

    2012-12-01

    Full Text Available The article is devoted to the relevance of Betesda System for Reporting Thyroid Cytopathology. This article summarizes recent data on the main differences and advantages of new classification system. Application of the Betesda System for Reporting Thyroid Cytopathology leads to the increased sensitivity and specificity of FNA.

  16. Global Stress Classification System for Materials Used in Solar Energy Applications

    Science.gov (United States)

    Slamova, Karolina; Schill, Christian; Herrmann, Jan; Datta, Pawan; Chih Wang, Chien

    2016-08-01

    Depending on the geographical location, the individual or combined impact of environmental stress factors and corresponding performance losses for solar applications varies significantly. Therefore, as a strategy to reduce investment risks and operating and maintenance costs, it is necessary to adapt the materials and components of solar energy systems specifically to regional environmental conditions. The project «GloBe Solar» supports this strategy by focusing on the development of a global stress classification system for materials in solar energy applications. The aim of this classification system is to assist in the identification of the individual stress conditions for every location on the earth's surface. The stress classification system could serve as a decision support tool for the industry (manufacturers, investors, lenders and project developers) and help to improve knowledge and services that can provide higher confidence to solar power systems.

  17. Applying inventory classification to a large inventory management system

    Directory of Open Access Journals (Sweden)

    Benjamin Isaac May

    2017-06-01

    Full Text Available Inventory classification aims to ensure that business-driving inventory items are efficiently managed in spite of constrained resources. There are numerous single- and multiple-criteria approaches to it. Our objective is to improve resource allocation to focus on items that can lead to high equipment availability. This concern is typical of many service industries such as military logistics, airlines, amusement parks and public works. Our study tests several inventory prioritization techniques and finds that a modified multi-criterion weighted non-linear optimization (WNO technique is a powerful approach for classifying inventory, outperforming traditional techniques of inventory prioritization such as ABC analysis in a variety of performance objectives.

  18. Classification of transportation packaging and dry spent fuel storage system components according to importance to safety

    International Nuclear Information System (INIS)

    Tyacke, M.J.; McConnell, J.W. Jr.; Ayers, A.L. Jr.; O'Connor, S.C.; Jankovich, J.P.

    1996-01-01

    The Idaho National Engineering Laboratory prepared a technical report for the Office of Nuclear Material Safety and Safeguards of the US Nuclear Regulatory Commission, entitled Classification of Transportation Packaging and Dry Spent Fuel Storage System Components According to Importance to Safety, NUREG/CR-6407. This paper provides the results of that report. It also presents the graded approach for classification of components used in transportation packagings and dry spent fuel storage systems. This approach provides a method for identifying the classification of components according to importance to safety within transportation packagings and dry spent fuel storage systems. Record retention requirements are discussed to identify the documentation necessary to validate that the individual components were fabricated in accordance with their assigned classification. A review of the existing regulations pertaining to transportation packagings and dry storage systems was performed to identify current requirements. The general types of transportation packagings and dry storage systems are identified. The methodology used in this paper is based on Regulatory Guide 7.10, Establishing Quality Assurance Programs for Packaging Used in the Transport of Radioactive Material. This paper also includes a list of generic components for each of the general types of transportation packagings and spent fuel storage systems, with a classification category assigned to each component. Several examples concerning the safety importance of components are presented

  19. Evaluation of the Waste Isolation Pilot Plant classification of systems, structures and components

    International Nuclear Information System (INIS)

