WorldWideScience

Sample records for scor structural classification

  1. Validation of the Persian version of the Schizophrenia Cognition Rating Scale (SCoRS) in patients with schizophrenia.

    Science.gov (United States)

    Mazhari, Shahrzad; Ghafaree-Nejad, Ali R; Soleymani-Zade, Somayeh; Keefe, Richard S E

    2017-06-01

    The Schizophrenia Cognition Rating Scale (SCoRS) is an interview-based assessment of cognition that involves interviews with patients and informants. The SCoRS has shown good reliability, validity, and sensitivity to cognitive impairment in schizophrenia, with the advantage of brief administration and scoring time. The present study aimed to test the concurrent validity of the Persian version of the SCoRS. A group of 35 patients with schizophrenia and a group of 35 healthy controls received the Persian-SCoRS in the first session, and a standardized performance-based cognitive battery, the Brief Assessment of Cognition in Schizophrenia (BACS), in the second session.Our results indicated that the Persian version of the SCoRS was sensitive to cognitive impairment in the patients. The Persian SCoRS global rating was significantly associated with the composite score generated from the Persian version of the BACS and predicted functional outcomes as measured by Global Assessment of Functioning (GAF) and World Health Organization Quality of Life (WHO QOL). A Persian version of the SCoRS, an interview based measure of cognition that included informants, is related to cognitive performance and global functioning. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. A new approach for supply chain risk management: Mapping SCOR into Bayesian network

    Directory of Open Access Journals (Sweden)

    Mahdi Abolghasemi

    2015-01-01

    Full Text Available Purpose: Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. SCRM has a close relationship with supply chain performance. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are either qualitative or quantitative. Supply chain operation reference (SCOR is a standard model for SCP evaluation which have uncertainty in its metrics. In This paper by combining qualitative and quantitative metrics of SCOR, supply chain performance will be measured by Bayesian Networks. Design/methodology/approach: First qualitative assessment will be done by recognizing uncertain metrics of SCOR model and then by quantifying them, supply chain performance will be measured by Bayesian Networks (BNs and supply chain operations reference (SCOR in which making decision on uncertain variables will be done by predictive and diagnostic capabilities. Findings: After applying the proposed method in one of the biggest automotive companies in Iran, we identified key factors of supply chain performance based on SCOR model through predictive and diagnostic capability of Bayesian Networks. After sensitivity analysis, we find out that ‘Total cost’ and its criteria that include costs of labors, warranty, transportation and inventory have the widest range and most effect on supply chain performance. So, managers should take their importance into account for decision making. We can make decisions simply by running model in different situations. Research limitations/implications: A more precise model consisted of numerous factors but it is difficult and sometimes impossible to solve big models, if we insert all of them in a Bayesian model. We have adopted real world characteristics with our software and method abilities. On the other hand, fewer data exist for some

  3. Analysis of Business Process at PT XYZ by Using SCOR Thread Diagram

    Science.gov (United States)

    Sembiring, M. T.; Rambe, H. C.

    2017-03-01

    Supply Chain Operations Reference (SCOR) is a standard supply chain performance evaluation model which is proposed by Supply Chain Council (SCC). SCOR makes companies can analyse and evaluate their supply chain performance. SCOR has Thread Diagram which describes business process simply and systematically to help the analysis of company’s business process. This research takes place in PT XYZ that is involved in Crude Palm Oil (CPO) industry. PT XYZ used to be the market leader of CPO industry but nowadays they have a trouble to compete with new competitors. The purpose of this study is to provide the input for PT XYZ business process improvement to enhance the competitiveness of the company with the others. The result obtained shows that there are two performance metrics that are not reached. The analysis of business process shows the lack of control role of PT XYZ to supplier and customer side which is going to be the suggestion of improvement.

  4. Integrating the augmented SCOR model and the ISO 15288 life cycle model into a single logistic model

    CSIR Research Space (South Africa)

    Schmitz, Peter MU

    2010-07-01

    Full Text Available using the Supply Chain Operations Reference (SCOR) model. The SANDF indicated that the augmented SCOR model (Bean, Schmitz and Engelbrecht, 2009) should be extended into a single logistics process which should include a life-cycle perspective...

  5. Lean production in improving supply chain performance through hybrid model SCOR 11.0 - system dynamics

    Science.gov (United States)

    Saleh, Chairul; Fatcha Mubiena, Ghaida; Immawan, Taufiq; Hassan, Azmi

    2016-02-01

    Supply Chain Operation Reference (SCOR) is a method to measure supply chain serving the business process framework, performance indicators and unique technologies to support communication and collaboration among supply chain partners. The objective of this paper is to measure Supply Chain Management performance by using SCOR version 11.0 for production typology of MTS-MTO in Indonesian Batik Industry. This research combines SCOR's model and System Dynamics in order to predict the complex activities on batik industry. The hybrid SCOR-SD could identify the interaction among five attributes with the associated variables simultaneously. The results are obtained after the performance of lean production application is increased and the targets are achieved, even exceeding the target. For reliability attributes that associated with perfect order fulfilment started from 2015 to 2019 respectively are calculated as 80.06%, 103.53%, 105.58%, 93.76%, and 72.17%. Responsiveness attributes associated with the order fulfilment cycle time, respectively 122.45%, 149.10%, 159.26%, 131.53%, and 119.36%. Attributes associated with the total cost of service charge respectively 93.46%, 93.53%, 93.45%, 93.49, and 93.49%. Attributes associated with cash management assets to cash cycle time in a row were 160%, 153%, 146.3%, 150%, and 126.7%. The latter attribute is agility attributes associated with supply chain flexibility upside respectively 100%, 87.2%, 100%, 82%, and 82%.

  6. Space Technology Game Changing Development- Next Generation Life Support: Spacecraft Oxygen Recovery (SCOR)

    Science.gov (United States)

    Abney, Morgan; Barta, Daniel

    2015-01-01

    The Next Generation Life Support Spacecraft Oxygen Recovery (SCOR) project element is dedicated to developing technology that enables oxygen recovery from metabolically produced carbon dioxide in space habitats. The state-of-the-art system on the International Space Station uses Sabatier technology to recover (is) approximately 50% oxygen from carbon dioxide. The remaining oxygen required for crew respiration is supplied from Earth. For long duration manned missions beyond low-Earth orbit, resupply of oxygen becomes economically and logistically prohibitive. To mitigate these challenges, the SCOR project element is targeting development of technology to increase the recovery of oxygen to 75% or more, thereby reducing the total oxygen resupply required for future missions.

  7. Using SCOR as a Supply Chain Management Framework for Government Agency Contract Requirements

    Science.gov (United States)

    Paxton, Joseph; Tucker, Brian

    2010-01-01

    This paper will present a model that uses the Supply-Chain Operations Reference (SCOR) model as a foundation for a framework to illustrate the information needed throughout a product lifecycle to support a healthy supply chain management function and the subsequent contract requirements to enable it. It will also show where in the supply chain the information must be extracted. The ongoing case study used to exemplify the model is NASA's (National Aeronautics and Space Administration) Ares I program for human spaceflight. Effective supply chain management and contract requirements are ongoing opportunities for continuous improvement within government agencies, specifically development of systems for human spaceflight operations. Multiple reports from the Government Accountability Office (GAO) reinforce this importance. The SCOR model is a framework for describing a supply chain with process building blocks and business activities. It provides a set of metrics for measuring supply chain performance and best practices for continuously improving. This paper expands the application of the SCOR to also provide the framework for defining information needed from different levels of the supply chain and at different phases of the lifecycle. These needs can be incorporated into contracts to enable more effective supply chain management. Depending on the phase of the lifecycle, effective supply chain management will require involvement from different levels of the organization and different levels of the supply chain.

  8. Teaching Supply Chain Management Complexities: A SCOR Model Based Classroom Simulation

    Science.gov (United States)

    Webb, G. Scott; Thomas, Stephanie P.; Liao-Troth, Sara

    2014-01-01

    The SCOR (Supply Chain Operations Reference) Model Supply Chain Classroom Simulation is an in-class experiential learning activity that helps students develop a holistic understanding of the processes and challenges of supply chain management. The simulation has broader learning objectives than other supply chain related activities such as the…

  9. Adapting the SCOR model to suit the military: A South African example

    CSIR Research Space (South Africa)

    Bean, WL

    2009-09-01

    Full Text Available of military supply chains, therefore it was decided that supply chain management in conjunction with the SCOR model should be used during a logistics and supply chain improvement project for the South African National Defence Force (SANDF). Three case studies...

  10. Pengukuran Performansi Supply Chain Dengan Menggunakan Supply Chain Operation Reference (Scor) Berbasis Analytical Hierarchy Process (Ahp) Dan Objective Matrix (Omax)

    OpenAIRE

    Hanugrani, Nikita; Setyanto, Nasir Widha; Efranto, Remba Yanuar

    2013-01-01

    PT. Indonesian Tobacco merupakan salah satu Perusahaan rokok yang telah menerapkan konsep Supply Chain Management untuk mengatur proses aliran material. Selama berjalannya Supply Chain Management tersebut, Perusahaan belum pernah melakukan pengukuran terhadap performansi supply chain yang melibatkan semua pihak yang terkait. Metode yang digunakan untuk mengukur performansi supply chain adalah Supply Chain Operation Reference (SCOR). SCOR merupakan suatu model acuan proses untuk operasi supply...

  11. Pengukuran Kinerja Supply Chain Dengan Pendekatan Supply Chain Operation References (SCOR)

    OpenAIRE

    Rizki Wahyuniardi; Moh. Syarwani; Ryan Anggani

    2017-01-01

    PT. Brodo Ganesha Indonesia is a national company engaged in manufacturing with the production of leather shoes. The company has many stakeholders and it is difficult to manage its supply chain, thereby affecting the effectiveness and efficiency of the company's supply chains. The research was conducted to measure the performance of supply chain by using Supply Chain Operation References (SCOR) approach. The initial hierarchy model of performance measurement is tailored to the company's condi...

  12. SCOR based key success factors in cooking oil supply chain buyers perspective in Padang City

    Science.gov (United States)

    Zahara, Fatimah; Hadiguna, Rika Ampuh

    2017-11-01

    Supply chain of cooking oil is a network of companies from palm oil as raw material to retailers which work to create the value and deliver products into the end consumers. This paper is aimed to study key success factors based on consumer's perspective as the last stage in the supply chain. Consumers who are examined in this study are restaurants management or owners. Restaurant is the biggest consumption of cooking oil. The factors is studied based on Supply Chain Operation Reference (SCOR) version 10.0. Factors used are formulated based on the third-level metrics of SCOR Model. Factors are analyzed using factors analysis. This study found factors which become key success factors in managing supply chain of cooking oil encompass reliability, responsiveness and agility. Key success factors can be applied by governments as policy making and cooking oil companies as formulation of the distribution strategies.

  13. Penilaian Implementasi Green Supply Chain Management di UKM Batik Pekalongan dengan Pendekatan GreenSCOR

    OpenAIRE

    Aries Susanty; Haryo Santosa; Fani Tania

    2017-01-01

    This article assesses the implementation level of Green Supply Chain Management (GSCM) practices in SMEs Pekalongan batik business with GreenSCOR approach and mapped out the results with an approach of importance peformance analysis (IPA). The article also devised a strategy to improve the implementation of GSCM practices. Data collection was done by distributing questionnaires and interviews. This article shows that the level of GSCM implementation in small-scale batik SMEs is in the poor ca...

  14. Object relations and interpersonal problems in sexually abused female patients: an empirical study with the SCORS and the IIP.

    Science.gov (United States)

    Kernhof, Karin; Kaufhold, Johannes; Grabhorn, Ralph

    2008-01-01

    In this study, we examined how retrospective reports of experiencing traumatic sexual abuse in childhood relates to both the development of self-representations and object representations and the occurrence of interpersonal problems. A total of 30 psychosomatic female patients who reported sexual abuse in childhood were compared with a corresponding number of eating-disordered patients and a nonclinical control group. The object relations technique (ORT; Phillipson, 1955), evaluated using the Social Cognition and Object Relations Scale (SCORS; Westen, 1985, 1991b), and the Inventory of Interpersonal Problems (Horowitz, Rosenberg, Baer, & Ureno, 1988) were used to measure the groups. The patients reporting sexual abuse achieved significantly lower scores in the cognitive scales of the SCORS; in the affective scales, they differed from the control group but not from the patients with an eating disorder. Concerning interpersonal problems, the patients reporting childhood sexual abuse reported interpersonal conflicts more frequently. The results of the study support the influence of traumatic sexual abuse on the formation of self-representations and object representations and on the occurrence of interpersonal conflicts.

  15. Pengukuran Tingkat Efektivitas Kinerja UMKM Batik Bakaran Secara Berkelanjutan Mengunakan Model Green SCOR

    Directory of Open Access Journals (Sweden)

    Daniel Alfa Puryono

    2017-09-01

    Full Text Available Usaha Mikro Kecil dan Menengah (UMKM merupakan salah satu kekuatan pendorong terdepan dalam pembangunan perekonomi di Indonesia. Agar UMKM tersebut tetap mampu bertahan dalam menghadapai tantangan sekaligus peluang yang ada, maka UMKM harus bisa meningkatkan kinerja dan kerja sama dengan sektor usaha yang lainnya. Selain itu UMKM tersebut juga harus tetap memperhatikan dampak terhadap linkgungannya. Untuk itu maka diperlukan adanya pengukuran tingkat efektivitas kinerja dalam UMKM tersebut. Supaya bisa menjadi tolak ukur maupun penetuan arah kebijakan kedepanya. Serta bisa memastikan bahwa semua faktor dalam usaha tersebut tidak menimbulkan pencemaran serta dampak sosial ekonomi bagi lingkungannya. Metode yang digunakan untuk menyelesaikan permasalahan pada penelitian ini mengunakan model Green Supply Chain Operations Refernece (Green SCOR. Model tersebut digunakan untuk menentukan kriteria serta tujuan sistem rantai pasok UMKM Batik Bakaran yang ramah lingkungan. Selain metode tersebut penelitian ini juga mengunakan metode Analitycal Hierarchy Process (AHP yang digunakan untuk menentukan Key performance Indikator (KPI yang mempengaruhi tingkat efektivitas kinerja UMKM Batik, serta dapat mengukur tingkat kinerja maupun proses kinerja dari masing masing kriteria tersebut. Sehingga akan menghasilkan tingkat efektivitas kinerja yang ramah lingkungan bagi UMKM Batik Bakaran. Model Green SCOR dan metode AHP mampu untuk menghubungkan semua kriteria kinerja yang ada. Kombinasi metode tersebut, terbukti mampu untuk memberikan penilaian tingkat efesiensi sebesar 65,4% dan profitability sebesar 34,6%. Green Supply Chain Management (GSCM merupakan kata kunci untuk meyakinkan bahwa semua faktor atau semua elemen dalam rantai pasokan memperhatikan lingkungannya atau tidak menimbulkan dampak berbahaya bagi lingkungan. Namun karena pengukuran dan penerapan GSCM yang begitu kompleks jadi tidak semua kriteria dapat diidentifikasi dan di hubungkan dengan

  16. Indicadores logísticos en la cadena de suministro como apoyo al modelo scor

    Directory of Open Access Journals (Sweden)

    Abdul Zuluaga Mazo

    2015-01-01

    Full Text Available Este artículo tiene como principal objetivo revisar, analizar y proponer el uso de indicadores en los diferentes procesos logísticos de la cadena de suministro, los cuales cubren desde el aprovisionamiento pasando por el almacenamiento, la producción, el servicio al cliente, entre otros. Como resultado del desarrollo de un trabajo de investigación llamado « Estrategias logísticas para el abastecimiento de las pymes del sector confección del municipio de Itagüí». Se concluye que los indicadores planteados permiten medir el desempeño de los diferentes procesos logísticos en la cadena de suministro, lo cual, se convierte en la base para control del uso de los recursos, seguimiento al cumplimiento de objetivos e identificación de oportunidades de mejoramiento. La metodología que se utilizó para definir los indicadores fue a través del análisis de bibliografía especializada y la creación de unos indicadores propios a partir de modelos de referencia estándar de algunas empresas. Adicionalmente, los indicadores que se presentan sirven de apoyo a la medición del modelo de cadena de suministro SCOR, lo cual, se convierte en un valor agregado para el ámbito académico y empresarial.Palabras clave: Cadena de Suministro, nivel de desempeño, indicador, logística, KPI’s (Indicadores  de desempeño.Logisticals indicators in the supply chain as support to scor model.This paper has as its main objective of reviewing, analyzing and propose the use of indicators in different logistics processes  in the supply chain, which range from the supply, warehouse, production, customer service, among others. As a result of developing the document, supported by a previous research work called « Estrategias logísticas para el abastecimiento de las pymes del sector confección del municipio de Itagüí». We obtain indicators to measure the performance of the different logistics process in the supply chain, which becomes the basis to control the

  17. Aplicación del modelo scor para el servicio de limpieza de contenedores tanque (iso tanks)

    OpenAIRE

    Fontalvo-Herrera, Tomás J; Cardona-Rojas, Daimer; Morelos Gómez, José

    2014-01-01

    En este artículo de investigación se propone una estructura soportada en el modelo SCOR para los procesos ejecutados por un operador logístico en las transacciones internacionales en Cartagena- Colombia. Se pretende analizar la cadena de suministro del servicio de limpieza y mantenimiento de contenedores de circulación internacional tipo ISO tanque como actividad fundamental en el comercio internacional de líquidos y gases a granel se utiliza el modelo de referencia para la cadena de suminist...

  18. ANALISIS PEMBOBOTAN KEY PERFORMANCE INDICATOR (KPI DENGAN SCOR MODEL MENGGUNAKAN METODE ANALITICAL HIERARCHY PROCESS (AHP PRODUK KEJU MOZZARELLA DI CV BRAWIJAYA DAIRY INDUSTRY, JUNREJO KOTA BATU

    Directory of Open Access Journals (Sweden)

    Ariani Ariani

    2017-06-01

    Full Text Available Penelitian ini bertujuan untuk menganalisis pembobotan Key performance Indicator dengan model SCOR menggunakan metode Analitical Hierarchy Process (AHP produk keju mozzarella di CV Brawijaya Dairy Industry. Hasil penelitian di peroleh 36 Key Performance Indicator yang disesuikan dengan model SCOR yaitu plan, source, deliver, make (process, dan return. Hasil pembobotan dengan menggunakan pembobotan AHP pada hierarki tingkat 1 yang memiliki bobot tertinggi adalah make (process dengan nilai bobot 0,534. Hal ini dikarenakan perusahaan mementingkan kualitas produk yang dipengaruhi oleh proses produksi. Pada hierarki tingkat 2 bobot tertinggi terdapat pada variabel reliability dengan total bobot 0,739. Sedangkan nilai bobot tertinggi pada hierarki tingkat 3 (Key Performance Indicator  adalah pada KPI 24 Kehandalan kinerja karyawan dalam mengolah menjadi produk jadi dengan total bobot 0,180.

  19. Pengukuran Kinerja Supply Chain Dengan Pendekatan Supply Chain Operation References (SCOR

    Directory of Open Access Journals (Sweden)

    Rizki Wahyuniardi

    2017-12-01

    Full Text Available PT. Brodo Ganesha Indonesia is a national company engaged in manufacturing with the production of leather shoes. The company has many stakeholders and it is difficult to manage its supply chain, thereby affecting the effectiveness and efficiency of the company's supply chains. The research was conducted to measure the performance of supply chain by using Supply Chain Operation References (SCOR approach. The initial hierarchy model of performance measurement is tailored to the company's condition to measure its supply chain performance, while the normalization of Snorm De Boer serves to equalize the value of the matrix used as the measurement indicator. The level of importance of performance attributes is measured by weighting with subjective questionnaires. Value of performance attribute obtained reliability 19,74, responsiveness 16,91, agility 11,00; and asset management 12.26. The total performance score of 59.90. This value indicates that the performance of the supply chain is in an average position.

  20. Classifications of track structures

    International Nuclear Information System (INIS)

    Paretzke, H.G.