    1985-07-01

    A review of the classification system for systems, structures, and components at the Waste Isolation Pilot Plant (WIPP) was performed using the WIPP Safety Analysis Report (SAR) and Bechtel document D-76-D-03 as primary source documents. The regulations of the US Nuclear Regulatory Commission (NRC) covering ''Disposal of High level Radioactive Wastes in Geologic Repositories,'' 10 CFR 60, and the regulations relevant to nuclear power plant siting and construction (10 CFR 50, 51, 100) were used as standards to evaluate the WIPP design classification system, although it is recognized that the US Department of Energy (DOE) is not required to comply with these NRC regulations in the design and construction of WIPP. The DOE General Design Criteria Manual (DOE Order 6430.1) and the Safety Analysis and Review System for AL Operation document (AL 54f81.1A) were reviewed in part. This report includes a discussion of the historical basis for nuclear power plant requirements, a review of WIPP and nuclear power plant classification bases, and a comparison of the codes and standards applicable to each quality level. Observations made during the review of the WIPP SAR are noted in the text of this reoport. The conclusions reached by this review are: WIPP classification methodology is comparable to corresponding nuclear power procedures. The classification levels assigned to WIPP systems are qualitatively the same as those assigned to nuclear power plant systems

  20. The development of the globally harmonized system (GHS) of classification and labelling of hazardous chemicals

    International Nuclear Information System (INIS)

    Winder, Chris; Azzi, Rola; Wagner, Drew

    2005-01-01

    The hazards of chemicals can be classified using classification criteria that are based on physical, chemical and ecotoxicological endpoints. These criteria may be developed be iteratively, based on scientific or regulatory processes. A number of national and international schemes have been developed over the past 50 years, and some, such as the UN Dangerous Goods system or the EC system for hazardous substances, are in widespread use. However, the unnecessarily complicated multiplicity of existing hazard classifications created much unnecessary confusion at the user level, and a recommendation was made at the 1992 Rio Earth summit to develop a globally harmonized chemical hazard classification and compatible labelling system, including material safety data sheets and easily understandable symbols, that could be used for manufacture, transport, use and disposal of chemical substances. This became the globally harmonized system for the Classification and Labelling of Chemicals (GHS). The developmental phase of the GHS is largely complete. Consistent criteria for categorising chemicals according to their toxic, physical, chemical and ecological hazards are now available. Consistent hazard communication tools such as labelling and material safety data sheets are also close to finalisation. The next phase is implementation of the GHS. The Intergovernmental Forum for Chemical Safety recommends that all countries implement the GHS as soon as possible with a view to have the system fully operational by 2008. When the GHS is in place, the world will finally have one system for classification of chemical hazards

  1. Pattern formation in reaction diffusion systems with finite geometry

    International Nuclear Information System (INIS)

    Borzi, C.; Wio, H.

    1990-04-01

    We analyze the one-component, one-dimensional, reaction-diffusion equation through a simple inverse method. We confine the system and fix the boundary conditions as to induce pattern formation. We analyze the stability of those patterns. Our goal is to get information about the reaction term out of the preknowledgment of the pattern. (author). 5 refs

  2. Analysis of Architecture Pattern Usage in Legacy System Architecture Documentation

    NARCIS (Netherlands)

    Harrison, Neil B.; Avgeriou, Paris

    2008-01-01

    Architecture patterns are an important tool in architectural design. However, while many architecture patterns have been identified, there is little in-depth understanding of their actual use in software architectures. For instance, there is no overview of how many patterns are used per system or

  3. Host Rock Classification (HRC) system for nuclear waste disposal in crystalline bedrock

    International Nuclear Information System (INIS)

    Hagros, A.

    2006-01-01

    A new rock mass classification scheme, the Host Rock Classification system (HRC-system) has been developed for evaluating the suitability of volumes of rock mass for the disposal of high-level nuclear waste in Precambrian crystalline bedrock. To support the development of the system, the requirements of host rock to be used for disposal have been studied in detail and the significance of the various rock mass properties have been examined. The HRC-system considers both the long-term safety of the repository and the constructability in the rock mass. The system is specific to the KBS-3V disposal concept and can be used only at sites that have been evaluated to be suitable at the site scale. By using the HRC-system, it is possible to identify potentially suitable volumes within the site at several different scales (repository, tunnel and canister scales). The selection of the classification parameters to be included in the HRC-system is based on an extensive study on the rock mass properties and their various influences on the long-term safety, the constructability and the layout and location of the repository. The parameters proposed for the classification at the repository scale include fracture zones, strength/stress ratio, hydraulic conductivity and the Groundwater Chemistry Index. The parameters proposed for the classification at the tunnel scale include hydraulic conductivity, Q' and fracture zones and the parameters proposed for the classification at the canister scale include hydraulic conductivity, Q', fracture zones, fracture width (aperture + filling) and fracture trace length. The parameter values will be used to determine the suitability classes for the volumes of rock to be classified. The HRC-system includes four suitability classes at the repository and tunnel scales and three suitability classes at the canister scale and the classification process is linked to several important decisions regarding the location and acceptability of many components of

  4. Histology-based classification predicts pattern of recurrence and improves risk stratification in primary retroperitoneal sarcoma

    Science.gov (United States)

    Tan, Marcus C.B.; Brennan, Murray F.; Kuk, Deborah; Agaram, Narasimhan P.; Antonescu, Cristina; Qin, Li-Xuan; Moraco, Nicole; Crago, Aimee M.; Singer, Samuel

    2015-01-01

    Objective To determine the prognostic significance of histologic type/subtype in a large series of patients with primary resected retroperitoneal sarcoma. Summary Background Data The histologic diversity and rarity of retroperitoneal sarcoma has hampered the ability to predict patient outcome. Methods From a single-institution, prospective database, 675 patients treated surgically for primary, non-metastatic retroperitoneal sarcoma during 1982–2010 were identified and histologic type/subtype was reviewed. Clinicopathologic variables were analyzed for association with disease-specific death (DSD), local recurrence (LR), and distant recurrence (DR). Results Median follow-up for survivors was 7.5 years. The predominant histologies were well-differentiated liposarcoma, dedifferentiated liposarcoma, and leiomyosarcoma. Five-year cumulative incidence of DSD was 31%, and factors independently associated with DSD were R2 resection, resection of ≥3 contiguous organs, and histologic type. Five-year cumulative incidence for LR was 39% and for DR was 24%. R1 resection, age, tumor size, and histologic type were independently associated with LR; size, resection of ≥3 organs, and histologic type were independently associated with DR. Liposarcoma and leiomyosarcoma were associated with late recurrence and DSD (as long as 15 years from diagnosis). For solitary fibrous tumor, local recurrence was uncommon (sarcoma. Histology predicts the pattern and incidence of LR and DR and will aid in more accurate patient counseling and selection of patients for adjuvant therapy trials. PMID:25915910

  5. Textural Classification of Mammographic Parenchymal Patterns with the SONNET Selforganizing Neural Network

    Directory of Open Access Journals (Sweden)

    Daniel Howard

    2008-01-01

    Full Text Available In nationwide mammography screening, thousands of mammography examinations must be processed. Each consists of two standard views of each breast, and each mammogram must be visually examined by an experienced radiologist to assess it for any anomalies. The ability to detect an anomaly in mammographic texture is important to successful outcomes in mammography screening and, in this study, a large number of mammograms were digitized with a highly accurate scanner; and textural features were derived from the mammograms as input data to a SONNET selforganizing neural network. The paper discusses how SONNET was used to produce a taxonomic organization of the mammography archive in an unsupervised manner. This process is subject to certain choices of SONNET parameters, in these numerical experiments using the craniocaudal view, and typically produced O(10, for example, 39 mammogram classes, by analysis of features from O(103 mammogram images. The mammogram taxonomy captured typical subtleties to discriminate mammograms, and it is submitted that this may be exploited to aid the detection of mammographic anomalies, for example, by acting as a preprocessing stage to simplify the task for a computational detection scheme, or by ordering mammography examinations by mammogram taxonomic class prior to screening in order to encourage more successful visual examination during screening. The resulting taxonomy may help train screening radiologists and conceivably help to settle legal cases concerning a mammography screening examination because the taxonomy can reveal the frequency of mammographic patterns in a population.