    1984-01-01

    When ionizing particles interact with matter they produce random topological structures of primary activations which represent the initial boundary conditions for all subsequent physical, chemical and/or biological reactions. There are two important aspects of research on such track structures, namely their experimental or theoretical determination on one hand and the quantitative classification of these complex structures which is a basic pre-requisite for the understanding of mechanisms of radiation actions. This paper deals only with the latter topic, i.e. the problems encountered in and possible approaches to quantitative ordering and grouping of these multidimensional objects by their degrees of similarity with respect to their efficiency in producing certain final radiation effects, i.e. to their ''radiation quality.'' Various attempts of taxonometric classification with respect to radiation efficiency have been made in basic and applied radiation research including macro- and microdosimetric concepts as well as track entities and stopping power based theories. In this paper no review of those well-known approaches is given but rather an outline and discussion of alternative methods new to this field of radiation research which have some very promising features and which could possibly solve at least some major classification problems

  1. Penilaian Implementasi Green Supply Chain Management di UKM Batik Pekalongan dengan Pendekatan GreenSCOR

    Directory of Open Access Journals (Sweden)

    Aries Susanty

    2017-07-01

    Full Text Available This article assesses the implementation level of Green Supply Chain Management (GSCM practices in SMEs Pekalongan batik business with GreenSCOR approach and mapped out the results with an approach of importance peformance analysis (IPA. The article also devised a strategy to improve the implementation of GSCM practices. Data collection was done by distributing questionnaires and interviews. This article shows that the level of GSCM implementation in small-scale batik SMEs is in the poor category; Whereas, the level of GSCM implementation in medium-scale batik SMEs is in the average category. The results of the mapping show that, for batik SMEs there are indicators that are in quadrant A. Preparation of strategies to improve GSCM practices in batik SME Pekalongan more focused on improving the performance of indicators of use of environmentally friendly raw materials.

  2. Structural classification and a binary structure model for superconductors

    Institute of Scientific and Technical Information of China (English)

    Dong Cheng

    2006-01-01

    Based on structural and bonding features, a new classification scheme of superconductors is proposed to classify conductors can be partitioned into two parts, a superconducting active component and a supplementary component.Partially metallic covalent bonding is found to be a common feature in all superconducting active components, and the electron states of the atoms in the active components usually make a dominant contribution to the energy band near the Fermi surface. Possible directions to explore new superconductors are discussed based on the structural classification and the binary structure model.

  3. 33 CFR 67.01-15 - Classification of structures.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Classification of structures. 67... AIDS TO NAVIGATION AIDS TO NAVIGATION ON ARTIFICIAL ISLANDS AND FIXED STRUCTURES General Requirements § 67.01-15 Classification of structures. (a) When will structures be assigned to a Class? The District...

  4. Classification of proteins: available structural space for molecular modeling.

    Science.gov (United States)

    Andreeva, Antonina

    2012-01-01

    The wealth of available protein structural data provides unprecedented opportunity to study and better understand the underlying principles of protein folding and protein structure evolution. A key to achieving this lies in the ability to analyse these data and to organize them in a coherent classification scheme. Over the past years several protein classifications have been developed that aim to group proteins based on their structural relationships. Some of these classification schemes explore the concept of structural neighbourhood (structural continuum), whereas other utilize the notion of protein evolution and thus provide a discrete rather than continuum view of protein structure space. This chapter presents a strategy for classification of proteins with known three-dimensional structure. Steps in the classification process along with basic definitions are introduced. Examples illustrating some fundamental concepts of protein folding and evolution with a special focus on the exceptions to them are presented.

  5. Protein structure: geometry, topology and classification

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, William R.; May, Alex C.W.; Brown, Nigel P.; Aszodi, Andras [Division of Mathematical Biology, National Institute for Medical Research, London (United Kingdom)

    2001-04-01

    The structural principals of proteins are reviewed and analysed from a geometric perspective with a view to revealing the underlying regularities in their construction. Computer methods for the automatic comparison and classification of these structures are then reviewed with an analysis of the statistical significance of comparing different shapes. Following an analysis of the current state of the classification of proteins, more abstract geometric and topological representations are explored, including the occurrence of knotted topologies. The review concludes with a consideration of the origin of higher-level symmetries in protein structure. (author)

  6. An approach for formalising the supply chain operations

    Science.gov (United States)

    Zdravković, Milan; Panetto, Hervé; Trajanović, Miroslav; Aubry, Alexis

    2011-11-01

    Reference models play an important role in the knowledge management of the various complex collaboration domains (such as supply chain networks). However, they often show a lack of semantic precision and, they are sometimes incomplete. In this article, we present an approach to overcome semantic inconsistencies and incompleteness of the Supply Chain Operations Reference (SCOR) model and hence improve its usefulness and expand the application domain. First, we describe a literal web ontology language (OWL) specification of SCOR concepts (and related tools) built with the intention to preserve the original approach in the classification of process reference model entities, and hence enable the effectiveness of usage in original contexts. Next, we demonstrate the system for its exploitation, in specific - tools for SCOR framework browsing and rapid supply chain process configuration. Then, we describe the SCOR-Full ontology, its relations with relevant domain ontology and show how it can be exploited for improvement of SCOR ontological framework competence. Finally, we elaborate the potential impact of the presented approach, to interoperability of systems in supply chain networks.

  7. 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

  8. 32 CFR 196.520 - Job classification and structure.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 2 2010-07-01 2010-07-01 false Job classification and structure. 196.520 Section 196.520 National Defense Department of Defense (Continued) OFFICE OF THE SECRETARY OF DEFENSE... Activities Prohibited § 196.520 Job classification and structure. A recipient shall not: (a) Classify a job...

  9. 45 CFR 2555.520 - Job classification and structure.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 4 2010-10-01 2010-10-01 false Job classification and structure. 2555.520 Section 2555.520 Public Welfare Regulations Relating to Public Welfare (Continued) CORPORATION FOR NATIONAL AND... Activities Prohibited § 2555.520 Job classification and structure. A recipient shall not: (a) Classify a job...

  10. 36 CFR 1211.520 - Job classification and structure.

    Science.gov (United States)

    2010-07-01

    ... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Job classification and structure. 1211.520 Section 1211.520 Parks, Forests, and Public Property NATIONAL ARCHIVES AND RECORDS... Activities Prohibited § 1211.520 Job classification and structure. A recipient shall not: (a) Classify a job...

  11. 45 CFR 618.520 - Job classification and structure.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 3 2010-10-01 2010-10-01 false Job classification and structure. 618.520 Section 618.520 Public Welfare Regulations Relating to Public Welfare (Continued) NATIONAL SCIENCE FOUNDATION... classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  12. 6 CFR 17.520 - Job classification and structure.

    Science.gov (United States)

    2010-01-01

    ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Job classification and structure. 17.520 Section 17.520 Domestic Security DEPARTMENT OF HOMELAND SECURITY, OFFICE OF THE SECRETARY NONDISCRIMINATION... classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  13. 43 CFR 41.520 - Job classification and structure.

    Science.gov (United States)

    2010-10-01

    ... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Job classification and structure. 41.520 Section 41.520 Public Lands: Interior Office of the Secretary of the Interior NONDISCRIMINATION ON THE... classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  14. 18 CFR 1317.520 - Job classification and structure.

    Science.gov (United States)

    2010-04-01

    ... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Job classification and structure. 1317.520 Section 1317.520 Conservation of Power and Water Resources TENNESSEE VALLEY AUTHORITY... classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  15. 24 CFR 3.520 - Job classification and structure.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Job classification and structure. 3.520 Section 3.520 Housing and Urban Development Office of the Secretary, Department of Housing and... Activities Prohibited § 3.520 Job classification and structure. A recipient shall not: (a) Classify a job as...

  16. 31 CFR 28.520 - Job classification and structure.

    Science.gov (United States)

    2010-07-01

    ... 31 Money and Finance: Treasury 1 2010-07-01 2010-07-01 false Job classification and structure. 28.520 Section 28.520 Money and Finance: Treasury Office of the Secretary of the Treasury... classification and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  17. 34 CFR 106.55 - Job classification and structure.

    Science.gov (United States)

    2010-07-01

    ... 34 Education 1 2010-07-01 2010-07-01 false Job classification and structure. 106.55 Section 106.55 Education Regulations of the Offices of the Department of Education OFFICE FOR CIVIL RIGHTS, DEPARTMENT OF... Prohibited § 106.55 Job classification and structure. A recipient shall not: (a) Classify a job as being for...

  18. Dissimilarity-based classification of anatomical tree structures

    DEFF Research Database (Denmark)

    Sørensen, Lauge; Lo, Pechin Chien Pau; Dirksen, Asger

    2011-01-01

    A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment betw...

  19. Dissimilarity-based classification of anatomical tree structures

    DEFF Research Database (Denmark)

    Sørensen, Lauge Emil Borch Laurs; Lo, Pechin Chien Pau; Dirksen, Asger

    2011-01-01

    A novel method for classification of abnormality in anatomical tree structures is presented. A tree is classified based on direct comparisons with other trees in a dissimilarity-based classification scheme. The pair-wise dissimilarity measure between two trees is based on a linear assignment...

  20. Structure-based classification and ontology in chemistry

    Directory of Open Access Journals (Sweden)

    Hastings Janna

    2012-04-01

    Full Text Available Abstract Background Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures, while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies. Results We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches. Conclusion Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational

  1. Automatic structure classification of small proteins using random forest

    Directory of Open Access Journals (Sweden)

    Hirst Jonathan D

    2010-07-01

    Full Text Available Abstract Background Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the similarity of its structural descriptors to those of a template structure with an equal number of secondary structure elements (SSEs. An initial assessment of random forest is carried out for domains consisting of three SSEs. The usability of random forest in classifying larger domains is demonstrated by applying it to domains consisting of four, five and six SSEs. Results Random forest, trained on SCOP version 1.69, achieves a predictive accuracy of up to 94% on an independent and non-overlapping test set derived from SCOP version 1.73. For classification to the SCOP Class, Fold, Super-family or Family levels, the predictive quality of the model in terms of Matthew's correlation coefficient (MCC ranged from 0.61 to 0.83. As the number of constituent SSEs increases the MCC for classification to different structural levels decreases. Conclusions The utility of random forest in classifying domains from the place-holder classes of SCOP to the true Class, Fold, Super-family or Family levels is demonstrated. Issues such as introduction of a new structural level in SCOP and the merger of singleton levels can also be addressed using random forest. A real-world scenario is mimicked by predicting the classification for those protein structures from the PDB, which are yet to be assigned to the SCOP classification hierarchy.

  2. RNA structure alignment by a unit-vector approach.

    Science.gov (United States)

    Capriotti, Emidio; Marti-Renom, Marc A

    2008-08-15

    The recent discovery of tiny RNA molecules such as microRNAs and small interfering RNA are transforming the view of RNA as a simple information transfer molecule. Similar to proteins, the native three-dimensional structure of RNA determines its biological activity. Therefore, classifying the current structural space is paramount for functionally annotating RNA molecules. The increasing numbers of RNA structures deposited in the PDB requires more accurate, automatic and benchmarked methods for RNA structure comparison. In this article, we introduce a new algorithm for RNA structure alignment based on a unit-vector approach. The algorithm has been implemented in the SARA program, which results in RNA structure pairwise alignments and their statistical significance. The SARA program has been implemented to be of general applicability even when no secondary structure can be calculated from the RNA structures. A benchmark against the ARTS program using a set of 1275 non-redundant pairwise structure alignments results in inverted approximately 6% extra alignments with at least 50% structurally superposed nucleotides and base pairs. A first attempt to perform RNA automatic functional annotation based on structure alignments indicates that SARA can correctly assign the deepest SCOR classification to >60% of the query structures. The SARA program is freely available through a World Wide Web server http://sgu.bioinfo.cipf.es/services/SARA/. Supplementary data are available at Bioinformatics online.

  3. Catchment Classification: Connecting Climate, Structure and Function

    Science.gov (United States)

    Sawicz, K. A.; Wagener, T.; Sivapalan, M.; Troch, P. A.; Carrillo, G. A.

    2010-12-01

    Hydrology does not yet possess a generally accepted catchment classification framework. Such a classification framework needs to: [1] give names to things, i.e. the main classification step, [2] permit transfer of information, i.e. regionalization of information, [3] permit development of generalizations, i.e. to develop new theory, and [4] provide a first order environmental change impact assessment, i.e., the hydrologic implications of climate, land use and land cover change. One strategy is to create a catchment classification framework based on the notion of catchment functions (partitioning, storage, and release). Results of an empirical study presented here connects climate and structure to catchment function (in the form of select hydrologic signatures), based on analyzing over 300 US catchments. Initial results indicate a wide assortment of signature relationships with properties of climate, geology, and vegetation. The uncertainty in the different regionalized signatures varies widely, and therefore there is variability in the robustness of classifying ungauged basins. This research provides insight into the controls of hydrologic behavior of a catchment, and enables a classification framework applicable to gauged and ungauged across the study domain. This study sheds light on what we can expect to achieve in mapping climate, structure and function in a top-down manner. Results of this study complement work done using a bottom-up physically-based modeling framework to generalize this approach (Carrillo et al., this session).

  4. Structure of diagnostics horizons and humus classification

    Directory of Open Access Journals (Sweden)

    Zanella A

    2008-03-01

    Full Text Available The classification of the main humus forms is generally based on the morpho-genetic characters of the A and OH diagnostic horizons. This is the case in the new European key of classification presented in Freiburg on September 2004 (Eurosoil Congress. Among the morpho-genetic characters, the soil structure covers a very important role. In this work, the structure of the diagnostic A and OH horizons has been analysed in terms of aggregation force, diameter and composition of the soil lumps (peds. In order to study the aggregation force, two disaggregating tools have been conceived and used. The diameter of the lumps has been measured by sieving the soil samples with standardised webs. Observing the samples thanks to a binocular magnifying 10X and 50X, the organic or/and mineral composition of the soil aggregates has been determined, data being investigated with ANOVA and Factorial Analysis. The article examines the argument from two points of view: crashing tools for estimating the soil structure (part 1 and the dimensions of the peds given in European key of humus forms classification (part 2. The categories of soil peds diameter and composition seem to be linked to the main humus forms. For instance, aggregates having a diamater larger than 1 mm and well amalgamate organo-mineral composition are more present in the A horizons of the Mull forms than in which of the other forms; contrary to the OH horizon of the Moder or Mor, the OH horizon of the Amphi forms shows an important percent of small organic lumps. Some propositions have been given in order to improve the European key of humus forms classification.

  5. Learning about the internal structure of categories through classification and feature inference.

    Science.gov (United States)

    Jee, Benjamin D; Wiley, Jennifer

    2014-01-01

    Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

  6. Secondary structure classification of amino-acid sequences using state-space modeling

    OpenAIRE

    Brunnert, Marcus; Krahnke, Tillmann; Urfer, Wolfgang

    2001-01-01

    The secondary structure classification of amino acid sequences can be carried out by a statistical analysis of sequence and structure data using state-space models. Aiming at this classification, a modified filter algorithm programmed in S is applied to data of three proteins. The application leads to correct classifications of two proteins even when using relatively simple estimation methods for the parameters of the state-space models. Furthermore, it has been shown that the assumed initial...

  7. Hierarchical structure for audio-video based semantic classification of sports video sequences

    Science.gov (United States)

    Kolekar, M. H.; Sengupta, S.

    2005-07-01

    A hierarchical structure for sports event classification based on audio and video content analysis is proposed in this paper. Compared to the event classifications in other games, those of cricket are very challenging and yet unexplored. We have successfully solved cricket video classification problem using a six level hierarchical structure. The first level performs event detection based on audio energy and Zero Crossing Rate (ZCR) of short-time audio signal. In the subsequent levels, we classify the events based on video features using a Hidden Markov Model implemented through Dynamic Programming (HMM-DP) using color or motion as a likelihood function. For some of the game-specific decisions, a rule-based classification is also performed. Our proposed hierarchical structure can easily be applied to any other sports. Our results are very promising and we have moved a step forward towards addressing semantic classification problems in general.

  8. 22 CFR 146.520 - Job classification and structure.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Job classification and structure. 146.520... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the... and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  9. 49 CFR 25.520 - Job classification and structure.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 1 2010-10-01 2010-10-01 false Job classification and structure. 25.520 Section... IN EDUCATION PROGRAMS OR ACTIVITIES RECEIVING FEDERAL FINANCIAL ASSISTANCE Discrimination on the... and structure. A recipient shall not: (a) Classify a job as being for males or for females; (b...

  10. A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

    Directory of Open Access Journals (Sweden)

    Huai Yu

    2016-03-01

    Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

  11. 3D complex: a structural classification of protein complexes.

    Directory of Open Access Journals (Sweden)

    Emmanuel D Levy

    2006-11-01

    Full Text Available Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes.

  12. ASH structure alignment package: Sensitivity and selectivity in domain classification

    Directory of Open Access Journals (Sweden)

    Toh Hiroyuki

    2007-04-01

    Full Text Available Abstract Background Structure alignment methods offer the possibility of measuring distant evolutionary relationships between proteins that are not visible by sequence-based analysis. However, the question of how structural differences and similarities ought to be quantified in this regard remains open. In this study we construct a training set of sequence-unique CATH and SCOP domains, from which we develop a scoring function that can reliably identify domains with the same CATH topology and SCOP fold classification. The score is implemented in the ASH structure alignment package, for which the source code and a web service are freely available from the PDBj website http://www.pdbj.org/ASH/. Results The new ASH score shows increased selectivity and sensitivity compared with values reported for several popular programs using the same test set of 4,298,905 structure pairs, yielding an area of .96 under the receiver operating characteristic (ROC curve. In addition, weak sequence homologies between similar domains are revealed that could not be detected by BLAST sequence alignment. Also, a subset of domain pairs is identified that exhibit high similarity, even though their CATH and SCOP classification differs. Finally, we show that the ranking of alignment programs based solely on geometric measures depends on the choice of the quality measure. Conclusion ASH shows high selectivity and sensitivity with regard to domain classification, an important step in defining distantly related protein sequence families. Moreover, the CPU cost per alignment is competitive with the fastest programs, making ASH a practical option for large-scale structure classification studies.

  13. Topological Classification of Crystalline Insulators through Band Structure Combinatorics

    Science.gov (United States)

    Kruthoff, Jorrit; de Boer, Jan; van Wezel, Jasper; Kane, Charles L.; Slager, Robert-Jan

    2017-10-01

    We present a method for efficiently enumerating all allowed, topologically distinct, electronic band structures within a given crystal structure in all physically relevant dimensions. The algorithm applies to crystals without time-reversal, particle-hole, chiral, or any other anticommuting or anti-unitary symmetries. The results presented match the mathematical structure underlying the topological classification of these crystals in terms of K -theory and therefore elucidate this abstract mathematical framework from a simple combinatorial perspective. Using a straightforward counting procedure, we classify all allowed topological phases of spinless particles in crystals in class A . Employing this classification, we study transitions between topological phases within class A that are driven by band inversions at high-symmetry points in the first Brillouin zone. This enables us to list all possible types of phase transitions within a given crystal structure and to identify whether or not they give rise to intermediate Weyl semimetallic phases.

  14. Werner State Structure and Entanglement Classification

    Directory of Open Access Journals (Sweden)

    David W. Lyons

    2012-01-01

    Full Text Available We present applications of the representation theory of Lie groups to the analysis of structure and local unitary classification of Werner states, sometimes called the decoherence-free states, which are states of n quantum bits left unchanged by local transformations that are the same on each particle. We introduce a multiqubit generalization of the singlet state and a construction that assembles these qubits into Werner states.

  15. 41 CFR 101-4.520 - Job classification and structure.

    Science.gov (United States)

    2010-07-01

    ... 41 Public Contracts and Property Management 2 2010-07-01 2010-07-01 true Job classification and structure. 101-4.520 Section 101-4.520 Public Contracts and Property Management Federal Property Management... structure. A recipient shall not: (a) Classify a job as being for males or for females; (b) Maintain or...

  16. SCOWLP classification: Structural comparison and analysis of protein binding regions

    Directory of Open Access Journals (Sweden)

    Anders Gerd

    2008-01-01

    Full Text Available Abstract Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions

  17. 13 CFR 113.520 - Job classification and structure.

    Science.gov (United States)

    2010-01-01

    ... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Job classification and structure. 113.520 Section 113.520 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION NONDISCRIMINATION... males or for females; (b) Maintain or establish separate lines of progression, seniority lists, career...

  18. Local pulmonary structure classification for computer-aided nodule detection

    Science.gov (United States)

    Bahlmann, Claus; Li, Xianlin; Okada, Kazunori

    2006-03-01

    We propose a new method of classifying the local structure types, such as nodules, vessels, and junctions, in thoracic CT scans. This classification is important in the context of computer aided detection (CAD) of lung nodules. The proposed method can be used as a post-process component of any lung CAD system. In such a scenario, the classification results provide an effective means of removing false positives caused by vessels and junctions thus improving overall performance. As main advantage, the proposed solution transforms the complex problem of classifying various 3D topological structures into much simpler 2D data clustering problem, to which more generic and flexible solutions are available in literature, and which is better suited for visualization. Given a nodule candidate, first, our solution robustly fits an anisotropic Gaussian to the data. The resulting Gaussian center and spread parameters are used to affine-normalize the data domain so as to warp the fitted anisotropic ellipsoid into a fixed-size isotropic sphere. We propose an automatic method to extract a 3D spherical manifold, containing the appropriate bounding surface of the target structure. Scale selection is performed by a data driven entropy minimization approach. The manifold is analyzed for high intensity clusters, corresponding to protruding structures. Techniques involve EMclustering with automatic mode number estimation, directional statistics, and hierarchical clustering with a modified Bhattacharyya distance. The estimated number of high intensity clusters explicitly determines the type of pulmonary structures: nodule (0), attached nodule (1), vessel (2), junction (>3). We show accurate classification results for selected examples in thoracic CT scans. This local procedure is more flexible and efficient than current state of the art and will help to improve the accuracy of general lung CAD systems.

  19. 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

  20. The family and family structure classification redefined for the current times

    Directory of Open Access Journals (Sweden)

    Rahul Sharma

    2013-01-01

    Full Text Available The family is a basic unit of study in many medical and social science disciplines. Definitions of family have varied from country to country, and also within country. Because of this and the changing realities of the current times, there is a felt need for redefining the family and the common family structure types, for the purpose of study of the family as a factor in health and other variables of interest. A redefinition of a ′′family′′ has been proposed and various nuances of the definition are also discussed in detail. A classification scheme for the various types of family has also been put forward. A few exceptional case scenarios have been envisaged and their classification as per the new scheme is discussed, in a bid to clarify the classification scheme further. The proposed scheme should prove to be of use across various countries and cultures, for broadly classifying the family structure. The unique scenarios of particular cultures can be taken into account by defining region or culture-specific subtypes of the overall types of family structure.

  1. Classification of Farmland Landscape Structure in Multiple Scales

    Science.gov (United States)

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

    2017-12-01

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

  2. Chinese wine classification system based on micrograph using combination of shape and structure features

    Science.gov (United States)

    Wan, Yi

    2011-06-01

    Chinese wines can be classification or graded by the micrographs. Micrographs of Chinese wines show floccules, stick and granule of variant shape and size. Different wines have variant microstructure and micrographs, we study the classification of Chinese wines based on the micrographs. Shape and structure of wines' particles in microstructure is the most important feature for recognition and classification of wines. So we introduce a feature extraction method which can describe the structure and region shape of micrograph efficiently. First, the micrographs are enhanced using total variation denoising, and segmented using a modified Otsu's method based on the Rayleigh Distribution. Then features are extracted using proposed method in the paper based on area, perimeter and traditional shape feature. Eight kinds total 26 features are selected. Finally, Chinese wine classification system based on micrograph using combination of shape and structure features and BP neural network have been presented. We compare the recognition results for different choices of features (traditional shape features or proposed features). The experimental results show that the better classification rate have been achieved using the combinational features proposed in this paper.

  3. 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

  4. ERC hazard classification matrices for above ground structures and groundwater and soil remediation activities

    International Nuclear Information System (INIS)

    Curry, L.R.

    1997-01-01

    This document provides the status of the preliminary hazard classification (PHC) process for the Environmental Restoration Contractor (ERC) above ground structures and groundwater and soil remediation activities currently underway for planned for fiscal year (FY) 1997. This classification process is based on current US Department of Energy (DOE), Richland Operations Office (RL) guidance for the classification of facilities and activities containing radionuclide and nonradiological hazardous material inventories. The above ground structures presented in the matrices were drawn from the Bechtel Hanford, Inc. (BHI) Decontamination and Decommissioning (D and D) Project Facility List (DOE 1996), which identifies the facilities in the RL-Environmental Restoration baseline contract in 1997. This document contains the following two appendices: (1) Appendix A, which consists of a matrix identifying PHC documents that have been issued for BHI's above ground structures and groundwater and soil remediation activities underway or planned for FY 1997, and (2) Appendix B, which consists of a matrix showing anticipated PHCs for above ground structures, and groundwater and soil remediation activities underway or planned for FY 1997. Appendix B also shows the schedule for finalization of PHCs for above ground structures with an anticipated classification of Nuclear

  5. E-LEARNING TOOLS: STRUCTURE, CONTENT, CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Yuliya H. Loboda

    2012-05-01

    Full Text Available The article analyses the problems of organization of educational process with use of electronic means of education. Specifies the definition of "electronic learning", their structure and content. Didactic principles are considered, which are the basis of their creation and use. Given the detailed characteristics of e-learning tools for methodological purposes. On the basis of the allocated pedagogical problems of the use of electronic means of education presented and complemented by their classification, namely the means of theoretical and technological training, means of practical training, support tools, and comprehensive facilities.

  6. Protein structure database search and evolutionary classification.

    Science.gov (United States)

    Yang, Jinn-Moon; Tung, Chi-Hua

    2006-01-01

    As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].

  7. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    KAUST Repository

    Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

    2017-01-01

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  8. Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

    KAUST Repository

    Najibi, Seyed Morteza

    2017-02-08

    Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

  9. Electronic structure classifications using scanning tunneling microscopy conductance imaging

    International Nuclear Information System (INIS)

    Horn, K.M.; Swartzentruber, B.S.; Osbourn, G.C.; Bouchard, A.; Bartholomew, J.W.

    1998-01-01

    The electronic structure of atomic surfaces is imaged by applying multivariate image classification techniques to multibias conductance data measured using scanning tunneling microscopy. Image pixels are grouped into classes according to shared conductance characteristics. The image pixels, when color coded by class, produce an image that chemically distinguishes surface electronic features over the entire area of a multibias conductance image. Such open-quotes classedclose quotes images reveal surface features not always evident in a topograph. This article describes the experimental technique used to record multibias conductance images, how image pixels are grouped in a mathematical, classification space, how a computed grouping algorithm can be employed to group pixels with similar conductance characteristics in any number of dimensions, and finally how the quality of the resulting classed images can be evaluated using a computed, combinatorial analysis of the full dimensional space in which the classification is performed. copyright 1998 American Institute of Physics

  10. Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures.

    Directory of Open Access Journals (Sweden)

    Alberto Pascual-García

    2009-03-01

    Full Text Available Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications

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

    Science.gov (United States)

    Kavianpour, Hamidreza; Vasighi, Mahdi

    2017-02-01

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

  12. Aesthetics-based classification of geological structures in outcrops for geotourism purposes: a tentative proposal

    Science.gov (United States)

    Mikhailenko, Anna V.; Nazarenko, Olesya V.; Ruban, Dmitry A.; Zayats, Pavel P.

    2017-03-01

    The current growth in geotourism requires an urgent development of classifications of geological features on the basis of criteria that are relevant to tourist perceptions. It appears that structure-related patterns are especially attractive for geotourists. Consideration of the main criteria by which tourists judge beauty and observations made in the geodiversity hotspot of the Western Caucasus allow us to propose a tentative aesthetics-based classification of geological structures in outcrops, with two classes and four subclasses. It is possible to distinguish between regular and quasi-regular patterns (i.e., striped and lined and contorted patterns) and irregular and complex patterns (paysage and sculptured patterns). Typical examples of each case are found both in the study area and on a global scale. The application of the proposed classification permits to emphasise features of interest to a broad range of tourists. Aesthetics-based (i.e., non-geological) classifications are necessary to take into account visions and attitudes of visitors.

  13. Structured Literature Review of Electricity Consumption Classification Using Smart Meter Data

    Directory of Open Access Journals (Sweden)

    Alexander Martin Tureczek

    2017-04-01

    Full Text Available Smart meters for measuring electricity consumption are fast becoming prevalent in households. The meters measure consumption on a very fine scale, usually on a 15 min basis, and the data give unprecedented granularity of consumption patterns at household level. A multitude of papers have emerged utilizing smart meter data for deepening our knowledge of consumption patterns. This paper applies a modification of Okoli’s method for conducting structured literature reviews to generate an overview of research in electricity customer classification using smart meter data. The process assessed 2099 papers before identifying 34 significant papers, and highlights three key points: prominent methods, datasets and application. Three important findings are outlined. First, only a few papers contemplate future applications of the classification, rendering papers relevant only in a classification setting. Second; the encountered classification methods do not consider correlation or time series analysis when classifying. The identified papers fail to thoroughly analyze the statistical properties of the data, investigations that could potentially improve classification performance. Third, the description of the data utilized is of varying quality, with only 50% acknowledging missing values impact on the final sample size. A data description score for assessing the quality in data description has been developed and applied to all papers reviewed.

  14. Prediction of individual differences in risky behaviour in young adults via variations in local brain structure

    OpenAIRE

    Zahra eNasiriavanaki; Mohsen eArianNik; Abdolhosein eAbbassian; Abdolhosein eAbbassian; Elham eMahmoudi; Sohrab eShahzadi; Neda eRoufigari; Mohammadreza eNasiriavanaki; Bahador eBahrami

    2015-01-01

    In recent years the problem of how inter-individual differences play a role in risk-taking behaviour has become a much debated issue. We investigated this problem based on the well-known balloon analogue risk task (BART) in which participants inflate a virtual balloon opting for a higher score in the face of a riskier chance of the balloon explosion. In this study, based on a structural Voxel Based Morphometry (VBM) technique we demonstrate a significant positive correlation between BART scor...

  15. Structured Literature Review of Electricity Consumption Classification Using Smart Meter Data

    DEFF Research Database (Denmark)

    Tureczek, Alexander Martin; Nielsen, Per Sieverts

    2017-01-01

    utilizing smart meter data for deepening our knowledge of consumption patterns. This paper applies a modification of Okoli's method for conducting structured literature reviews to generate an overview of research in electricity customer classification using smart meter data. The process assessed 2099 papers...

  16. Classification of structurally related commercial contrast media by near infrared spectroscopy.

    Science.gov (United States)

    Yip, Wai Lam; Soosainather, Tom Collin; Dyrstad, Knut; Sande, Sverre Arne

    2014-03-01

    Near infrared spectroscopy (NIRS) is a non-destructive measurement technique with broad application in pharmaceutical industry. Correct identification of pharmaceutical ingredients is an important task for quality control. Failure in this step can result in several adverse consequences, varied from economic loss to negative impact on patient safety. We have compared different methods in classification of a set of commercially available structurally related contrast media, Iodixanol (Visipaque(®)), Iohexol (Omnipaque(®)), Caldiamide Sodium and Gadodiamide (Omniscan(®)), by using NIR spectroscopy. The performance of classification models developed by soft independent modelling of class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and Main and Interactions of Individual Principal Components Regression (MIPCR) were compared. Different variable selection methods were applied to optimize the classification models. Models developed by backward variable elimination partial least squares regression (BVE-PLS) and MIPCR were found to be most effective for classification of the set of contrast media. Below 1.5% of samples from the independent test set were not recognized by the BVE-PLS and MIPCR models, compared to up to 15% when models developed by other techniques were applied. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. A simple working classification proposed for the latrogenic lesions of teeth and associated structures in the oral cavity.

    Science.gov (United States)

    Shamim, Thorakkal

    2013-09-01

    Iatrogenic lesions can affect both hard and soft tissues in the oral cavity, induced by the dentist's activity, manner or therapy. There is no approved simple working classification for the iatrogenic lesions of teeth and associated structures in the oral cavity in the literature. A simple working classification is proposed here for iatrogenic lesions of teeth and associated structures in the oral cavity based on its relation with dental specialities. The dental specialities considered in this classification are conservative dentistry and endodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. This classification will be useful for the dental clinician who is dealing with diseases of oral cavity.

  18. Causal structure and algebraic classification of non-dissipative linear optical media

    International Nuclear Information System (INIS)

    Schuller, Frederic P.; Witte, Christof; Wohlfarth, Mattias N.R.

    2010-01-01

    In crystal optics and quantum electrodynamics in gravitational vacua, the propagation of light is not described by a metric, but an area metric geometry. In this article, this prompts us to study conditions for linear electrodynamics on area metric manifolds to be well-posed. This includes an identification of the timelike future cones and their duals associated to an area metric geometry, and thus paves the ground for a discussion of the related local and global causal structures in standard fashion. In order to provide simple algebraic criteria for an area metric manifold to present a consistent spacetime structure, we develop a complete algebraic classification of area metric tensors up to general transformations of frame. This classification, valuable in its own right, is then employed to prove a theorem excluding the majority of algebraic classes of area metrics as viable spacetimes. Physically, these results classify and drastically restrict the viable constitutive tensors of non-dissipative linear optical media.

  19. Automated artery-venous classification of retinal blood vessels based on structural mapping method

    Science.gov (United States)

    Joshi, Vinayak S.; Garvin, Mona K.; Reinhardt, Joseph M.; Abramoff, Michael D.

    2012-03-01

    Retinal blood vessels show morphologic modifications in response to various retinopathies. However, the specific responses exhibited by arteries and veins may provide a precise diagnostic information, i.e., a diabetic retinopathy may be detected more accurately with the venous dilatation instead of average vessel dilatation. In order to analyze the vessel type specific morphologic modifications, the classification of a vessel network into arteries and veins is required. We previously described a method for identification and separation of retinal vessel trees; i.e. structural mapping. Therefore, we propose the artery-venous classification based on structural mapping and identification of color properties prominent to the vessel types. The mean and standard deviation of each of green channel intensity and hue channel intensity are analyzed in a region of interest around each centerline pixel of a vessel. Using the vector of color properties extracted from each centerline pixel, it is classified into one of the two clusters (artery and vein), obtained by the fuzzy-C-means clustering. According to the proportion of clustered centerline pixels in a particular vessel, and utilizing the artery-venous crossing property of retinal vessels, each vessel is assigned a label of an artery or a vein. The classification results are compared with the manually annotated ground truth (gold standard). We applied the proposed method to a dataset of 15 retinal color fundus images resulting in an accuracy of 88.28% correctly classified vessel pixels. The automated classification results match well with the gold standard suggesting its potential in artery-venous classification and the respective morphology analysis.

  20. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  1. Multilabel user classification using the community structure of online networks.

    Science.gov (United States)

    Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis

    2017-01-01

    We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

  2. Multilabel user classification using the community structure of online networks.

    Directory of Open Access Journals (Sweden)

    Georgios Rizos

    Full Text Available We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE, an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

  3. 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

  4. Hierarchically structured identification and classification method for vibrational monitoring of reactor components

    International Nuclear Information System (INIS)

    Saedtler, E.

    1981-01-01

    The dissertation discusses: 1. Approximative filter algorithms for identification of systems and hierarchical structures. 2. Adaptive statistical pattern recognition and classification. 3. Parameter selection, extraction, and modelling for an automatic control system. 4. Design of a decision tree and an adaptive diagnostic system. (orig./RW) [de

  5. Structure D'Ensemble, Multiple Classification, Multiple Seriation and Amount of Irrelevant Information

    Science.gov (United States)

    Hamel, B. Remmo; Van Der Veer, M. A. A.

    1972-01-01

    A significant positive correlation between multiple classification was found, in testing 65 children aged 6 to 8 years, at the stage of concrete operations. This is interpreted as support for the existence of a structure d'ensemble of operational schemes in the period of concrete operations. (Authors)

  6. 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.

  7. Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

    Science.gov (United States)

    Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V.; Robles, Montserrat; Aparici, F.; Martí-Bonmatí, L.; García-Gómez, Juan M.

    2015-01-01

    Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation. PMID:25978453

  8. Classification of Hyperspectral Images by SVM Using a Composite Kernel by Employing Spectral, Spatial and Hierarchical Structure Information

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2018-03-01

    Full Text Available In this paper, we introduce a novel classification framework for hyperspectral images (HSIs by jointly employing spectral, spatial, and hierarchical structure information. In this framework, the three types of information are integrated into the SVM classifier in a way of multiple kernels. Specifically, the spectral kernel is constructed through each pixel’s vector value in the original HSI, and the spatial kernel is modeled by using the extended morphological profile method due to its simplicity and effectiveness. To accurately characterize hierarchical structure features, the techniques of Fish-Markov selector (FMS, marker-based hierarchical segmentation (MHSEG and algebraic multigrid (AMG are combined. First, the FMS algorithm is used on the original HSI for feature selection to produce its spectral subset. Then, the multigrid structure of this subset is constructed using the AMG method. Subsequently, the MHSEG algorithm is exploited to obtain a hierarchy consist of a series of segmentation maps. Finally, the hierarchical structure information is represented by using these segmentation maps. The main contributions of this work is to present an effective composite kernel for HSI classification by utilizing spatial structure information in multiple scales. Experiments were conducted on two hyperspectral remote sensing images to validate that the proposed framework can achieve better classification results than several popular kernel-based classification methods in terms of both qualitative and quantitative analysis. Specifically, the proposed classification framework can achieve 13.46–15.61% in average higher than the standard SVM classifier under different training sets in the terms of overall accuracy.

  9. Probability of major depression diagnostic classification using semi-structured versus fully structured diagnostic interviews.

    Science.gov (United States)

    Levis, Brooke; Benedetti, Andrea; Riehm, Kira E; Saadat, Nazanin; Levis, Alexander W; Azar, Marleine; Rice, Danielle B; Chiovitti, Matthew J; Sanchez, Tatiana A; Cuijpers, Pim; Gilbody, Simon; Ioannidis, John P A; Kloda, Lorie A; McMillan, Dean; Patten, Scott B; Shrier, Ian; Steele, Russell J; Ziegelstein, Roy C; Akena, Dickens H; Arroll, Bruce; Ayalon, Liat; Baradaran, Hamid R; Baron, Murray; Beraldi, Anna; Bombardier, Charles H; Butterworth, Peter; Carter, Gregory; Chagas, Marcos H; Chan, Juliana C N; Cholera, Rushina; Chowdhary, Neerja; Clover, Kerrie; Conwell, Yeates; de Man-van Ginkel, Janneke M; Delgadillo, Jaime; Fann, Jesse R; Fischer, Felix H; Fischler, Benjamin; Fung, Daniel; Gelaye, Bizu; Goodyear-Smith, Felicity; Greeno, Catherine G; Hall, Brian J; Hambridge, John; Harrison, Patricia A; Hegerl, Ulrich; Hides, Leanne; Hobfoll, Stevan E; Hudson, Marie; Hyphantis, Thomas; Inagaki, Masatoshi; Ismail, Khalida; Jetté, Nathalie; Khamseh, Mohammad E; Kiely, Kim M; Lamers, Femke; Liu, Shen-Ing; Lotrakul, Manote; Loureiro, Sonia R; Löwe, Bernd; Marsh, Laura; McGuire, Anthony; Mohd Sidik, Sherina; Munhoz, Tiago N; Muramatsu, Kumiko; Osório, Flávia L; Patel, Vikram; Pence, Brian W; Persoons, Philippe; Picardi, Angelo; Rooney, Alasdair G; Santos, Iná S; Shaaban, Juwita; Sidebottom, Abbey; Simning, Adam; Stafford, Lesley; Sung, Sharon; Tan, Pei Lin Lynnette; Turner, Alyna; van der Feltz-Cornelis, Christina M; van Weert, Henk C; Vöhringer, Paul A; White, Jennifer; Whooley, Mary A; Winkley, Kirsty; Yamada, Mitsuhiko; Zhang, Yuying; Thombs, Brett D

    2018-06-01

    Different diagnostic interviews are used as reference standards for major depression classification in research. Semi-structured interviews involve clinical judgement, whereas fully structured interviews are completely scripted. The Mini International Neuropsychiatric Interview (MINI), a brief fully structured interview, is also sometimes used. It is not known whether interview method is associated with probability of major depression classification.AimsTo evaluate the association between interview method and odds of major depression classification, controlling for depressive symptom scores and participant characteristics. Data collected for an individual participant data meta-analysis of Patient Health Questionnaire-9 (PHQ-9) diagnostic accuracy were analysed and binomial generalised linear mixed models were fit. A total of 17 158 participants (2287 with major depression) from 57 primary studies were analysed. Among fully structured interviews, odds of major depression were higher for the MINI compared with the Composite International Diagnostic Interview (CIDI) (odds ratio (OR) = 2.10; 95% CI = 1.15-3.87). Compared with semi-structured interviews, fully structured interviews (MINI excluded) were non-significantly more likely to classify participants with low-level depressive symptoms (PHQ-9 scores ≤6) as having major depression (OR = 3.13; 95% CI = 0.98-10.00), similarly likely for moderate-level symptoms (PHQ-9 scores 7-15) (OR = 0.96; 95% CI = 0.56-1.66) and significantly less likely for high-level symptoms (PHQ-9 scores ≥16) (OR = 0.50; 95% CI = 0.26-0.97). The MINI may identify more people as depressed than the CIDI, and semi-structured and fully structured interviews may not be interchangeable methods, but these results should be replicated.Declaration of interestDrs Jetté and Patten declare that they received a grant, outside the submitted work, from the Hotchkiss Brain Institute, which was jointly funded by the Institute and Pfizer. Pfizer was the

  10. Object Classification in Semi Structured Enviroment Using Forward-Looking Sonar

    Directory of Open Access Journals (Sweden)

    Matheus dos Santos

    2017-09-01

    Full Text Available The submarine exploration using robots has been increasing in recent years. The automation of tasks such as monitoring, inspection, and underwater maintenance requires the understanding of the robot’s environment. The object recognition in the scene is becoming a critical issue for these systems. On this work, an underwater object classification pipeline applied in acoustic images acquired by Forward-Looking Sonar (FLS are studied. The object segmentation combines thresholding, connected pixels searching and peak of intensity analyzing techniques. The object descriptor extract intensity and geometric features of the detected objects. A comparison between the Support Vector Machine, K-Nearest Neighbors, and Random Trees classifiers are presented. An open-source tool was developed to annotate and classify the objects and evaluate their classification performance. The proposed method efficiently segments and classifies the structures in the scene using a real dataset acquired by an underwater vehicle in a harbor area. Experimental results demonstrate the robustness and accuracy of the method described in this paper.