  6. Classification of glutinous rice (Oryza sativa L.) starches based on X-ray diffraction pattern

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Q.; Abe, T.; Ando, H.; Sasahara, T.

    1993-07-01

    This study was carried out to analyse the cultivar variability of the X-ray diffraction pattern of glutinous rice starches. Four peaks in the X-ray diffractograms were identified, i.e. 3b, 4a, 4b and 6a. The four peaks were measured from the base line for 71 cultivars and three M{sub 3} lines which were irradiated by γ-rays at the rates of 10, 20 and 30 kr, respectively. Glutinous rice starches were classified into two types by discriminant analysis based on the values of 3b/4b, 4a/4b and 6a/4b. The X-ray diffraction type of the three cultivars did not change with the cultivation areas of different latitude, while that of eleven cultivars varied. Degree of crystallinity was estimated using the formula, (I{sub max} — I{sub i})/I{sub max} where I{sub max} is the maximum height from background intensity line among cultivars, and I{sub i} represents the four peaks. These ratios indicated that the changes in the order of crystallinity were similar to those with the water content and/or hydration and temperature for gelatinization among and/or within cultivars. (author)

  7. Improving the analysis of near-spectroscopy data with multivariate classification of hemodynamic patterns: a theoretical formulation and validation.

    Science.gov (United States)

    Gemignani, Jessica; Middell, Eike; Barbour, Randall L; Graber, Harry L; Blankertz, Benjamin

    2018-04-04

    The statistical analysis of functional near infrared spectroscopy (fNIRS) data based on the general linear model (GLM) is often made difficult by serial correlations, high inter-subject variability of the hemodynamic response, and the presence of motion artifacts. In this work we propose to extract information on the pattern of hemodynamic activations without using any a priori model for the data, by classifying the channels as 'active' or 'not active' with a multivariate classifier based on linear discriminant analysis (LDA). This work is developed in two steps. First we compared the performance of the two analyses, using a synthetic approach in which simulated hemodynamic activations were combined with either simulated or real resting-state fNIRS data. This procedure allowed for exact quantification of the classification accuracies of GLM and LDA. In the case of real resting-state data, the correlations between classification accuracy and demographic characteristics were investigated by means of a Linear Mixed Model. In the second step, to further characterize the reliability of the newly proposed analysis method, we conducted an experiment in which participants had to perform a simple motor task and data were analyzed with the LDA-based classifier as well as with the standard GLM analysis. The results of the simulation study show that the LDA-based method achieves higher classification accuracies than the GLM analysis, and that the LDA results are more uniform across different subjects and, in contrast to the accuracies achieved by the GLM analysis, have no significant correlations with any of the demographic characteristics. Findings from the real-data experiment are consistent with the results of the real-plus-simulation study, in that the GLM-analysis results show greater inter-subject variability than do the corresponding LDA results. The results obtained suggest that the outcome of GLM analysis is highly vulnerable to violations of theoretical assumptions

  8. Cellular image classification

    CERN Document Server

    Xu, Xiang; Lin, Feng

    2017-01-01

    This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical...

  9. Evaluation of Urinary Tract Dilation Classification System for Grading Postnatal Hydronephrosis.

    Science.gov (United States)

    Hodhod, Amr; Capolicchio, John-Paul; Jednak, Roman; El-Sherif, Eid; El-Doray, Abd El-Alim; El-Sherbiny, Mohamed