  11. Page Layout Analysis of the Document Image Based on the Region Classification in a Decision Hierarchical Structure

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2010-10-01

    Full Text Available The conversion of document image to its electronic version is a very important problem in the saving, searching and retrieval application in the official automation system. For this purpose, analysis of the document image is necessary. In this paper, a hierarchical classification structure based on a two-stage segmentation algorithm is proposed. In this structure, image is segmented using the proposed two-stage segmentation algorithm. Then, the type of the image regions such as document and non-document image is determined using multiple classifiers in the hierarchical classification structure. The proposed segmentation algorithm uses two algorithms based on wavelet transform and thresholding. Texture features such as correlation, homogeneity and entropy that extracted from co-occurrenc matrix and also two new features based on wavelet transform are used to classifiy and lable the regions of the image. The hierarchical classifier is consisted of two Multilayer Perceptron (MLP classifiers and a Support Vector Machine (SVM classifier. The proposed algorithm is evaluated on a database consisting of document and non-document images that provides from Internet. The experimental results show the efficiency of the proposed approach in the region segmentation and classification. The proposed algorithm provides accuracy rate of 97.5% on classification of the regions.

  12. 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

  13. Safety classification of systems, structures, and components for pool-type research reactors

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Tae Ryong [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2016-08-15

    Structures, systems, and components (SSCs) important to safety of nuclear facilities shall be designed, fabricated, erected, and tested to quality standards commensurate with the importance of the safety functions. Although SSC classification guidelines for nuclear power plants have been well established and applied, those for research reactors have been only recently established by the International Atomic Energy Agency (IAEA). Korea has operated a pool-type research reactor (the High Flux Advanced Neutron Application Reactor) and has recently exported another pool-type reactor (Jordan Research and Training Reactor), which is being built in Jordan. Korea also has a plan to build one more pool-type reactor, the Kijang Research Reactor, in Kijang, Busan. The safety classification of SSCs for pool-type research reactors is proposed in this paper based on the IAEA methodology. The proposal recommends that the SSCs of pool-type research reactors be categorized and classified on basis of their safety functions and safety significance. Because the SSCs in pool-type research reactors are not the pressure-retaining components, codes and standards for design of the SSCs following the safety classification can be selected in a graded approach.

  14. Functional classification of protein structures by local structure matching in graph representation.

    Science.gov (United States)

    Mills, Caitlyn L; Garg, Rohan; Lee, Joslynn S; Tian, Liang; Suciu, Alexandru; Cooperman, Gene; Beuning, Penny J; Ondrechen, Mary Jo

    2018-03-31

    As a result of high-throughput protein structure initiatives, over 14,400 protein structures have been solved by structural genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP-Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP-Func method to our previously reported method, structurally aligned local sites of activity (SALSA), using the ribulose phosphate binding barrel (RPBB), 6-hairpin glycosidase (6-HG), and Concanavalin A-like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP-Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP-Func methods to predict function. Forty-one SG proteins in the RPBB superfamily, nine SG proteins in the 6-HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. © 2018 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

  15. A broad-scale structural classification of vegetation for practical purposes

    Directory of Open Access Journals (Sweden)

    E. Edwards

    1983-11-01

    Full Text Available An a priori system is presented for the broad structural classification of vegetation. The objectives are to provide a descriptive, consistent, easily applied system, with unambiguous, straight-forward terminology, which can be used in the field and with remote sensing and air photo techniques, and which can be used in conjuction with floristic and habitat terms to convey the essential physiognomy and structure of the vegetation. The attributes used are a primary set of four growth forms, a set of four projected crown cover classes, and a set of four height classes for each growth form. In addition, shrub substratum is used to define thicket and bushland. Special growth forms, substrata!, leaf and other attributes can be readily incorporated to extend the two-way table system where such detail is needed.

  16. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

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

  17. On the classification of structures, systems and components of nuclear research and test reactors

    International Nuclear Information System (INIS)

    Mattar Neto, Miguel

    2009-01-01

    The classification of structures, systems and components of nuclear reactors is a relevant issue related to their design because it is directly associated with their safety functions. There is an important statement regarding quality standards and records that says Structures, systems, and components important to safety shall be designed, fabricated, erected, and tested to quality standards commensurate with the importance of the safety functions to be performed. The definition of the codes, standards and technical requirements applied to the nuclear reactor design, fabrication, inspection and tests may be seen as the main result from this statement. There are well established guides to classify structures, systems and components for nuclear power reactors such as the Pressurized Water Reactors but one can not say the same for nuclear research and test reactors. The nuclear reactors safety functions are those required to the safe reactor operation, the safe reactor shutdown and continued safe conditions, the response to anticipated transients, the response to potential accidents and the control of radioactive material. So, it is proposed in this paper an approach to develop the classification of structures, systems and components of these reactors based on their intended safety functions in order to define the applicable set of codes, standards and technical requirements. (author)

  18. [Landscape classification: research progress and development trend].

    Science.gov (United States)

    Liang, Fa-Chao; Liu, Li-Ming

    2011-06-01

    Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

  19. Interview-based assessment of cognition is a strong predictor of quality of life in patients with schizophrenia and severe negative symptoms

    Directory of Open Access Journals (Sweden)

    Breno F. Cruz

    2016-01-01

    Full Text Available Objective: To analyze the correlation between quality of life, symptoms, and cognition assessed by the interview-based Schizophrenia Cognition Rating Scale (SCoRS. Methods: Seventy-nine outpatients diagnosed with schizophrenia were evaluated with the Quality of Life Scale – Brazilian version (QLS-BR, the SCoRS, and symptoms scales (Positive and Negative Syndrome Scale [PANSS]. After determining the potential explanatory variables using Spearman’s correlation and Student’s t test results, we ran simple, multivariate, and decision-tree regression analyses to assess the impact of SCoRS and PANSS ratings on mean overall quality of life. Results: Cognitive deficits and negative symptoms were the best predictors of quality of life. A low degree of negative symptoms (PANSS negative < 11 was a strong predictor of better quality of life (QLS ∼ 75, regardless of SCoRS rating. Among participants with more severe negative symptoms, elevated cognitive impairment (interviewer SCoRS ∼ 44 was a predictor of worse quality of life (QLS ∼ 44. Conclusions: Cognitive impairment determined by interview-based assessment seems to be a strong predictor of quality of life in subjects with severe negative symptoms. These results support the usefulness of SCoRS for cognitive assessment that is relevant to the everyday life of patients with schizophrenia.

  20. Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

    Science.gov (United States)

    Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

    2016-01-01

    With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

  1. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

  2. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information classifi......Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information...... classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...... information and their ability to navigate the websites. The results of the study indicate group differences in user classification and related taskperformance differences. The main implications of the study are that (a) the edit distance appears a useful measure in cross-country HCI research and practice...

  3. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information classifi......Websites are increasingly used as a medium for providing information to university students. The quality of a university website depends on how well the students’ information classification fits with the structure of the information on the website. This paper investigates the information...... classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...... information and their ability to navigate the websites. The results of the study indicate group differences in user classification and related task-performance differences. The main implications of the study are that (a) the edit distance appears a useful measure in cross-country HCI research and practice...

  4. Distinguishing Adolescents With Conduct Disorder From Typically Developing Youngsters Based on Pattern Classification of Brain Structural MRI

    Directory of Open Access Journals (Sweden)

    Jianing Zhang

    2018-04-01

    Full Text Available Background: Conduct disorder (CD is a mental disorder diagnosed in childhood or adolescence that presents antisocial behaviors, and is associated with structural alterations in brain. However, whether these structural alterations can distinguish CD from healthy controls (HCs remains unknown. Here, we quantified these structural differences and explored the classification ability of these quantitative features based on machine learning (ML.Materials and Methods: High-resolution 3D structural magnetic resonance imaging (sMRI was acquired from 60 CD subjects and 60 age-matched HCs. Voxel-based morphometry (VBM was used to assess the regional gray matter (GM volume difference. The significantly different regional GM volumes were then extracted as features, and input into three ML classifiers: logistic regression, random forest and support vector machine (SVM. We trained and tested these ML models for classifying CD from HCs by using fivefold cross-validation (CV.Results: Eight brain regions with abnormal GM volumes were detected, which mainly distributed in the frontal lobe, parietal lobe, anterior cingulate, cerebellum posterior lobe, lingual gyrus, and insula areas. We found that these ML models achieved comparable classification performance, with accuracy of 77.9 ∼ 80.4%, specificity of 73.3 ∼ 80.4%, sensitivity of 75.4 ∼ 87.5%, and area under the receiver operating characteristic curve (AUC of 0.76 ∼ 0.80.Conclusion: Based on sMRI and ML, the regional GM volumes may be used as potential imaging biomarkers for stable and accurate classification of CD.

  5. Structure-Based Algorithms for Microvessel Classification

    KAUST Repository

    Smith, Amy F.

    2015-02-01

    © 2014 The Authors. Microcirculation published by John Wiley & Sons Ltd. Objective: Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods: Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results: The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions: The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries, and venules.

  6. Provision of a draft version for standard classification structure for information of radiation technologies through analyzing their information and derivation of its applicable requirements to the information system

    International Nuclear Information System (INIS)

    Jang, Sol Ah; Kim, Joo Yeon; Yoo, Ji Yup; Shin, Woo Ho; Park, Tai Jin; Song, Myung Jae

    2015-01-01

    Radiation technology is the one for developing new products or processes by applying radiation or for creating new functions in industry, research and medical fields, and its application is increasing consistently. For securing an advanced technology competitiveness, it is required to create a new added value by information consumer through providing an efficient system for supporting information, which is the infrastructure for research and development, contributed to its collection, analysis and use with a rapidity and structure in addition to some direct research and development. Provision of the management structure for information resources is especially crucial for efficient operating the system for supporting information in radiation technology, and then a standard classification structure of information must be first developed as the system for supporting information will be constructed. The standard classification structure has been analyzed by reviewing the definition of information resources in radiation technology, and those classification structures in similar systems operated by institute in radiation and other scientific fields. And, a draft version of the standard classification structure has been then provided as 7 large, 25 medium and 71 small classifications, respectively. The standard classification structure in radiation technology will be developed in 2015 through reviewing this draft version and experts' opinion. Finally, developed classification structure will be applied to the system for supporting information by considering the plan for constructing this system and database, and requirements for designing the system. Furthermore, this structure will be designed in the system for searching information by working to the individual need of information consumers

  7. Provision of a draft version for standard classification structure for information of radiation technologies through analyzing their information and derivation of its applicable requirements to the information system

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Sol Ah; Kim, Joo Yeon; Yoo, Ji Yup; Shin, Woo Ho; Park, Tai Jin; Song, Myung Jae [Korean Association for Radiation Application, Seoul (Korea, Republic of)

    2015-02-15

    Radiation technology is the one for developing new products or processes by applying radiation or for creating new functions in industry, research and medical fields, and its application is increasing consistently. For securing an advanced technology competitiveness, it is required to create a new added value by information consumer through providing an efficient system for supporting information, which is the infrastructure for research and development, contributed to its collection, analysis and use with a rapidity and structure in addition to some direct research and development. Provision of the management structure for information resources is especially crucial for efficient operating the system for supporting information in radiation technology, and then a standard classification structure of information must be first developed as the system for supporting information will be constructed. The standard classification structure has been analyzed by reviewing the definition of information resources in radiation technology, and those classification structures in similar systems operated by institute in radiation and other scientific fields. And, a draft version of the standard classification structure has been then provided as 7 large, 25 medium and 71 small classifications, respectively. The standard classification structure in radiation technology will be developed in 2015 through reviewing this draft version and experts' opinion. Finally, developed classification structure will be applied to the system for supporting information by considering the plan for constructing this system and database, and requirements for designing the system. Furthermore, this structure will be designed in the system for searching information by working to the individual need of information consumers.

  8. Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP

    Science.gov (United States)

    Jain, Sankalp; Grandits, Melanie; Richter, Lars; Ecker, Gerhard F.

    2017-06-01

    The bile salt export pump (BSEP) actively transports conjugated monovalent bile acids from the hepatocytes into the bile. This facilitates the formation of micelles and promotes digestion and absorption of dietary fat. Inhibition of BSEP leads to decreased bile flow and accumulation of cytotoxic bile salts in the liver. A number of compounds have been identified to interact with BSEP, which results in drug-induced cholestasis or liver injury. Therefore, in silico approaches for flagging compounds as potential BSEP inhibitors would be of high value in the early stage of the drug discovery pipeline. Up to now, due to the lack of a high-resolution X-ray structure of BSEP, in silico based identification of BSEP inhibitors focused on ligand-based approaches. In this study, we provide a homology model for BSEP, developed using the corrected mouse P-glycoprotein structure (PDB ID: 4M1M). Subsequently, the model was used for docking-based classification of a set of 1212 compounds (405 BSEP inhibitors, 807 non-inhibitors). Using the scoring function ChemScore, a prediction accuracy of 81% on the training set and 73% on two external test sets could be obtained. In addition, the applicability domain of the models was assessed based on Euclidean distance. Further, analysis of the protein-ligand interaction fingerprints revealed certain functional group-amino acid residue interactions that could play a key role for ligand binding. Though ligand-based models, due to their high speed and accuracy, remain the method of choice for classification of BSEP inhibitors, structure-assisted docking models demonstrate reasonably good prediction accuracies while additionally providing information about putative protein-ligand interactions.

  9. Society for Ambulatory Anesthesia

    Science.gov (United States)

    ... SAMBA Link Digital Newsletter Educational Bibliography Research IARS/Anesthesia & Analgesia SCOR About SCOR Sponsor SAMBA Meetings Affinity Sponsor Program We Represent Ambulatory and Office-Based Anesthesia The Society for Ambulatory Anesthesia provides educational opportunities, ...

  10. FACET CLASSIFICATIONS OF E-LEARNING TOOLS

    Directory of Open Access Journals (Sweden)

    Olena Yu. Balalaieva

    2013-12-01

    Full Text Available The article deals with the classification of e-learning tools based on the facet method, which suggests the separation of the parallel set of objects into independent classification groups; at the same time it is not assumed rigid classification structure and pre-built finite groups classification groups are formed by a combination of values taken from the relevant facets. An attempt to systematize the existing classification of e-learning tools from the standpoint of classification theory is made for the first time. Modern Ukrainian and foreign facet classifications of e-learning tools are described; their positive and negative features compared to classifications based on a hierarchical method are analyzed. The original author's facet classification of e-learning tools is proposed.

  11. New guidelines for dam safety classification

    International Nuclear Information System (INIS)

    Dascal, O.

    1999-01-01

    Elements are outlined of recommended new guidelines for safety classification of dams. Arguments are provided for the view that dam classification systems should require more than one system as follows: (a) classification for selection of design criteria, operation procedures and emergency measures plans, based on potential consequences of a dam failure - the hazard classification of water retaining structures; (b) classification for establishment of surveillance activities and for safety evaluation of dams, based on the probability and consequences of failure - the risk classification of water retaining structures; and (c) classification for establishment of water management plans, for safety evaluation of the entire project, for preparation of emergency measures plans, for definition of the frequency and extent of maintenance operations, and for evaluation of changes and modifications required - the hazard classification of the project. The hazard classification of the dam considers, as consequence, mainly the loss of lives or persons in jeopardy and the property damages to third parties. Difficulties in determining the risk classification of the dam lie in the fact that no tool exists to evaluate the probability of the dam's failure. To overcome this, the probability of failure can be substituted for by a set of dam characteristics that express the failure potential of the dam and its foundation. The hazard classification of the entire project is based on the probable consequences of dam failure influencing: loss of life, persons in jeopardy, property and environmental damage. The classification scheme is illustrated for dam threatening events such as earthquakes and floods. 17 refs., 5 tabs

  12. Classification of Vessels in Single-Pol COSMO-SkyMed Images Based on Statistical and Structural Features

    Directory of Open Access Journals (Sweden)

    Fan Wu

    2015-05-01

    Full Text Available Vessel monitoring is one of the most important maritime applications of Synthetic Aperture Radar (SAR data. Because of the dihedral reflections between the vessel hull and sea surface and the trihedral reflections among superstructures, vessels usually have strong backscattering in SAR images. Furthermore, in high-resolution SAR images, detailed information on vessel structures can be observed, allowing for vessel classification in high-resolution SAR images. This paper focuses on the feature analysis of merchant vessels, including bulk carriers, container ships and oil tankers, in 3 m resolution COSMO-SkyMed stripmap HIMAGE mode images and proposes a method for vessel classification. After preprocessing, a feature vector is estimated by calculating the average value of the kernel density estimation, three structural features and the mean backscattering coefficient. Support vector machine (SVM classifier is used for the vessel classification, and the results are compared with traditional methods, such as the K-nearest neighbor algorithm (K-NN and minimum distance classifier (MDC. In situ investigations are conducted during the SAR data acquisition. Corresponding Automatic Identification System (AIS reports are also obtained as ground truth to evaluate the effectiveness of the classifier. The preliminary results show that the combination of the average value of the kernel density estimation and mean backscattering coefficient has good ability for classifying the three types of vessels. When adding the three structural features, the results slightly improve. The result of the SVM classifier is better than that of K-NN and MDC. However, the SVM requires more time, when the parameters of the kernel are estimated.

  13. Classification and Compression of Multi-Resolution Vectors: A Tree Structured Vector Quantizer Approach

    Science.gov (United States)

    2002-01-01

    their expression profile and for classification of cells into tumerous and non- tumerous classes. Then we will present a parallel tree method for... cancerous cells. We will use the same dataset and use tree structured classifiers with multi-resolution analysis for classifying cancerous from non- cancerous ...cells. We have the expressions of 4096 genes from 98 different cell types. Of these 98, 72 are cancerous while 26 are non- cancerous . We are interested

  14. Il ruolo di El Escorial, V.III.6 e dei suoi discendenti nella tradizione manoscritta del Lucullus

    Directory of Open Access Journals (Sweden)

    Corinna Senore

    2017-05-01

    Full Text Available L’articolo riguarda un gruppo di sette codici che tramanda il testo del Lucullus di Cicerone e che appartiene al ramo della tradizione discendente dal manoscritto Wien, Österreichische Nationalbibliothek 189. I sette manoscritti costituiscono uno stadio della tradizione caratterizzato dalla presenza di tre lacune testuali. Sulla base di alcuni elementi paleografici e della presenza di una glossa riportata a margine del testo di uno di essi, El Escorial, V.III.6 (Scor4, e inglobata all’interno del testo degli altri sei, è possibile individuare in Scor4 il capostipite di questo gruppo della tradizione. Lo studio si occupa inoltre di fare chiarezza sui rapporti che intercorrono tra i sei discendenti di Scor4. The article focuses on a group of seven codices which carry the text of Cicero’s Lucullus. This group belongs to the branch of the tradition descending from the manuscript Wien, Österreichische Nationalbibliothek 189. The seven manuscripts represent a step of the tradition marked by the presence of some textual lacunas. I start from some paleographic elements and from the presence of a gloss on text’s margin of one of them, El Escorial, V.III.6 (Scor4. The gloss has been then incorporated in the text of the other six manuscripts and I assume that Scor4 is the founder of this group of tradition. Furthermore, this article aims to clarify the relations between the six descendants of Scor4.