    2016-03-01

    We assessed the reliability and validity of the Urinary Tract Dilation classification system as a new grading system for postnatal hydronephrosis. We retrospectively reviewed charts of patients who presented with hydronephrosis from 2008 to 2013. We included patients diagnosed prenatally and those with hydronephrosis discovered incidentally during the first year of life. We excluded cases involving urinary tract infection, neurogenic bladder and chromosomal anomalies, those associated with extraurinary congenital malformations and those with followup of less than 24 months without resolution. Hydronephrosis was graded postnatally using the Society for Fetal Urology system, and then the management protocol was chosen. All units were regraded using the Urinary Tract Dilation classification system and compared to the Society for Fetal Urology system to assess reliability. Univariate and multivariate analyses were performed to assess the validity of the Urinary Tract Dilation classification system in predicting hydronephrosis resolution and surgical intervention. A total of 490 patients (730 renal units) were eligible to participate. The Urinary Tract Dilation classification system was reliable in the assessment of hydronephrosis (parallel forms 0.92). Hydronephrosis resolved in 357 units (49%), and 86 units (12%) were managed by surgical intervention. The remainder of renal units demonstrated stable or improved hydronephrosis. Multivariate analysis revealed that the likelihood of surgical intervention was predicted independently by Urinary Tract Dilation classification system risk group, while Society for Fetal Urology grades were predictive of likelihood of resolution. The Urinary Tract Dilation classification system is reliable for evaluation of postnatal hydronephrosis and is valid in predicting surgical intervention. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    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

  11. Design Patterns Application in the ERP Systems Improvements

    Science.gov (United States)

    Jovičić, Bojan; Vlajić, Siniša

    Design patterns application have long been present in software engineering. The same is true for ERP systems in business software. Is it possible that ERP systems do not have a good maintenance score? We have found out that there is room for maintenance improvement and that it is possible to improve ERP systems using design patterns. We have conducted comparative analysis of ease of maintenance of the ERP systems. The results show that the average score for our questions is 64%, with most answers for ERP systems like SAP, Oracle EBS, Dynamics AX. We found that 59% of ERP system developer users are not familiar with design patterns. Based on this research, we have chosen Dynamics AX as the ERP system for examination of design patterns improvement possibilities. We used software metrics to measure improvement possibility. We found that we could increase the Conditional Complexity score 17-fold by introducing design patterns.

  12. Pattern-Oriented Reengineering of a Network System

    Directory of Open Access Journals (Sweden)

    Chung-Horng Lung

    2004-08-01

    Full Text Available Reengineering is to reorganize and modify existing systems to enhance them or to make them more maintainable. Reengineering is usually necessary as systems evolve due to changes in requirements, technologies, and/or personnel. Design patterns capture recurring structures and dynamics among software participants to facilitate reuse of successful designs. Design patterns are common and well studied in network systems. In this project, we reengineer part of a network system with some design patterns to support future evolution and performance improvement. We start with reverse engineering effort to understand the system and recover its high level architecture. Then we apply concurrent and networked design patterns to restructure the main sub-system. Those patterns include Half-Sync/Half-Async, Monitor Object, and Scoped Locking idiom. The resulting system is more maintainable and has better performance.

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

    Science.gov (United States)

    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.

  14. Optimization of Neuro-Fuzzy System Using Genetic Algorithm for Chromosome Classification

    Directory of Open Access Journals (Sweden)

    M. Sarosa

    2013-09-01

    Full Text Available Neuro-fuzzy system has been shown to provide a good performance on chromosome classification but does not offer a simple method to obtain the accurate parameter values required to yield the best recognition rate. This paper presents a neuro-fuzzy system where its parameters can be automatically adjusted using genetic algorithms. The approach combines the advantages of fuzzy logic theory, neural networks, and genetic algorithms. The structure consists of a four layer feed-forward neural network that uses a GBell membership function as the output function. The proposed methodology has been applied and tested on banded chromosome classification from the Copenhagen Chromosome Database. Simulation result showed that the proposed neuro-fuzzy system optimized by genetic algorithms offers advantages in setting the parameter values, improves the recognition rate significantly and decreases the training/testing time which makes genetic neuro-fuzzy system suitable for chromosome classification.