  15. Scientific and General Subject Classifications in the Digital World

    CERN Document Server

    De Robbio, Antonella; Marini, A

    2001-01-01

    In the present work we discuss opportunities, problems, tools and techniques encountered when interconnecting discipline-specific subject classifications, primarily organized as search devices in bibliographic databases, with general classifications originally devised for book shelving in public libraries. We first state the fundamental distinction between topical (or subject) classifications and object classifications. Then we trace the structural limitations that have constrained subject classifications since their library origins, and the devices that were used to overcome the gap with genuine knowledge representation. After recalling some general notions on structure, dynamics and interferences of subject classifications and of the objects they refer to, we sketch a synthetic overview on discipline-specific classifications in Mathematics, Computing and Physics, on one hand, and on general classifications on the other. In this setting we present The Scientific Classifications Page, which collects groups of...

  16. Bioinformatics analyses of Shigella CRISPR structure and spacer classification.

    Science.gov (United States)

    Wang, Pengfei; Zhang, Bing; Duan, Guangcai; Wang, Yingfang; Hong, Lijuan; Wang, Linlin; Guo, Xiangjiao; Xi, Yuanlin; Yang, Haiyan

    2016-03-01

    Clustered regularly interspaced short palindromic repeats (CRISPR) are inheritable genetic elements of a variety of archaea and bacteria and indicative of the bacterial ecological adaptation, conferring acquired immunity against invading foreign nucleic acids. Shigella is an important pathogen for anthroponosis. This study aimed to analyze the features of Shigella CRISPR structure and classify the spacers through bioinformatics approach. Among 107 Shigella, 434 CRISPR structure loci were identified with two to seven loci in different strains. CRISPR-Q1, CRISPR-Q4 and CRISPR-Q5 were widely distributed in Shigella strains. Comparison of the first and last repeats of CRISPR1, CRISPR2 and CRISPR3 revealed several base variants and different stem-loop structures. A total of 259 cas genes were found among these 107 Shigella strains. The cas gene deletions were discovered in 88 strains. However, there is one strain that does not contain cas gene. Intact clusters of cas genes were found in 19 strains. From comprehensive analysis of sequence signature and BLAST and CRISPRTarget score, the 708 spacers were classified into three subtypes: Type I, Type II and Type III. Of them, Type I spacer referred to those linked with one gene segment, Type II spacer linked with two or more different gene segments, and Type III spacer undefined. This study examined the diversity of CRISPR/cas system in Shigella strains, demonstrated the main features of CRISPR structure and spacer classification, which provided critical information for elucidation of the mechanisms of spacer formation and exploration of the role the spacers play in the function of the CRISPR/cas system.

  17. Structure constrained semi-nonnegative matrix factorization for EEG-based motor imagery classification.

    Science.gov (United States)

    Lu, Na; Li, Tengfei; Pan, Jinjin; Ren, Xiaodong; Feng, Zuren; Miao, Hongyu

    2015-05-01

    Electroencephalogram (EEG) provides a non-invasive approach to measure the electrical activities of brain neurons and has long been employed for the development of brain-computer interface (BCI). For this purpose, various patterns/features of EEG data need to be extracted and associated with specific events like cue-paced motor imagery. However, this is a challenging task since EEG data are usually non-stationary time series with a low signal-to-noise ratio. In this study, we propose a novel method, called structure constrained semi-nonnegative matrix factorization (SCS-NMF), to extract the key patterns of EEG data in time domain by imposing the mean envelopes of event-related potentials (ERPs) as constraints on the semi-NMF procedure. The proposed method is applicable to general EEG time series, and the extracted temporal features by SCS-NMF can also be combined with other features in frequency domain to improve the performance of motor imagery classification. Real data experiments have been performed using the SCS-NMF approach for motor imagery classification, and the results clearly suggest the superiority of the proposed method. Comparison experiments have also been conducted. The compared methods include ICA, PCA, Semi-NMF, Wavelets, EMD and CSP, which further verified the effectivity of SCS-NMF. The SCS-NMF method could obtain better or competitive performance over the state of the art methods, which provides a novel solution for brain pattern analysis from the perspective of structure constraint. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Proposal plan of classification faceted for federal universities

    Directory of Open Access Journals (Sweden)

    Renata Santos Brandão

    2017-09-01

    Full Text Available This study aims to present a faceted classification plan for the archival management of documents in the federal universities of Brazil. For this, was done a literature review on the archival management in Brazil, the types of classification plans and the theory of the Ranganathan faceted classification, through searches in databases in the areas of Librarianship and Archivology. It was identified the classification plan used in the Federal Institutions of Higher Education to represent the functional facet and created the structural classification plan to represent the structural facet. The two classification plans were inserted into a digital repository management system to give rise to the faceted classification plan. The system used was Tainacan, free software wordpress-based used in digital document management. The developed faceted classification plan allows the user to choose and even combine the way to look for the information that guarantees agreater efficiency in the information retrieval.

  19. Computerized crystal-chemical classification of silicates and related materials with CRYSTANA and formula notation for classified structures

    International Nuclear Information System (INIS)

    Klein, Hans-Joachim; Liebau, Friedrich

    2008-01-01

    The computer program CRYSTANA is described which implements a method for the crystal-chemical classification of silicates and related materials. This method is mainly based upon the topological structure of the connected units of a compound and can be applied when the units are built from tetrahedra as coordination polyhedra. The classification parameters and the rules which have to be applied for their determination are summarized and a formalization of the method is provided based upon a finite graph representation of the units. A description of how CRYSTANA can be used and which kind of output it produces is included. From this output crystal-chemical formulas can be derived, which differ slightly from an existing notation in order to meet recommendations of the International Union of Crystallography. - The computer program CRYSTANA is described which implements a method for the crystal-chemical classification of silicates and related materials. The implementation is based upon a graph-theoretical formalization of the classification method. An extended notation of crystal-chemical formulas is introduced. The formulas can be derived from the output of the program

  20. a Point Cloud Classification Approach Based on Vertical Structures of Ground Objects

    Science.gov (United States)

    Zhao, Y.; Hu, Q.; Hu, W.

    2018-04-01

    This paper proposes a novel method for point cloud classification using vertical structural characteristics of ground objects. Since urbanization develops rapidly nowadays, urban ground objects also change frequently. Conventional photogrammetric methods cannot satisfy the requirements of updating the ground objects' information efficiently, so LiDAR (Light Detection and Ranging) technology is employed to accomplish this task. LiDAR data, namely point cloud data, can obtain detailed three-dimensional coordinates of ground objects, but this kind of data is discrete and unorganized. To accomplish ground objects classification with point cloud, we first construct horizontal grids and vertical layers to organize point cloud data, and then calculate vertical characteristics, including density and measures of dispersion, and form characteristic curves for each grids. With the help of PCA processing and K-means algorithm, we analyze the similarities and differences of characteristic curves. Curves that have similar features will be classified into the same class and point cloud correspond to these curves will be classified as well. The whole process is simple but effective, and this approach does not need assistance of other data sources. In this study, point cloud data are classified into three classes, which are vegetation, buildings, and roads. When horizontal grid spacing and vertical layer spacing are 3 m and 1 m respectively, vertical characteristic is set as density, and the number of dimensions after PCA processing is 11, the overall precision of classification result is about 86.31 %. The result can help us quickly understand the distribution of various ground objects.

  1. AcEST: DK954773 [AcEST

    Lifescience Database Archive (English)

    Full Text Available y: 436 K 438 K Sbjct: 364 K 364 >sp|Q9WJC7|POLN_EEVVM Non-structural polyprotein OS=Venezuelan equine enceph...ILFSPK 1648 >sp|Q8V294|POLN_EEVVC Non-structural polyprotein OS=Venezuelan equine encephalitis virus (strain... polyprotein OS=Venezuelan equine encephalitis virus PE=4 SV=1 Length = 2506 Scor

  2. Dimensional assessment of self- and interpersonal functioning in adolescents: implications for DSM-5's general definition of personality disorder.

    Science.gov (United States)

    DeFife, Jared A; Goldberg, Melissa; Westen, Drew

    2015-04-01

    Central to the proposed DSM-5 general definition of personality disorder (PD) are features of self- and interpersonal functioning. The Social Cognition and Object Relations Scale-Global Rating Method (SCORS-G) is a coding system that assesses eight dimensions of self- and relational experience that can be applied to narrative data or used by clinically experienced observers to quantify observations of patients in ongoing psychotherapy. This study aims to evaluate the relationship of SCORS-G dimensions to personality pathology in adolescents and their incremental validity for predicting multiple domains of adaptive functioning. A total of 294 randomly sampled doctoral-level clinical psychologists and psychiatrists described an adolescent patient in their care based on all available data. Individual SCORS-G variables demonstrated medium-to-large effect size differences for PD versus non-PD identified adolescents (d = .49-1.05). A summary SCORS-Composite rating was significantly related to composite measurements of global adaptive functioning (r = .66), school functioning (r = .47), externalizing behavior (r = -.49), and prior psychiatric history (r = -.31). The SCORS-Composite significantly predicted variance in domains of adaptive functioning above and beyond age and DSM-IV PD diagnosis (ΔR(2)s = .07-.32). As applied to adolescents, the SCORS-G offers a framework for a clinically meaningful and empirically sound dimensional assessment of self- and other representations and interpersonal functioning capacities. Our findings support the inclusion of self- and interpersonal capacities in the DSM-5 general definition of personality disorder as an improvement to existing PD diagnosis for capturing varied domains of adaptive functioning and psychopathology.

  3. Disorder-specific predictive classification of adolescents with attention deficit hyperactivity disorder (ADHD relative to autism using structural magnetic resonance imaging.

    Directory of Open Access Journals (Sweden)

    Lena Lim

    Full Text Available Attention Deficit Hyperactivity Disorder (ADHD is a neurodevelopmental disorder, but diagnosed by subjective clinical and rating measures. The study's aim was to apply Gaussian process classification (GPC to grey matter (GM volumetric data, to assess whether individual ADHD adolescents can be accurately differentiated from healthy controls based on objective, brain structure measures and whether this is disorder-specific relative to autism spectrum disorder (ASD.Twenty-nine adolescent ADHD boys and 29 age-matched healthy and 19 boys with ASD were scanned. GPC was applied to make disorder-specific predictions of ADHD diagnostic status based on individual brain structure patterns. In addition, voxel-based morphometry (VBM analysis tested for traditional univariate group level differences in GM.The pattern of GM correctly classified 75.9% of patients and 82.8% of controls, achieving an overall classification accuracy of 79.3%. Furthermore, classification was disorder-specific relative to ASD. The discriminating GM patterns showed higher classification weights for ADHD in earlier developing ventrolateral/premotor fronto-temporo-limbic and stronger classification weights for healthy controls in later developing dorsolateral fronto-striato-parieto-cerebellar networks. Several regions were also decreased in GM in ADHD relative to healthy controls in the univariate VBM analysis, suggesting they are GM deficit areas.The study provides evidence that pattern recognition analysis can provide significant individual diagnostic classification of ADHD patients and healthy controls based on distributed GM patterns with 79.3% accuracy and that this is disorder-specific relative to ASD. Findings are a promising first step towards finding an objective differential diagnostic tool based on brain imaging measures to aid with the subjective clinical diagnosis of ADHD.

  4. CLASSIFICATION OF VIRUSES

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. CLASSIFICATION OF VIRUSES. On basis of morphology. On basis of chemical composition. On basis of structure of genome. On basis of mode of replication. Notes:

  5. Radon classification of building ground

    International Nuclear Information System (INIS)

    Slunga, E.

    1988-01-01

    The Laboratories of Building Technology and Soil Mechanics and Foundation Engineering at the Helsinki University of Technology in cooperation with The Ministry of the Environment have proposed a radon classification for building ground. The proposed classification is based on the radon concentration in soil pores and on the permeability of the foundation soil. The classification includes four radon classes: negligible, normal, high and very high. Depending on the radon class the radon-technical solution for structures is chosen. It is proposed that the classification be done in general terms in connection with the site investigations for the planning of land use and in more detail in connection with the site investigations for an individual house. (author)

  6. Structural and functional perspectives on classification and seriation in psychotic and normal children.

    Science.gov (United States)

    Breslow, L; Cowan, P A

    1984-02-01

    This study describes a strategy for examining cognitive functioning in psychotic and normal children without the usual confounding effects of marked differences in cognitive structure that occur when children of the same age are compared. Participants were 14 psychotic children, 12 males and 2 females, mean age 9-2, matched with normal children at preoperational and concrete operational stage levels on a set of Piagetian classification tasks. The mean age of the normal children was 6-4, replicating the usually found developmental delay in psychotic samples. Participants were then compared on both structural level and functional abilities on a set of tasks involving seriation of sticks; the higher-level children were also administered a seriation drawing task. Analysis of children's processes of seriating and seriation drawings indicated that over and above the structural retardation, psychotic children at all levels showed functional deficits, especially in the use of anticipatory imagery. The implications for general developmental theory are that progress in structural development is not sufficient for imaginal development, and that structural development of logical concepts is relatively independent of the development of imagery. It was suggested that "thought disorder" may not be a disordered structure of thinking or a retardation in psychotic populations but rather a mismatch between higher-level logical structures and lower-level functions.

  7. Natural and human-induced hypoxia and consequences for coastal areas: synthesis and future development

    NARCIS (Netherlands)

    Zhang, J.Z.; Gilbert, D.; Gooday, A.J.; Levin, L.A.; Naqvi, S.W.A.; Middelburg, J.J.; Scranton, M.; Ekau, W.; Pena, A.; Dewitte, B.; Oguz, T.; Monteiro, P.M.S.; Urban, E.; Rabalais, N.; Ittekkot, V.; Kemp, W.M.; Ulloa, O.; Elmgren, R.; Escobar-Briones, E.; Van der Plas, A.K.

    2010-01-01

    Hypoxia has become a world-wide phenomenon in the global coastal ocean and causes a deterioration of the structure and function of ecosystems. Based on the collective contributions of members of SCOR Working Group #128, the present study provides an overview of the major aspects of coastal hypoxia

  8. Fast Gaussian kernel learning for classification tasks based on specially structured global optimization.

    Science.gov (United States)

    Zhong, Shangping; Chen, Tianshun; He, Fengying; Niu, Yuzhen

    2014-09-01

    For a practical pattern classification task solved by kernel methods, the computing time is mainly spent on kernel learning (or training). However, the current kernel learning approaches are based on local optimization techniques, and hard to have good time performances, especially for large datasets. Thus the existing algorithms cannot be easily extended to large-scale tasks. In this paper, we present a fast Gaussian kernel learning method by solving a specially structured global optimization (SSGO) problem. We optimize the Gaussian kernel function by using the formulated kernel target alignment criterion, which is a difference of increasing (d.i.) functions. Through using a power-transformation based convexification method, the objective criterion can be represented as a difference of convex (d.c.) functions with a fixed power-transformation parameter. And the objective programming problem can then be converted to a SSGO problem: globally minimizing a concave function over a convex set. The SSGO problem is classical and has good solvability. Thus, to find the global optimal solution efficiently, we can adopt the improved Hoffman's outer approximation method, which need not repeat the searching procedure with different starting points to locate the best local minimum. Also, the proposed method can be proven to converge to the global solution for any classification task. We evaluate the proposed method on twenty benchmark datasets, and compare it with four other Gaussian kernel learning methods. Experimental results show that the proposed method stably achieves both good time-efficiency performance and good classification performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. CLASSIFICATION OF POPULATION STRUCTURE FOR ALLELOPATHIC PROPERTIES IN ITCHGRASS (Rottboellia cochinchinensis

    Directory of Open Access Journals (Sweden)

    Apirat Bundit

    2014-10-01

    Full Text Available Biodiversity of Rottboellia cochinchinensis from different areas were studied by morphological traits and amplified fragment length polymorphism (AFLP analysis for classify of an allelopathic ability. The correlation of the similarity/distance between AFLP markers (Jaccard coefficient and morphological traits (Euclidean distance was significant with r = − 0.84**. Itchgrass could be divided into two groups from both UPGMA and STRUCTURE analyses: the group A consisted of itchgrass from Chaehom-Lampang, Si Thep-Phetchabun, Phrom Phiram-Phitsanulok, Amphur Muang-Nakhon Sawan, Kamalasai-Kalasin, Amphur Muang-Chachoengsao and Bang Yai-Nonthaburi, whereas itchgrass from Amphur Muang-Chiang Mai, Pak Chong-Nakhon Ratchasima and Kamphaeng Saen-Nakhon Pathom constituted the group B. Allelopathic properties of itchgrass as representative from different group were determined in bioassay test, the result showed that the aqueous extract of itchgrass from Chaehom-Lampang area has a strong allelopathic ability on growth of Echinochloa crus-galli L., Bidens pilosa L. and Lactuca sativa L. than the other group. The molecular analysis was strongly supported in morphological analysis clustering with bioassay test for allelopathic ability, specific morphological traits were soft trichomes, and the dark purple stems and roots which can be used for the preliminary classification of allelopathic ability. Our findings suggest that classification of itchgrass by morphological traits is related to the analysis of the genetic relationship of itchgrass with AFLP analysis, that allowing the assessment of the bio-diversity of itchgrass and their allelopathic potentials.

  10. NEW CLASSIFICATION OF ECOPOLICES

    Directory of Open Access Journals (Sweden)

    VOROBYOV V. V.

    2016-09-01

    Full Text Available Problem statement. Ecopolices are the newest stage of the urban planning. They have to be consideredsuchas material and energy informational structures, included to the dynamic-evolutionary matrix netsofex change processes in the ecosystems. However, there are not made the ecopolice classifications, developing on suchapproaches basis. And this determined the topicality of the article. Analysis of publications on theoretical and applied aspects of the ecopolices formation showed, that the work on them is managed mainly in the context of the latest scientific and technological achievements in the various knowledge fields. These settlements are technocratic. They are connected with the morphology of space, network structures of regional and local natural ecosystems, without independent stability, can not exist without continuous man support. Another words, they do not work in with an ecopolices idea. It is come to a head for objective, symbiotic searching of ecopolices concept with the development of their classifications. Purpose statement is to develop the objective evidence for ecopolices and to propose their new classification. Conclusion. On the base of the ecopolices classification have to lie an elements correlation idea of their general plans and men activity type according with natural mechanism of accepting, reworking and transmission of material, energy and information between geo-ecosystems, planet, man, ecopolices material part and Cosmos. New ecopolices classification should be based on the principles of multi-dimensional, time-spaced symbiotic clarity with exchange ecosystem networks. The ecopolice function with this approach comes not from the subjective anthropocentric economy but from the holistic objective of Genesis paradigm. Or, otherwise - not from the Consequence, but from the Cause.

  11. Impact of Growth in the Universe of Subjects on Classification.

    Science.gov (United States)

    Ranganathan, Shiyali Ramamritam

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

  12. Data structures and target classification; Proceedings of the Meeting, Orlando, FL, Apr. 1, 2, 1991

    Science.gov (United States)

    Libby, Vibeke

    1991-08-01

    The present conference discusses topics in multisensor fusion and signal processing, data structures in distributed environments, computational methods and architectures, and automatic target recognition. Attention is given to the adaptive selection of sensors, multisensor imagery fusion based on target motion, multisensor imaging technology for airborne surveillance, optimal topology communications networks, scanning strategies for target detection, VLSI fuzzy-logic controller design, an optical pattern recognizer, radar-based target recognition techniques, and algorithms for radar clutter statistical classification.

  13. Seismic texture classification. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Vinther, R.

    1997-12-31

    The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

  14. River and wetland classifications for freshwater conservation ...

    African Journals Online (AJOL)

    River and wetland classifications for freshwater conservation planning in KwaZulu-Natal, South Africa. ... regional- or provincial-scale conservation planning. The hierarchical structure of the classifications provides scope for finer resolution, by the addition of further levels, for application at a sub-regional or municipal scale.

  15. A Novel Texture Classification Procedure by using Association Rules

    Directory of Open Access Journals (Sweden)

    L. Jaba Sheela

    2008-11-01

    Full Text Available Texture can be defined as a local statistical pattern of texture primitives in observer’s domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules have been used in various applications during the past decades. Association rules capture both structural and statistical information, and automatically identify the structures that occur most frequently and relationships that have significant discriminative power. So, association rules can be adapted to capture frequently occurring local structures in textures. This paper describes the usage of association rules for texture classification problem. The performed experimental studies show the effectiveness of the association rules. The overall success rate is about 98%.

  16. Classification and description of world formation types

    Science.gov (United States)

    D. Faber-Langendoen; T. Keeler-Wolf; D. Meidinger; C. Josse; A. Weakley; D. Tart; G. Navarro; B. Hoagland; S. Ponomarenko; G. Fults; Eileen Helmer

    2016-01-01

    An ecological vegetation classification approach has been developed in which a combination of vegetation attributes (physiognomy, structure, and floristics) and their response to ecological and biogeographic factors are used as the basis for classifying vegetation types. This approach can help support international, national, and subnational classification efforts. The...

  17. High resolution crystal structure of PedB: a structural basis for the classification of pediocin-like immunity proteins

    Directory of Open Access Journals (Sweden)

    Cha Sun-Shin

    2007-05-01

    Full Text Available Abstract Background Pediocin-like bacteriocins, ribosomally-synthesized antimicrobial peptides, are generally coexpressed with cognate immunity proteins in order to protect the bacteriocin-producer from its own bacteriocin. As a step for understanding the mode of action of immunity proteins, we determined the crystal structure of PedB, a pediocin-like immunity protein conferring immunity to pediocin PP-1. Results The 1.6 Å crystal structure of PedB reveals that PedB consists of an antiparallel four-helix bundle with a flexible C-terminal end. PedB shows structural similarity to an immunity protein against enterocin A (EntA-im but some disparity to an immunity protein against carnobacteriocin B2 (ImB2 in both the C-terminal conformation and the local structure constructed by α3, α4, and their connecting loop. Structure-inspired mutational studies reveal that deletion of the last seven residues of the C-terminus of PedB almost abolished its immunity activity. Conclusion The fact that PedB, EntA-im, and ImB2 share a four-helix bundle structure strongly suggests the structural conservation of this motif in the pediocin-like immunity proteins. The significant difference in the core structure and the C-terminal conformation provides a structural basis for the classification of pediocin-like immunity proteins. Our mutational study using C-terminal-shortened PedBs and the investigation of primary sequence of the C-terminal region, propose that several polar or charged residues in the extreme C-terminus of PedB which is crucial for the immunity are involved in the specific recognition of pediocin PP-1.

  18. A systematic classification of Plasmodium falciparum P-loop NTPases: structural and functional correlation

    Directory of Open Access Journals (Sweden)

    Chauhan Virander S

    2009-04-01

    Full Text Available Abstract Background The P-loop NTPases constitute one of the largest groups of globular protein domains that play highly diverse functional roles in most of the organisms. Even with the availability of nearly 300 different Hidden Markov Models representing the P-loop NTPase superfamily, not many P-loop NTPases are known in Plasmodium falciparum. A number of characteristic attributes of the genome have resulted into the lack of knowledge about this functionally diverse, but important class of proteins. Method In the study, protein sequences with characteristic motifs of NTPase domain (Walker A and Walker B are computationally extracted from the P. falciparum database. A detailed secondary structure analysis, functional classification, phylogenetic and orthology studies of the NTPase domain of repertoire of 97 P. falciparum P-loop NTPases is carried out. Results Based upon distinct sequence features and secondary structure profile of the P-loop domain of obtained sequences, a cladistic classification is also conceded: nucleotide kinases and GTPases, ABC and SMC family, SF1/2 helicases, AAA+ and AAA protein families. Attempts are made to identify any ortholog(s for each of these proteins in other Plasmodium sp. as well as its vertebrate host, Homo sapiens. A number of P. falciparum P-loop NTPases that have no homologue in the host, as well as those annotated as hypothetical proteins and lack any characteristic functional domain are identified. Conclusion The study suggests a strong correlation between sequence and secondary structure profile of P-loop domains and functional roles of these proteins and thus provides an opportunity to speculate the role of many hypothetical proteins. The study provides a methodical framework for the characterization of biologically diverse NTPases in the P. falciparum genome. The efforts made in the analysis are first of its kind; and the results augment to explore the functional role of many of these proteins from

  19. 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

  20. Protist classification and the kingdoms of organisms.

    Science.gov (United States)

    Whittaker, R H; Margulis, L

    1978-04-01

    Traditional classification imposed a division into plant-like and animal-like forms on the unicellular eukaryotes, or protists; in a current view the protists are a diverse assemblage of plant-, animal- and fungus-like groups. Classification of these into phyla is difficult because of their relatively simple structure and limited geological record, but study of ultrastructure and other characteristics is providing new insight on protist classification. Possible classifications are discussed, and a summary classification of the living world into kingdoms (Monera, Protista, Fungi, Animalia, Plantae) and phyla is suggested. This classification also suggests groupings of phyla into superphyla and form-superphyla, and a broadened kingdom Protista (including green algae, oomycotes and slime molds but excluding red and brown algae). The classification thus seeks to offer a compromise between the protist and protoctist kingdoms of Whittaker and Margulis and to combine a full listing of phyla with grouping of these for synoptic treatment.

  1. Diagnosis of periodontal diseases using different classification ...

    African Journals Online (AJOL)

    The codes created for risk factors, periodontal data, and radiographically bone loss were formed as a matrix structure and regarded as inputs for the classification unit. A total of six periodontal conditions was the outputs of the classification unit. The accuracy of the suggested methods was compared according to their ...

  2. Unveiling a spinor field classification with non-Abelian gauge symmetries

    Science.gov (United States)

    Fabbri, Luca; da Rocha, Roldão

    2018-05-01

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

  3. Ligand and structure-based classification models for Prediction of P-glycoprotein inhibitors

    DEFF Research Database (Denmark)

    Klepsch, Freya; Poongavanam, Vasanthanathan; Ecker, Gerhard Franz

    2014-01-01

    an algorithm based on Euclidean distance. Results show that random forest and SVM performed best for classification of P-gp inhibitors and non-inhibitors, correctly predicting 73/75 % of the external test set compounds. Classification based on the docking experiments using the scoring function Chem...

  4. An Approach to Structure Determination and Estimation of Hierarchical Archimedean Copulas and its Application to Bayesian Classification

    Czech Academy of Sciences Publication Activity Database

    Górecki, J.; Hofert, M.; Holeňa, Martin

    2016-01-01

    Roč. 46, č. 1 (2016), s. 21-59 ISSN 0925-9902 R&D Projects: GA ČR GA13-17187S Grant - others:Slezská univerzita v Opavě(CZ) SGS/21/2014 Institutional support: RVO:67985807 Keywords : Copula * Hierarchical archimedean copula * Copula estimation * Structure determination * Kendall’s tau * Bayesian classification Subject RIV: IN - Informatics, Computer Science Impact factor: 1.294, year: 2016

  5. Multi-label literature classification based on the Gene Ontology graph

    Directory of Open Access Journals (Sweden)

    Lu Xinghua

    2008-12-01

    Full Text Available Abstract Background The Gene Ontology is a controlled vocabulary for representing knowledge related to genes and proteins in a computable form. The current effort of manually annotating proteins with the Gene Ontology is outpaced by the rate of accumulation of biomedical knowledge in literature, which urges the development of text mining approaches to facilitate the process by automatically extracting the Gene Ontology annotation from literature. The task is usually cast as a text classification problem, and contemporary methods are confronted with unbalanced training data and the difficulties associated with multi-label classification. Results In this research, we investigated the methods of enhancing automatic multi-label classification of biomedical literature by utilizing the structure of the Gene Ontology graph. We have studied three graph-based multi-label classification algorithms, including a novel stochastic algorithm and two top-down hierarchical classification methods for multi-label literature classification. We systematically evaluated and compared these graph-based classification algorithms to a conventional flat multi-label algorithm. The results indicate that, through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods can significantly improve predictions of the Gene Ontology terms implied by the analyzed text. Furthermore, the graph-based multi-label classifiers are capable of suggesting Gene Ontology annotations (to curators that are closely related to the true annotations even if they fail to predict the true ones directly. A software package implementing the studied algorithms is available for the research community. Conclusion Through utilizing the information from the structure of the Gene Ontology graph, the graph-based multi-label classification methods have better potential than the conventional flat multi-label classification approach to facilitate

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

    Science.gov (United States)

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

    2014-09-01

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

  7. Activation analysis. A basis for chemical similarity and classification

    Energy Technology Data Exchange (ETDEWEB)

    Beeck, J OP de [Ghent Rijksuniversiteit (Belgium). Instituut voor Kernwetenschappen

    1977-01-01

    It is shown that activation analysis is especially suited to serve as a basis for determining the chemical similarity between samples defined by their trace-element concentration patterns. The general problem of classification and identification is discussed. The nature of possible classification structures and their appropriate clustering strategies is considered. A practical computer method is suggested and its application as well as the graphical representation of classification results are given. The possibility for classification using information theory is mentioned. Classification of chemical elements is discussed and practically realized after Hadamard transformation of the concentration variation patterns in a series of samples.

  8. Toward mechanistic classification of enzyme functions.

    Science.gov (United States)

    Almonacid, Daniel E; Babbitt, Patricia C

    2011-06-01

    Classification of enzyme function should be quantitative, computationally accessible, and informed by sequences and structures to enable use of genomic information for functional inference and other applications. Large-scale studies have established that divergently evolved enzymes share conserved elements of structure and common mechanistic steps and that convergently evolved enzymes often converge to similar mechanisms too, suggesting that reaction mechanisms could be used to develop finer-grained functional descriptions than provided by the Enzyme Commission (EC) system currently in use. Here we describe how evolution informs these structure-function mappings and review the databases that store mechanisms of enzyme reactions along with recent developments to measure ligand and mechanistic similarities. Together, these provide a foundation for new classifications of enzyme function. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Taxonomies of Educational Objectives and Theories of Classification.

    Science.gov (United States)

    Travers, Robert M. W.

    1980-01-01

    Classification is the taxonomic science in which a system of categories is established and in which the categories have some logical structure. Scientific classifications have included those by Aristotle, Linnaeus, and Lavoisier. Educational taxonomies include those developed by Bloom, Herbart, Dewey, and Piaget. The problems of taxonomy…

  10. Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides.

    Science.gov (United States)

    Torrens, Francisco; Castellano, Gloria

    2014-06-05

    Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

  11. Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

    International Nuclear Information System (INIS)

    Kapur, G.S.; Sastry, M.I.S.; Jaiswal, A.K.; Sarpal, A.S.

    2004-01-01

    The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using 1 H and 13 C nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their 1 H NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the 'measured' and 'estimated' RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only 1 H NMR data) also showed high correlation between the 'measured' and 'estimated' RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets

  12. Classification of perovskites with supervised self-organizing maps

    International Nuclear Information System (INIS)

    Kuzmanovski, Igor; Dimitrovska-Lazova, Sandra; Aleksovska, Slobotka

    2007-01-01

    In this work supervised self-organizing maps were used for structural classification of perovskites. For this purpose, structural data for total number of 286 perovskites, belonging to ABO 3 and/or A 2 BB'O 6 types, were collected from literature: 130 of these are cubic, 85 orthorhombic and 71 monoclinic. For classification purposes, the effective ionic radii of the cations, electronegativities of the cations in B-position, as well as, the oxidation states of these cations, were used as input variables. The parameters of the developed models, as well as, the most suitable variables for classification purposes were selected using genetic algorithms. Two-third of all the compounds were used in the training phase. During the optimization process the performances of the models were checked using cross-validation leave-1/10-out. The performances of obtained solutions were checked using the test set composed of the remaining one-third of the compounds. The obtained models for classification of these three classes of perovskite compounds show very good results. Namely, the classification of the compounds in the test set resulted in small number of discrepancies (4.2-6.4%) between the actual crystallographic class and the one predicted by the models. All these results are strong arguments for the validity of supervised self-organizing maps for performing such types of classification. Therefore, the proposed procedure could be successfully used for crystallographic classification of perovskites in one of these three classes

  13. Use of the TAT in the assessment of DSM-IV cluster B personality disorders.

    Science.gov (United States)

    Ackerman, S J; Clemence, A J; Weatherill, R; Hilsenroth, M J

    1999-12-01

    The Social Cognition and Object Relations Scale (SCORS), developed by Western, Lohr, Silk, Kerber, and Goodrich (1985), is a diagnostic instrument used to assess an array of psychological functioning by using clinical narratives such as the Thematic Apperception Test (TAT; Murray, 1943) stories. This study investigated the utility of the SCORS to differentiate between Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) antisocial personality disorder (ANPD), borderline personality disorder (BPD), narcissistic personality disorder (NPD), and Cluster C personality disorder (CPD). A sample of 58 patients was separated into four groups: ANPD (n = 9), BPD (n = 21; 18 with a primary BPD diagnosis and 3 with prominent borderline traits who met 4 of the 5 DSM-IV criteria necessary for a BPD diagnosis), NPD (n = 16; 8 with a primary NPD diagnosis and 8 with prominent narcissistic traits who met 4 of the 5 DSM-IV criteria necessary for a NPD diagnosis), and CPD (n = 12). These groups were then compared on the 8 SCORS variables by using 5 TAT cards (1, 2, 3BM, 4, and 13MF). Spearman-Brown correction for 2-way mixed effects model of reliability for the 8 SCORS variables ranged from .70 to .95. The results of categorical and dimensional analyses indicate that (a) SCORS variables can be used to differentiate ANPD, BPD, and NPD; (b) the BPD group scored significantly lower (greater maladjustment) than did the CPD group on certain variables; (c) the BPD group scored significantly lower (greater maladjustment) than did the NPD group on all 8 SCORS variables; (d) the ANPD group scored significantly lower than did the NPD group on certain variables; (e) certain variables were found to be empirically related to the total number of DSM-IV ANPD, BPD, and NPD criteria; and (f) certain variables were found to be empirically related to Minnesota Multiphasic Personality Inventory-2 (MMPI-2; Butcher, Dahlstrom, Graham, Tellegen

  14. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  15. Failure diagnosis using deep belief learning based health state classification

    International Nuclear Information System (INIS)

    Tamilselvan, Prasanna; Wang, Pingfeng

    2013-01-01

    Effective health diagnosis provides multifarious benefits such as improved safety, improved reliability and reduced costs for operation and maintenance of complex engineered systems. This paper presents a novel multi-sensor health diagnosis method using deep belief network (DBN). DBN has recently become a popular approach in machine learning for its promised advantages such as fast inference and the ability to encode richer and higher order network structures. The DBN employs a hierarchical structure with multiple stacked restricted Boltzmann machines and works through a layer by layer successive learning process. The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset. Health diagnosis using DBN based health state classification technique is compared with four existing diagnosis techniques. Benchmark classification problems and two engineering health diagnosis applications: aircraft engine health diagnosis and electric power transformer health diagnosis are employed to demonstrate the efficacy of the proposed approach

  16. Learning soil classification with the Kayapó indians

    OpenAIRE

    Cooper,Miguel; Teramoto,Edson Roberto; Vidal-Torrado,Pablo; Sparovek,Gerd

    2005-01-01

    The Kayapó Xicrin do Cateté (Xicrin) indigenous reserve is located within the Amazon forest in Pará (Brazil). The Xicrins have developed a soil classification system that is incorporated in their language and culture. The etymology of their classification system and its logical structure makes it similar and comparable with modern soil classification. The etymology of the Xicrin's language is based on the junction of radicals to form words for different soil names. The name of the soil is for...

  17. The research on business rules classification and specification methods

    OpenAIRE

    Baltrušaitis, Egidijus

    2005-01-01

    The work is based on the research of business rules classification and specification methods. The basics of business rules approach are discussed. The most common business rules classification and modeling methods are analyzed. Business rules modeling techniques and tools for supporting them in the information systems are presented. Basing on the analysis results business rules classification method is proposed. Templates for every business rule type are presented. Business rules structuring ...

  18. Mapping of the Universe of Knowledge in Different Classification Schemes

    Directory of Open Access Journals (Sweden)

    M. P. Satija

    2017-06-01

    Full Text Available Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter’s Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider’s International Classification, Bibliothecal Bibliographic Klassification (BBK, and Broad System of Ordering (BSO. We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design.

  19. Heuristic Classification. Technical Report Number 12.

    Science.gov (United States)

    Clancey, William J.

    A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic…

  20. Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space

    NARCIS (Netherlands)

    Nicolaou, Mihalis A.; Gunes, Hatice; Pantic, Maja

    2010-01-01

    This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in terms of Maximum Likelihood Classification with the assumption that the generative model structure in the classifier is

  1. Group theoretical classification of chemical elements

    International Nuclear Information System (INIS)

    Byakov, V.M.; Kulakov, V.I.; Rumer, Y.B.; Fet, A.L.

    1977-01-01

    The method of classification of chemical elements, based on group symmetry principles, is compared with element properties. Elements are considered to be states of a single quantum system, the atomic structure being ignored. Elements treated as states of the system, break down into successively diminishing subsystems, big and small multiplets. The theory, being a group classification, does not describe in detail any of element properties, but leads to a unified qualitative description of all of them simultaneously

  2. Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

    Science.gov (United States)

    Wlodarski, Tomasz; Kutner, Jan; Towpik, Joanna; Knizewski, Lukasz; Rychlewski, Leszek; Kudlicki, Andrzej; Rowicka, Maga; Dziembowski, Andrzej; Ginalski, Krzysztof

    2011-01-01

    Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity). Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

  3. Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

    Directory of Open Access Journals (Sweden)

    Tomasz Wlodarski

    Full Text Available Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity. Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

  4. Validation of a new classification for periprosthetic shoulder fractures.

    Science.gov (United States)

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

    2018-06-01

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

  5. 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)

  6. Organizational Data Classification Based on the Importance Concept of Complex Networks.

    Science.gov (United States)

    Carneiro, Murillo Guimaraes; Zhao, Liang

    2017-08-01

    Data classification is a common task, which can be performed by both computers and human beings. However, a fundamental difference between them can be observed: computer-based classification considers only physical features (e.g., similarity, distance, or distribution) of input data; by contrast, brain-based classification takes into account not only physical features, but also the organizational structure of data. In this paper, we figure out the data organizational structure for classification using complex networks constructed from training data. Specifically, an unlabeled instance is classified by the importance concept characterized by Google's PageRank measure of the underlying data networks. Before a test data instance is classified, a network is constructed from vector-based data set and the test instance is inserted into the network in a proper manner. To this end, we also propose a measure, called spatio-structural differential efficiency, to combine the physical and topological features of the input data. Such a method allows for the classification technique to capture a variety of data patterns using the unique importance measure. Extensive experiments demonstrate that the proposed technique has promising predictive performance on the detection of heart abnormalities.

  7. Extension classification method for low-carbon product cases

    Directory of Open Access Journals (Sweden)

    Yanwei Zhao

    2016-05-01

    Full Text Available In product low-carbon design, intelligent decision systems integrated with certain classification algorithms recommend the existing design cases to designers. However, these systems mostly dependent on prior experience, and product designers not only expect to get a satisfactory case from an intelligent system but also hope to achieve assistance in modifying unsatisfactory cases. In this article, we proposed a new categorization method composed of static and dynamic classification based on extension theory. This classification method can be integrated into case-based reasoning system to get accurate classification results and to inform designers of detailed information about unsatisfactory cases. First, we establish the static classification model for cases by dependent function in a hierarchical structure. Then for dynamic classification, we make transformation for cases based on case model, attributes, attribute values, and dependent function, thus cases can take qualitative changes. Finally, the applicability of proposed method is demonstrated through a case study of screw air compressor cases.

  8. Classification of Specialized Farms Applying Multivariate Statistical Methods

    Directory of Open Access Journals (Sweden)

    Zuzana Hloušková

    2017-01-01

    Full Text Available Classification of specialized farms applying multivariate statistical methods The paper is aimed at application of advanced multivariate statistical methods when classifying cattle breeding farming enterprises by their economic size. Advantage of the model is its ability to use a few selected indicators compared to the complex methodology of current classification model that requires knowledge of detailed structure of the herd turnover and structure of cultivated crops. Output of the paper is intended to be applied within farm structure research focused on future development of Czech agriculture. As data source, the farming enterprises database for 2014 has been used, from the FADN CZ system. The predictive model proposed exploits knowledge of actual size classes of the farms tested. Outcomes of the linear discriminatory analysis multifactor classification method have supported the chance of filing farming enterprises in the group of Small farms (98 % filed correctly, and the Large and Very Large enterprises (100 % filed correctly. The Medium Size farms have been correctly filed at 58.11 % only. Partial shortages of the process presented have been found when discriminating Medium and Small farms.