  15. Classification of Aeronautics System Health and Safety Documents

    Data.gov (United States)

    National Aeronautics and Space Administration — Most complex aerospace systems have many text reports on safety, maintenance, and associated issues. The Aviation Safety Reporting System (ASRS) spans several...

  16. Automated nuclear fuel rod pattern loading system

    International Nuclear Information System (INIS)

    Lambert, D.V.; Nyland, T.W.; Byers, J.W.; Haley, D.E. Jr.; Cioffi, J.V.

    1990-01-01

    This patent describes an apparatus for loading fuel rods in a desired pattern. It comprises: a carousel having a plurality of movable gondolas for stocking thereon fuel rods of known enrichments; an elongated magazine defining a matrix of elongated slots being open at their forward ends for receiving fuel rods; a workstation defining a fuel rod feed path; and a holder and indexing mechanism for movably supporting the magazine and being actuatable for moving the magazine along X-Y axes to successively align one at a time selected ones of the slots with the feed path for loading in the magazine the successive fuel rods in a desired enrichment pattern

  17. Clinical Usefulness of the VS Classification System Using Magnifying Endoscopy with Blue Laser Imaging for Early Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Yoshikazu Yoshifuku

    2017-01-01

    Full Text Available Background. Blue laser imaging (BLI enables the acquisition of more information from tumors’ surfaces compared with white light imaging. Few reports confirm the validity of magnifying endoscopy (ME with BLI (ME-BLI for early gastric cancer (EGC. We aimed to assess the detailed endoscopic findings from EGCs using ME-BLI. Methods. We enrolled 386 consecutive patients with 417 EGCs that were diagnosed using ME-BLI and resected by endoscopic submucosal dissection. Using the VS classification system, three highly experienced endoscopists (HEEs and three less experienced endoscopists (LEEs evaluated the demarcation line (DL, microsurface pattern (MSP, and microvascular pattern (MVP within the endoscopic images of EGCs obtained using ME-BLI, assigning high-confidence (HC or low-confidence (LC levels. We investigated the clinicopathological features associated with each confidence level. Results. The HEEs’ evaluations determined the presence of DL in 99%, irregular MSP in 96%, and irregular MVP in 96%, and the LEEs’ evaluations determined the presence of DL in 98%, irregular MSP in 95%, and irregular MVP in 95% of the EGCs. When DL was present, HC levels in the Helicobacter pylori- (H. pylori- eradicated group and noneradicated group were evident in 65% and 89%, a difference that was significant (p<0.001. Conclusions. In the diagnosis of EGC with ME-BLI, the VS classification system with ME-NBI can be applied, but identifying the DL after H. pylori was difficult.

  18. Reflecting on the structure of soil classification systems: insights from a proposal for integrating subsoil data into soil information systems

    Science.gov (United States)

    Dondeyne, Stefaan; Juilleret, Jérôme; Vancampenhout, Karen; Deckers, Jozef; Hissler, Christophe

    2017-04-01

    Classification of soils in both World Reference Base for soil resources (WRB) and Soil Taxonomy hinges on the identification of diagnostic horizons and characteristics. However as these features often occur within the first 100 cm, these classification systems convey little information on subsoil characteristics. An integrated knowledge of the soil, soil-to-substratum and deeper substratum continuum is required when dealing with environmental issues such as vegetation ecology, water quality or the Critical Zone in general. Therefore, we recently proposed a classification system of the subsolum complementing current soil classification systems. By reflecting on the structure of the subsoil classification system which is inspired by WRB, we aim at fostering a discussion on some potential future developments of WRB. For classifying the subsolum we define Regolite, Saprolite, Saprock and Bedrock as four Subsolum Reference Groups each corresponding to different weathering stages of the subsoil. Principal qualifiers can be used to categorize intergrades of these Subsoil Reference Groups while morphologic and lithologic characteristics can be presented with supplementary qualifiers. We argue that adopting a low hierarchical structure - akin to WRB and in contrast to a strong hierarchical structure as in Soil Taxonomy - offers the advantage of having an open classification system avoiding the need for a priori knowledge of all possible combinations which may be encountered in the field. Just as in WRB we also propose to use principal and supplementary qualifiers as a second level of classification. However, in contrast to WRB we propose to reserve the principal qualifiers for intergrades and to regroup the supplementary qualifiers into thematic categories (morphologic or lithologic). Structuring the qualifiers in this manner should facilitate the integration and handling of both soil and subsoil classification units into soil information systems and calls for paying