  9. A Classification of Clay-Rich Subaqueous Density Flow Structures

    NARCIS (Netherlands)

    Hermidas, N.; Eggenhuisen, Joris T.; Jacinto, Ricardo Silva; Luthi, S.M.; Toth, Ferenc; Pohl, Florian

    2018-01-01

    This study presents a classification for subaqueous clay-laden sediment gravity flows. A series of laboratory flume experiments were performed using 9%, 15%, and 21% sediment mixture concentrations composed of sand, silt, clay, and tap water, on varying bed slopes of 6°, 8°, and 9.5°, and with

  10. Proposal of a new classification scheme for periocular injuries

    Directory of Open Access Journals (Sweden)

    Devi Prasad Mohapatra

    2017-01-01

    Full Text Available Background: Eyelids are important structures and play a role in protecting the globe from trauma, brightness, in maintaining the integrity of tear films and moving the tears towards the lacrimal drainage system and contribute to aesthetic appearance of the face. Ophthalmic trauma is an important cause of morbidity among individuals and has also been responsible for additional cost of healthcare. Periocular trauma involving eyelids and adjacent structures has been found to have increased recently probably due to increased pace of life and increased dependence on machinery. A comprehensive classification of periocular trauma would help in stratifying these injuries as well as study outcomes. Material and Methods: This study was carried out at our institute from June 2015 to Dec 2015. We searched multiple English language databases for existing classification systems for periocular trauma. We designed a system of classification of periocular soft tissue injuries based on clinico-anatomical presentations. This classification was applied prospectively to patients presenting with periocular soft tissue injuries to our department. Results: A comprehensive classification scheme was designed consisting of five types of periocular injuries. A total of 38 eyelid injuries in 34 patients were evaluated in this study. According to the System for Peri-Ocular Trauma (SPOT classification, Type V injuries were most common. SPOT Type II injuries were more common isolated injuries among all zones. Discussion: Classification systems are necessary in order to provide a framework in which to scientifically study the etiology, pathogenesis, and treatment of diseases in an orderly fashion. The SPOT classification has taken into account the periocular soft tissue injuries i.e., upper eyelid, lower eyelid, medial and lateral canthus injuries., based on observed clinico-anatomical patterns of eyelid injuries. Conclusion: The SPOT classification seems to be a reliable

  11. Automatic Genre Classification of Musical Signals

    Science.gov (United States)

    Barbedo, Jayme Garcia sArnal; Lopes, Amauri

    2006-12-01

    We present a strategy to perform automatic genre classification of musical signals. The technique divides the signals into 21.3 milliseconds frames, from which 4 features are extracted. The values of each feature are treated over 1-second analysis segments. Some statistical results of the features along each analysis segment are used to determine a vector of summary features that characterizes the respective segment. Next, a classification procedure uses those vectors to differentiate between genres. The classification procedure has two main characteristics: (1) a very wide and deep taxonomy, which allows a very meticulous comparison between different genres, and (2) a wide pairwise comparison of genres, which allows emphasizing the differences between each pair of genres. The procedure points out the genre that best fits the characteristics of each segment. The final classification of the signal is given by the genre that appears more times along all signal segments. The approach has shown very good accuracy even for the lowest layers of the hierarchical structure.

  12. Impact of job classification on employment of seasonal workers

    Directory of Open Access Journals (Sweden)

    Zoran Pandža

    2011-07-01

    Full Text Available The paper aims to improve the existing work organization, thus improving success of business process and ultimately reducing company costs. A change in organizational structure is proposed with the objective of achieving better and more efficient use of resources available within the company. Since the existing organization and classification of jobs does not meet the requirements of the age we live in, there is a need for new classification which would address many changes that have taken place over the years, including changes that are yet to be made for the purpose of further development of the company. Organization and management of the company as well as reorganization and implementation of a new classification is necessary to make it possible for the company to perform regular adjustment of business activities, because the conditions in which the company operates are changing fast. New classification would not actually change the number of sectors. Rather, existing personnel would be allocated in a better way, which would result in reduced needs for seasonal work force. In the process of defining the new organizational structure, one should consider the type, way of doing business, structural variables (division of labour, unity of command, authority and responsibility, span of control, division in business units, etc.. Expected results include improved organization and classification of jobs, improved quality of work, speed and efficiency. It should result in a company organized according to standards that are adjusted to modern times.

  13. Decimal Classification Editions

    OpenAIRE

    Zenovia Niculescu

    2009-01-01

    The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  14. Classification of crystal structure using a convolutional neural network.

    Science.gov (United States)

    Park, Woon Bae; Chung, Jiyong; Jung, Jaeyoung; Sohn, Keemin; Singh, Satendra Pal; Pyo, Myoungho; Shin, Namsoo; Sohn, Kee-Sun

    2017-07-01

    A deep machine-learning technique based on a convolutional neural network (CNN) is introduced. It has been used for the classification of powder X-ray diffraction (XRD) patterns in terms of crystal system, extinction group and space group. About 150 000 powder XRD patterns were collected and used as input for the CNN with no handcrafted engineering involved, and thereby an appropriate CNN architecture was obtained that allowed determination of the crystal system, extinction group and space group. In sharp contrast with the traditional use of powder XRD pattern analysis, the CNN never treats powder XRD patterns as a deconvoluted and discrete peak position or as intensity data, but instead the XRD patterns are regarded as nothing but a pattern similar to a picture. The CNN interprets features that humans cannot recognize in a powder XRD pattern. As a result, accuracy levels of 81.14, 83.83 and 94.99% were achieved for the space-group, extinction-group and crystal-system classifications, respectively. The well trained CNN was then used for symmetry identification of unknown novel inorganic compounds.

  15. Phylogenetic classification of the world’s tropical forests

    OpenAIRE

    Slik, J. W. Ferry; Franklin, Janet; Arroyo-Rodríguez, Víctor; Field, Richard; Aguilar, Salomon; Aguirre, Nikolay; Ahumada, Jorge; Aiba, Shin-Ichiro; Alves, Luciana F.; K, Anitha; Avella, Andres; Mora, Francisco; Aymard C., Gerardo A.; Báez, Selene; Balvanera, Patricia

    2018-01-01

    Identifying and explaining regional differences in tropical forest dynamics, structure, diversity, and composition are critical for anticipating region-specific responses to global environmental change. Floristic classifications are of fundamental importance for these efforts. Here we provide a global tropical forest classification that is explicitly based on community evolutionary similarity, resulting in identification of five major tropical forest regions and their relationships: (i) Indo-...

  16. Classification and mapping of the composition and structure of dry woodland and savanna in the eastern Okavango Delta

    Directory of Open Access Journals (Sweden)

    Michelle J. Tedder

    2013-02-01

    Full Text Available The dry woodland and savanna regions of the Okavango Delta form a transition zone between the Okavango Swamps and the Kalahari Desert and have been largely overlooked in terms of vegetation classification and mapping. This study focused on the species composition and height structure of this vegetation, with the aim of identifying vegetation classes and providing a vegetation map accompanied by quantitative data. Two hundred and fifty-six plots (50 m × 50 m were sampled and species cover abundance, total cover and structural composition were recorded. The plots were classified using agglomerative, hierarchical cluster analysis using group means and Bray-Curtis similarity and groups described using indicator species analysis. In total, 23 woody species and 28 grass species were recorded. Acacia erioloba and Colophospermum mopane were the most common woody species, whilst Urochloa mossambicensis, Panicum maximum, Dactyloctenium gigantiumand Eragrostis lehmanniana were the most widespread grasses. Eleven vegetation types were identified, with the most widespread being Short mixed mopane woodland, Tall mopane woodland and Tall mixed mopane woodland, covering 288.73 km2 (28%, 209.14 km2 (20% and 173.30 km2 (17% of the area, respectively. Despite their extensive area, these three vegetation types were the least species-rich, whilst Palm thornveld, Short mixed broadleaf woodland and Open mixed Acacia woodland were the most taxonomically variable. By contrast, Closed mixed Acacia woodland and Closed Acacia–Combretum woodland had the most limited distribution, accounting for less than 1% of the mapped area each.Conservation implications: The dry woodland and savanna vegetation of the Okavango Delta comprises a much wider suite of plant communities than the Acacia-dominated and Mopane-dominated classifications often used. This classification provided a more detailed understanding of this vegetation and essential background information for monitoring

  17. Managing risks in the fisheries supply chain using House of Risk Framework (HOR) and Interpretive Structural Modeling (ISM)

    Science.gov (United States)

    Nguyen, T. L. T.; Tran, T. T.; Huynh, T. P.; Ho, T. K. D.; Le, A. T.; Do, T. K. H.

    2018-04-01

    One of the sectors which contributes importantly to the development of Vietnam economy is fishery industry. However, during recent year, it has been witnessed many difficulties on managing the performance of the fishery supply chain operations as a whole. In this paper, a framework for supply chain risk management (SCRM) is proposed. Initially, all the activities are mapped by using Supply Chain Operations Reference (SCOR) model. Next, the risk ranking is analyzed in House of Risk. Furthermore, interpretive structural modeling (ISM) is used to identify inter-relationships among supply chain risks and to visualize the risks according to their levels. For illustration, the model has been tested in several case studies with fishery companies in Can Tho, Mekong Delta. This study identifies 22 risk events and 20 risk agents through the supply chain. Also, the risk priority could be used for further House of Risk with proactive actions in future studies.

  18. Representation learning with deep extreme learning machines for efficient image set classification

    KAUST Repository

    Uzair, Muhammad

    2016-12-09

    Efficient and accurate representation of a collection of images, that belong to the same class, is a major research challenge for practical image set classification. Existing methods either make prior assumptions about the data structure, or perform heavy computations to learn structure from the data itself. In this paper, we propose an efficient image set representation that does not make any prior assumptions about the structure of the underlying data. We learn the nonlinear structure of image sets with deep extreme learning machines that are very efficient and generalize well even on a limited number of training samples. Extensive experiments on a broad range of public datasets for image set classification show that the proposed algorithm consistently outperforms state-of-the-art image set classification methods both in terms of speed and accuracy.

  19. Representation learning with deep extreme learning machines for efficient image set classification

    KAUST Repository

    Uzair, Muhammad; Shafait, Faisal; Ghanem, Bernard; Mian, Ajmal

    2016-01-01

    Efficient and accurate representation of a collection of images, that belong to the same class, is a major research challenge for practical image set classification. Existing methods either make prior assumptions about the data structure, or perform heavy computations to learn structure from the data itself. In this paper, we propose an efficient image set representation that does not make any prior assumptions about the structure of the underlying data. We learn the nonlinear structure of image sets with deep extreme learning machines that are very efficient and generalize well even on a limited number of training samples. Extensive experiments on a broad range of public datasets for image set classification show that the proposed algorithm consistently outperforms state-of-the-art image set classification methods both in terms of speed and accuracy.

  20. Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana

    Science.gov (United States)

    Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard

    2015-03-01

    The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.

  1. Searching bioremediation patents through Cooperative Patent Classification (CPC).

    Science.gov (United States)

    Prasad, Rajendra

    2016-03-01

    Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation.

  2. PI-RADS classification. Structured reporting for MRI of the prostate

    International Nuclear Information System (INIS)

    Roethke, Matthias; Schlemmer, H.P.; Blondin, D.; Franiel, T.

    2013-01-01

    Purpose: To flesh out the ESUR guidelines for the standardized interpretation of multiparametric magnetic resonance imaging (mMRI) for the detection of prostate cancer and to present a graphic reporting scheme for improved communication of findings to urologists. Materials and Methods: The ESUR has recently published a structured reporting system for mMRI of the prostate (PI-RADS). This system involves the use of 5-point Likert scales for grading the findings obtained with different MRI techniques. The mMRI includes T2-weighted MRI, diffusion-weighted imaging, dynamic contrast-enhanced MRI, and MR spectroscopy. In a first step, the fundamentals of technical implementation were determined by consensus, taking into account in particular the German-speaking community. Then, representative images were selected by consensus on the basis of examinations of the three institutions. In addition, scoring intervals for an aggregated PI-RADS score were determined in consensus. Results: The multiparametric methods were discussed critically with regard to implementation and the current status. Criteria used for grading mMRI findings with the PI-RADS classification were concretized by succinct examples. Using the consensus table for aggregated scoring in a clinical setting, a diagnosis of suspected prostate cancer should be made if the PI-RADS score is 4 or higher (≥ 10 points if 3 techniques are used or ≥ 13 points if 4 techniques are used). Finally, a graphic scheme was developed for communicating mMRI prostate findings. Conclusion: Structured reporting according to the ESUR guidelines contributes to quality assurance by standardizing prostate mMRI, and it facilities the communication of findings to urologists. (orig.)

  3. Decimal Classification Editions

    Directory of Open Access Journals (Sweden)

    Zenovia Niculescu

    2009-01-01

    Full Text Available The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  4. Investigating the use of support vector machine classification on structural brain images of preterm-born teenagers as a biological marker.

    Directory of Open Access Journals (Sweden)

    Carlton Chu

    Full Text Available Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM classification methods we aimed to investigate whether MRI data, collected in adolescence, could be used to predict whether an individual had been born preterm or at term. To this end we collected T1-weighted anatomical MRI data from 143 individuals (69 controls, mean age 14.6y. The inclusion criteria for those born preterm were birth weight ≤ 1500g and gestational age < 37w. A linear SVM was trained on the grey matter segment of MR images in two different ways. First, all the individuals were used for training and classification was performed by the leave-one-out method, yielding 93% correct classification (sensitivity = 0.905, specificity = 0.942. Separately, a random half of the available data were used for training twice and each time the other, unseen, half of the data was classified, resulting 86% and 91% accurate classifications. Both gestational age (R = -0.24, p<0.04 and birth weight (R = -0.51, p < 0.001 correlated with the distance to decision boundary within the group of individuals born preterm. Statistically significant correlations were also found between IQ (R = -0.30, p < 0.001 and the distance to decision boundary. Those born small for gestational age did not form a separate subgroup in these analyses. The high rate of correct classification by the SVM motivates further investigation. The long-term goal is to automatically and non-invasively predict the outcome of preterm-born individuals on an individual basis using as early a scan as possible.

  5. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  6. Airborne LIDAR Power Line Classification Based on Spatial Topological Structure Characteristics

    Science.gov (United States)

    Wang, Y.; Chen, Q.; Li, K.; Zheng, D.; Fang, J.

    2017-09-01

    Automatic extraction of power lines has become a topic of great importance in airborne LiDAR data processing for transmission line management. In this paper, we present a new, fully automated and versatile framework that consists of four steps: (i) power line candidate point filtering, (ii) neighbourhood selection, (iii) feature extraction based on spatial topology, and (iv) SVM classification. In a detailed evaluation involving seven neighbourhood definitions, 26 geometric features and two datasets, we demonstrated that the use of multi-scale neighbourhoods for individual 3D points significantly improved the power line classification. Additionally, we showed that the spatial topological features may even further improve the results while reducing data processing time.

  7. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-11-18

    ...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and... response to requests from the U.S. cotton industry and ICE, AMS will offer a futures classification option...

  8. 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

  9. Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics.

    Science.gov (United States)

    Chepelev, Leonid L; Riazanov, Alexandre; Kouznetsov, Alexandre; Low, Hong Sang; Dumontier, Michel; Baker, Christopher J O

    2011-07-26

    The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of

  10. Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics

    Directory of Open Access Journals (Sweden)

    Dumontier Michel

    2011-07-01

    Full Text Available Abstract Background The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. Results As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of

  11. Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination.

    Science.gov (United States)

    Sørensen, Lauge; Nielsen, Mads

    2018-05-15

    The International Challenge for Automated Prediction of MCI from MRI data offered independent, standardized comparison of machine learning algorithms for multi-class classification of normal control (NC), mild cognitive impairment (MCI), converting MCI (cMCI), and Alzheimer's disease (AD) using brain imaging and general cognition. We proposed to use an ensemble of support vector machines (SVMs) that combined bagging without replacement and feature selection. SVM is the most commonly used algorithm in multivariate classification of dementia, and it was therefore valuable to evaluate the potential benefit of ensembling this type of classifier. The ensemble SVM, using either a linear or a radial basis function (RBF) kernel, achieved multi-class classification accuracies of 55.6% and 55.0% in the challenge test set (60 NC, 60 MCI, 60 cMCI, 60 AD), resulting in a third place in the challenge. Similar feature subset sizes were obtained for both kernels, and the most frequently selected MRI features were the volumes of the two hippocampal subregions left presubiculum and right subiculum. Post-challenge analysis revealed that enforcing a minimum number of selected features and increasing the number of ensemble classifiers improved classification accuracy up to 59.1%. The ensemble SVM outperformed single SVM classifications consistently in the challenge test set. Ensemble methods using bagging and feature selection can improve the performance of the commonly applied SVM classifier in dementia classification. This resulted in competitive classification accuracies in the International Challenge for Automated Prediction of MCI from MRI data. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Texture operator for snow particle classification into snowflake and graupel

    Science.gov (United States)

    Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

    2012-11-01

    In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and

  13. Various forms of indexing HDMR for modelling multivariate classification problems

    Energy Technology Data Exchange (ETDEWEB)

    Aksu, Çağrı [Bahçeşehir University, Information Technologies Master Program, Beşiktaş, 34349 İstanbul (Turkey); Tunga, M. Alper [Bahçeşehir University, Software Engineering Department, Beşiktaş, 34349 İstanbul (Turkey)

    2014-12-10

    The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled. In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.

  14. Preliminary discussion on the classification of uranium deposits in China

    International Nuclear Information System (INIS)

    Zhou Weixun; Liu Xinzhong; Wang Zubang.

    1991-01-01

    The classification of uranium deposits is a comprehensive and complicated problem which is of great importance for the guide in prospecting and exploration. The authors review the merits and shortcomings of various classifications sumitted by uranium geologists in the world based on origin, geotectonics and host rocks. Considering the reasonable parts in previous classifications and characteristics of uranium metallogenesis in China, the authors suggest a new classification of uranium deposits of China mainly according to host rocks, and also deposits' structure and morphology of ore bodies. This classification is composed of 7 goups divided into 25 subgroups. Finally, an indication and explanation are presented in order to draw attention of the Chinese uranium geologists and make further discussions among them

  15. Towards Automatic Classification of Wikipedia Content

    Science.gov (United States)

    Szymański, Julian

    Wikipedia - the Free Encyclopedia encounters the problem of proper classification of new articles everyday. The process of assignment of articles to categories is performed manually and it is a time consuming task. It requires knowledge about Wikipedia structure, which is beyond typical editor competence, which leads to human-caused mistakes - omitting or wrong assignments of articles to categories. The article presents application of SVM classifier for automatic classification of documents from The Free Encyclopedia. The classifier application has been tested while using two text representations: inter-documents connections (hyperlinks) and word content. The results of the performed experiments evaluated on hand crafted data show that the Wikipedia classification process can be partially automated. The proposed approach can be used for building a decision support system which suggests editors the best categories that fit new content entered to Wikipedia.

  16. Cluster analysis of novel isometric strength measures produces a valid and evidence-based classification structure for wheelchair track racing.