  19. Associations between ozone and morbidity using the Spatial Synoptic Classification system

    Directory of Open Access Journals (Sweden)

    Arora Gurmeet

    2011-05-01

    Full Text Available Abstract Background Synoptic circulation patterns (large-scale tropospheric motion systems affect air pollution and, potentially, air-pollution-morbidity associations. We evaluated the effect of synoptic circulation patterns (air masses on the association between ozone and hospital admissions for asthma and myocardial infarction (MI among adults in North Carolina. Methods Daily surface meteorology data (including precipitation, wind speed, and dew point for five selected cities in North Carolina were obtained from the U.S. EPA Air Quality System (AQS, which were in turn based on data from the National Climatic Data Center of the National Oceanic and Atmospheric Administration. We used the Spatial Synoptic Classification system to classify each day of the 9-year period from 1996 through 2004 into one of seven different air mass types: dry polar, dry moderate, dry tropical, moist polar, moist moderate, moist tropical, or transitional. Daily 24-hour maximum 1-hour ambient concentrations of ozone were obtained from the AQS. Asthma and MI hospital admissions data for the 9-year period were obtained from the North Carolina Department of Health and Human Services. Generalized linear models were used to assess the association of the hospitalizations with ozone concentrations and specific air mass types, using pollutant lags of 0 to 5 days. We examined the effect across cities on days with the same air mass type. In all models we adjusted for dew point and day-of-the-week effects related to hospital admissions. Results Ozone was associated with asthma under dry tropical (1- to 5-day lags, transitional (3- and 4-day lags, and extreme moist tropical (0-day lag air masses. Ozone was associated with MI only under the extreme moist tropical (5-day lag air masses. Conclusions Elevated ozone levels are associated with dry tropical, dry moderate, and moist tropical air masses, with the highest ozone levels being associated with the dry tropical air mass. Certain

  20. Functional Classification of Uncultured "Candidatus Caldiarchaeum subterraneum" Using the Maple System.

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    Hideto Takami

    Full Text Available In this study, the metabolic and physiological potential evaluator system based on Kyoto Encyclopedia of Genes and Genomes (KEGG functional modules was employed to establish a functional classification of archaeal species and to determine the comprehensive functions (functionome of the previously uncultivated thermophile "Candidatus Caldiarchaeum subterraneum" (Ca. C. subterraneum. A phylogenetic analysis based on the concatenated sequences of proteins common among 142 archaea and 2 bacteria, and among 137 archaea and 13 unicellular eukaryotes suggested that Ca. C. subterraneum is closely related to thaumarchaeotic species. Consistent with the results of the phylogenetic analysis, clustering and principal component analyses based on the completion ratio patterns for all KEGG modules in 79 archaeal species suggested that the overall metabolic and physiological potential of Ca. C. subterraneum is similar to that of thaumarchaeotic species. However, Ca. C. subterraneum possessed almost no genes in the modules required for nitrification and the hydroxypropionate-hydroxybutyrate cycle for carbon fixation, unlike thaumarchaeotic species. However, it possessed all genes in the modules required for central carbohydrate metabolism, such as glycolysis, pyruvate oxidation, the tricarboxylic acid (TCA cycle, and the glyoxylate cycle, as well as multiple sets of sugar and branched chain amino acid ABC transporters. These metabolic and physiological features appear to support the predominantly aerobic character of Ca. C. subterraneum, which lives in a subsurface thermophilic microbial mat community with a heterotrophic lifestyle.