    Science.gov (United States)

    Connick, Mark J; Beckman, Emma; Vanlandewijck, Yves; Malone, Laurie A; Blomqvist, Sven; Tweedy, Sean M

    2017-11-25

    The Para athletics wheelchair-racing classification system employs best practice to ensure that classes comprise athletes whose impairments cause a comparable degree of activity limitation. However, decision-making is largely subjective and scientific evidence which reduces this subjectivity is required. To evaluate whether isometric strength tests were valid for the purposes of classifying wheelchair racers and whether cluster analysis of the strength measures produced a valid classification structure. Thirty-two international level, male wheelchair racers from classes T51-54 completed six isometric strength tests evaluating elbow extensors, shoulder flexors, trunk flexors and forearm pronators and two wheelchair performance tests-Top-Speed (0-15 m) and Top-Speed (absolute). Strength tests significantly correlated with wheelchair performance were included in a cluster analysis and the validity of the resulting clusters was assessed. All six strength tests correlated with performance (r=0.54-0.88). Cluster analysis yielded four clusters with reasonable overall structure (mean silhouette coefficient=0.58) and large intercluster strength differences. Six athletes (19%) were allocated to clusters that did not align with their current class. While the mean wheelchair racing performance of the resulting clusters was unequivocally hierarchical, the mean performance of current classes was not, with no difference between current classes T53 and T54. Cluster analysis of isometric strength tests produced classes comprising athletes who experienced a similar degree of activity limitation. The strength tests reported can provide the basis for a new, more transparent, less subjective wheelchair racing classification system, pending replication of these findings in a larger, representative sample. This paper also provides guidance for development of evidence-based systems in other Para sports. © Article author(s) (or their employer(s) unless otherwise stated in the text of

  17. A REVISED PARALLEL-SEQUENCE MORPHOLOGICAL CLASSIFICATION OF GALAXIES: STRUCTURE AND FORMATION OF S0 AND SPHEROIDAL GALAXIES

    International Nuclear Information System (INIS)

    Kormendy, John; Bender, Ralf

    2012-01-01

    We update van den Bergh's parallel-sequence galaxy classification in which S0 galaxies form a sequence S0a-S0b-S0c that parallels the sequence Sa-Sb-Sc of spiral galaxies. The ratio B/T of bulge-to-total light defines the position of a galaxy in this tuning-fork diagram. Our classification makes one major improvement. We extend the S0a-S0b-S0c sequence to spheroidal ('Sph') galaxies that are positioned in parallel to irregular galaxies in a similarly extended Sa-Sb-Sc-Im sequence. This provides a natural 'home' for spheroidals, which previously were omitted from galaxy classification schemes or inappropriately combined with ellipticals. To motivate our juxtaposition of Sph and Im galaxies, we present photometry and bulge-disk decompositions of four rare, late-type S0s that bridge the gap between the more common S0b and Sph galaxies. NGC 4762 is an edge-on SB0bc galaxy with a very small classical-bulge-to-total ratio of B/T = 0.13 ± 0.02. NGC 4452 is an edge-on SB0 galaxy with an even tinier pseudobulge-to-total ratio of PB/T = 0.017 ± 0.004. It is therefore an SB0c. VCC 2048, whose published classification is S0, contains an edge-on disk, but its 'bulge' plots in the structural parameter sequence of spheroidals. It is therefore a disky Sph. And NGC 4638 is similarly a 'missing link' between S0s and Sphs—it has a tiny bulge and an edge-on disk embedded in an Sph halo. In the Appendix, we present photometry and bulge-disk decompositions of all Hubble Space Telescope Advanced Camera for Surveys Virgo Cluster Survey S0s that do not have published decompositions. We use these data to update the structural parameter correlations of Sph, S+Im, and E galaxies. We show that Sph galaxies of increasing luminosity form a continuous sequence with the disks (but not bulges) of S0c-S0b-S0a galaxies. Remarkably, the Sph-S0-disk sequence is almost identical to that of Im galaxies and spiral galaxy disks. We review published observations for galaxy transformation processes

  18. A Revised Parallel-sequence Morphological Classification of Galaxies: Structure and Formation of S0 and Spheroidal Galaxies

    Science.gov (United States)

    Kormendy, John; Bender, Ralf

    2012-01-01

    We update van den Bergh's parallel-sequence galaxy classification in which S0 galaxies form a sequence S0a-S0b-S0c that parallels the sequence Sa-Sb-Sc of spiral galaxies. The ratio B/T of bulge-to-total light defines the position of a galaxy in this tuning-fork diagram. Our classification makes one major improvement. We extend the S0a-S0b-S0c sequence to spheroidal ("Sph") galaxies that are positioned in parallel to irregular galaxies in a similarly extended Sa-Sb-Sc-Im sequence. This provides a natural "home" for spheroidals, which previously were omitted from galaxy classification schemes or inappropriately combined with ellipticals. To motivate our juxtaposition of Sph and Im galaxies, we present photometry and bulge-disk decompositions of four rare, late-type S0s that bridge the gap between the more common S0b and Sph galaxies. NGC 4762 is an edge-on SB0bc galaxy with a very small classical-bulge-to-total ratio of B/T = 0.13 ± 0.02. NGC 4452 is an edge-on SB0 galaxy with an even tinier pseudobulge-to-total ratio of PB/T = 0.017 ± 0.004. It is therefore an SB0c. VCC 2048, whose published classification is S0, contains an edge-on disk, but its "bulge" plots in the structural parameter sequence of spheroidals. It is therefore a disky Sph. And NGC 4638 is similarly a "missing link" between S0s and Sphs—it has a tiny bulge and an edge-on disk embedded in an Sph halo. In the Appendix, we present photometry and bulge-disk decompositions of all Hubble Space Telescope Advanced Camera for Surveys Virgo Cluster Survey S0s that do not have published decompositions. We use these data to update the structural parameter correlations of Sph, S+Im, and E galaxies. We show that Sph galaxies of increasing luminosity form a continuous sequence with the disks (but not bulges) of S0c-S0b-S0a galaxies. Remarkably, the Sph-S0-disk sequence is almost identical to that of Im galaxies and spiral galaxy disks. We review published observations for galaxy transformation processes

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

    Science.gov (United States)

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

    2013-01-01

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

  20. Free classification of regional dialects of American English

    Science.gov (United States)

    Clopper, Cynthia G.; Pisoni, David B.

    2011-01-01

    Recent studies have found that naïve listeners perform poorly in forced-choice dialect categorization tasks. However, the listeners' error patterns in these tasks reveal systematic confusions between phonologically similar dialects. In the present study, a free classification procedure was used to measure the perceptual similarity structure of regional dialect variation in the United States. In two experiments, participants listened to a set of short English sentences produced by male talkers only (Experiment 1) and by male and female talkers (Experiment 2). The listeners were instructed to group the talkers by regional dialect into as many groups as they wanted with as many talkers in each group as they wished. Multidimensional scaling analyses of the data revealed three primary dimensions of perceptual similarity (linguistic markedness, geography, and gender). In addition, a comparison of the results obtained from the free classification task to previous results using the same stimulus materials in six-alternative forced-choice categorization tasks revealed that response biases in the six-alternative task were reduced or eliminated in the free classification task. Thus, the results obtained with the free classification task in the current study provided further evidence that the underlying structure of perceptual dialect category representations reflects important linguistic and sociolinguistic factors. PMID:21423862

  1. Free classification of regional dialects of American English.

    Science.gov (United States)

    Clopper, Cynthia G; Pisoni, David B

    2007-07-01

    Recent studies have found that naïve listeners perform poorly in forced-choice dialect categorization tasks. However, the listeners' error patterns in these tasks reveal systematic confusions between phonologically similar dialects. In the present study, a free classification procedure was used to measure the perceptual similarity structure of regional dialect variation in the United States. In two experiments, participants listened to a set of short English sentences produced by male talkers only (Experiment 1) and by male and female talkers (Experiment 2). The listeners were instructed to group the talkers by regional dialect into as many groups as they wanted with as many talkers in each group as they wished. Multidimensional scaling analyses of the data revealed three primary dimensions of perceptual similarity (linguistic markedness, geography, and gender). In addition, a comparison of the results obtained from the free classification task to previous results using the same stimulus materials in six-alternative forced-choice categorization tasks revealed that response biases in the six-alternative task were reduced or eliminated in the free classification task. Thus, the results obtained with the free classification task in the current study provided further evidence that the underlying structure of perceptual dialect category representations reflects important linguistic and sociolinguistic factors.

  2. International Spinal Cord Injury Pain Classification: part I. Background and description

    DEFF Research Database (Denmark)

    Bryce, T N; Biering-Sørensen, Fin; Finnerup, Nanna Brix

    2012-01-01

    of clinicians with minimal exposure to the classification, using case study vignettes. Based upon the results of this study, further revisions were made to the ISCIP Classification.Results:An overall structure and terminology has been developed and partially validated as a merger of and improvement...

  3. Performance-scalable volumetric data classification for online industrial inspection

    Science.gov (United States)

    Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

    2002-03-01

    Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

  4. Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

    Science.gov (United States)

    Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

    2018-05-01

    In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

  5. Analysis and application of classification methods of complex carbonate reservoirs

    Science.gov (United States)

    Li, Xiongyan; Qin, Ruibao; Ping, Haitao; Wei, Dan; Liu, Xiaomei

    2018-06-01

    There are abundant carbonate reservoirs from the Cenozoic to Mesozoic era in the Middle East. Due to variation in sedimentary environment and diagenetic process of carbonate reservoirs, several porosity types coexist in carbonate reservoirs. As a result, because of the complex lithologies and pore types as well as the impact of microfractures, the pore structure is very complicated. Therefore, it is difficult to accurately calculate the reservoir parameters. In order to accurately evaluate carbonate reservoirs, based on the pore structure evaluation of carbonate reservoirs, the classification methods of carbonate reservoirs are analyzed based on capillary pressure curves and flow units. Based on the capillary pressure curves, although the carbonate reservoirs can be classified, the relationship between porosity and permeability after classification is not ideal. On the basis of the flow units, the high-precision functional relationship between porosity and permeability after classification can be established. Therefore, the carbonate reservoirs can be quantitatively evaluated based on the classification of flow units. In the dolomite reservoirs, the average absolute error of calculated permeability decreases from 15.13 to 7.44 mD. Similarly, the average absolute error of calculated permeability of limestone reservoirs is reduced from 20.33 to 7.37 mD. Only by accurately characterizing pore structures and classifying reservoir types, reservoir parameters could be calculated accurately. Therefore, characterizing pore structures and classifying reservoir types are very important to accurate evaluation of complex carbonate reservoirs in the Middle East.

  6. Methodology for safety classification of PWR type nuclear power plants items

    International Nuclear Information System (INIS)

    Oliveira, Patricia Pagetti de

    1995-01-01

    This paper contains the criteria and methodology which define a classification system of structures, systems and components in safety classes according to their importance to nuclear safety. The use of this classification system will provide a set of basic safety requirements associated with each safety class specified. These requirements, when available and applicable, shall be utilized in the design, fabrication and installation of structures, systems and components of Pressurized Water Reactor Nuclear Power Plants. (author). 13 refs, 1 tab

  7. Classification versus inference learning contrasted with real-world categories.

    Science.gov (United States)

    Jones, Erin L; Ross, Brian H

    2011-07-01

    Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

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

    Science.gov (United States)

    Borchert, Otto Jerome

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

  9. Bayesian Classification of Image Structures

    DEFF Research Database (Denmark)

    Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert

    2009-01-01

    In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...

  10. Manifold regularized multitask learning for semi-supervised multilabel image classification.

    Science.gov (United States)

    Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

    2013-02-01

    It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

  11. Learning soil classification with the Kayapó indians

    Directory of Open Access Journals (Sweden)

    Cooper Miguel

    2005-01-01

    Full Text Available The Kayapó Xicrin do Cateté (Xicrin indigenous reserve is located within the Amazon forest in Pará (Brazil. The Xicrins have developed a soil classification system that is incorporated in their language and culture. The etymology of their classification system and its logical structure makes it similar and comparable with modern soil classification. The etymology of the Xicrin's language is based on the junction of radicals to form words for different soil names. The name of the soil is formed by the main noun radical "puka", to which adjectives referring to soil morphological attributes are added. Modern classification systems are also based on similar morphological variables, and analytical support for defining boundaries of chemical or physical soil attributes are important only in lower hierarchical levels. Soil scientists have developed a soil classification system that is sensitive for the restrictions and potentialities the soil will show for modern agriculture. The Xicrins classify soils for what is important for their life style, i.e. a harmonic and friendly life with the resources they gain from the forest.

  12. 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....

  13. 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)

  14. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  15. A Robust Geometric Model for Argument Classification

    Science.gov (United States)

    Giannone, Cristina; Croce, Danilo; Basili, Roberto; de Cao, Diego

    Argument classification is the task of assigning semantic roles to syntactic structures in natural language sentences. Supervised learning techniques for frame semantics have been recently shown to benefit from rich sets of syntactic features. However argument classification is also highly dependent on the semantics of the involved lexicals. Empirical studies have shown that domain dependence of lexical information causes large performance drops in outside domain tests. In this paper a distributional approach is proposed to improve the robustness of the learning model against out-of-domain lexical phenomena.

  16. 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...

  17. Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Bülent Haznedar

    2017-02-01

    Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

  18. Reliability, validity and treatment sensitivity of the Schizophrenia Cognition Rating Scale.

    Science.gov (United States)

    Keefe, Richard S E; Davis, Vicki G; Spagnola, Nathan B; Hilt, Dana; Dgetluck, Nancy; Ruse, Stacy; Patterson, Thomas D; Narasimhan, Meera; Harvey, Philip D

    2015-02-01

    Cognitive functioning can be assessed with performance-based assessments such as neuropsychological tests and with interview-based assessments. Both assessment methods have the potential to assess whether treatments for schizophrenia improve clinically relevant aspects of cognitive impairment. However, little is known about the reliability, validity and treatment responsiveness of interview-based measures, especially in the context of clinical trials. Data from two studies were utilized to assess these features of the Schizophrenia Cognition Rating Scale (SCoRS). One of the studies was a validation study involving 79 patients with schizophrenia assessed at 3 academic research centers in the US. The other study was a 32-site clinical trial conducted in the US and Europe comparing the effects of encenicline, an alpha-7 nicotine agonist, to placebo in 319 patients with schizophrenia. The SCoRS interviewer ratings demonstrated excellent test-retest reliability in several different circumstances, including those that did not involve treatment (ICC> 0.90), and during treatment (ICC>0.80). SCoRS interviewer ratings were related to cognitive performance as measured by the MCCB (r=-0.35), and demonstrated significant sensitivity to treatment with encenicline compared to placebo (Pcognition in schizophrenia, and may be useful for clinical practice. The weaknesses of the SCoRS include its reliance on informant information, which is not available for some patients, and reduced validity when patient's self-report is the sole information source. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

  19. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

  20. Hydrological Climate Classification: Can We Improve on Köppen-Geiger?

    Science.gov (United States)

    Knoben, W.; Woods, R. A.; Freer, J. E.

    2017-12-01

    Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which

  1. Building the United States National Vegetation Classification

    Science.gov (United States)

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

    2012-01-01

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

  2. TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    N. Li

    2016-06-01

    Full Text Available Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the “raw” data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

  3. 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.

  4. Classification of refrigerants; Classification des fluides frigorigenes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

  5. ClassyFire: automated chemical classification with a comprehensive, computable taxonomy.

    Science.gov (United States)

    Djoumbou Feunang, Yannick; Eisner, Roman; Knox, Craig; Chepelev, Leonid; Hastings, Janna; Owen, Gareth; Fahy, Eoin; Steinbeck, Christoph; Subramanian, Shankar; Bolton, Evan; Greiner, Russell; Wishart, David S

    2016-01-01

    Scientists have long been driven by the desire to describe, organize, classify, and compare objects using taxonomies and/or ontologies. In contrast to biology, geology, and many other scientific disciplines, the world of chemistry still lacks a standardized chemical ontology or taxonomy. Several attempts at chemical classification have been made; but they have mostly been limited to either manual, or semi-automated proof-of-principle applications. This is regrettable as comprehensive chemical classification and description tools could not only improve our understanding of chemistry but also improve the linkage between chemistry and many other fields. For instance, the chemical classification of a compound could help predict its metabolic fate in humans, its druggability or potential hazards associated with it, among others. However, the sheer number (tens of millions of compounds) and complexity of chemical structures is such that any manual classification effort would prove to be near impossible. We have developed a comprehensive, flexible, and computable, purely structure-based chemical taxonomy (ChemOnt), along with a computer program (ClassyFire) that uses only chemical structures and structural features to automatically assign all known chemical compounds to a taxonomy consisting of >4800 different categories. This new chemical taxonomy consists of up to 11 different levels (Kingdom, SuperClass, Class, SubClass, etc.) with each of the categories defined by unambiguous, computable structural rules. Furthermore each category is named using a consensus-based nomenclature and described (in English) based on the characteristic common structural properties of the compounds it contains. The ClassyFire webserver is freely accessible at http://classyfire.wishartlab.com/. Moreover, a Ruby API version is available at https://bitbucket.org/wishartlab/classyfire_api, which provides programmatic access to the ClassyFire server and database. ClassyFire has been used to

  6. 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...

  7. Whewell on classification and consilience.

    Science.gov (United States)

    Quinn, Aleta

    2017-08-01

    In this paper I sketch William Whewell's attempts to impose order on classificatory mineralogy, which was in Whewell's day (1794-1866) a confused science of uncertain prospects. Whewell argued that progress was impeded by the crude reductionist assumption that all macroproperties of crystals could be straightforwardly explained by reference to the crystals' chemical constituents. By comparison with biological classification, Whewell proposed methodological reforms that he claimed would lead to a natural classification of minerals, which in turn would support advances in causal understanding of the properties of minerals. Whewell's comparison to successful biological classification is particularly striking given that classificatory biologists did not share an understanding of the causal structure underlying the natural classification of life (the common descent with modification of all organisms). Whewell's key proposed methodological reform is consideration of multiple, distinct principles of classification. The most powerful evidence in support of a natural classificatory claim is the consilience of claims arrived at through distinct lines of reasoning, rooted in distinct conceptual approaches to the target objects. Mineralogists must consider not only elemental composition and chemical affinities, but also symmetry and polarity. Geometrical properties are central to what makes an individual mineral the type of mineral that it is. In Whewell's view, function and organization jointly define life, and so are the keys to understanding what makes an organism the type of organism that it is. I explain the relationship between Whewell's teleological account of life and his natural theology. I conclude with brief comments about the importance of Whewell's classificatory theory for the further development of his philosophy of science and in particular his account of consilience. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Learning semantic histopathological representation for basal cell carcinoma classification

    Science.gov (United States)

    Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

    2013-03-01

    Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

  9. Semi-supervised Probabilistic Distance Clustering and the Uncertainty of Classification

    Science.gov (United States)

    Iyigun, Cem; Ben-Israel, Adi

    Semi-supervised clustering is an attempt to reconcile clustering (unsupervised learning) and classification (supervised learning, using prior information on the data). These two modes of data analysis are combined in a parameterized model, the parameter θ ∈ [0, 1] is the weight attributed to the prior information, θ = 0 corresponding to clustering, and θ = 1 to classification. The results (cluster centers, classification rule) depend on the parameter θ, an insensitivity to θ indicates that the prior information is in agreement with the intrinsic cluster structure, and is otherwise redundant. This explains why some data sets (such as the Wisconsin breast cancer data, Merz and Murphy, UCI repository of machine learning databases, University of California, Irvine, CA) give good results for all reasonable classification methods. The uncertainty of classification is represented here by the geometric mean of the membership probabilities, shown to be an entropic distance related to the Kullback-Leibler divergence.

  10. Acoustic transient classification with a template correlation processor.

    Science.gov (United States)

    Edwards, R T

    1999-10-01

    I present an architecture for acoustic pattern classification using trinary-trinary template correlation. In spite of its computational simplicity, the algorithm and architecture represent a method which greatly reduces bandwidth of the input, storage requirements of the classifier memory, and power consumption of the system without compromising classification accuracy. The linear system should be amenable to training using recently-developed methods such as Independent Component Analysis (ICA), and we predict that behavior will be qualitatively similar to that of structures in the auditory cortex.

  11. An Object-Based Classification Approach for Mapping Migrant Housing in the Mega-Urban Area of the Pearl River Delta (China

    Directory of Open Access Journals (Sweden)

    Sebastian D’Oleire-Oltmanns

    2011-08-01

    Full Text Available Urban areas develop on formal and informal levels. Informal development is often highly dynamic, leading to a lag of spatial information about urban structure types. In this work, an object-based remote sensing approach will be presented to map the migrant housing urban structure type in the Pearl River Delta, China. SPOT5 data were utilized for the classification (auxiliary data, particularly up-to-date cadastral data, were not available. A hierarchically structured classification process was used to create (spectral independence from single satellite scenes and to arrive at a transferrable classification process. Using the presented classification approach, an overall classification accuracy of migrant housing of 68.0% is attained.

  12. 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

  13. Building classification trees to explain the radioactive contamination levels of the plants

    International Nuclear Information System (INIS)

    Briand, B.

    2008-04-01

    The objective of this thesis is the development of a method allowing the identification of factors leading to various radioactive contamination levels of the plants. The methodology suggested is based on the use of a radioecological transfer model of the radionuclides through the environment (A.S.T.R.A.L. computer code) and a classification-tree method. Particularly, to avoid the instability problems of classification trees and to preserve the tree structure, a node level stabilizing technique is used. Empirical comparisons are carried out between classification trees built by this method (called R.E.N. method) and those obtained by the C.A.R.T. method. A similarity measure is defined to compare the structure of two classification trees. This measure is used to study the stabilizing performance of the R.E.N. method. The methodology suggested is applied to a simplified contamination scenario. By the results obtained, we can identify the main variables responsible of the various radioactive contamination levels of four leafy-vegetables (lettuce, cabbage, spinach and leek). Some extracted rules from these classification trees can be usable in a post-accidental context. (author)

  14. Geological-genetic classification for uranium deposits

    International Nuclear Information System (INIS)

    Terentiev, V.M.; Naumov, S.S.

    1997-01-01

    The paper describes a system for classification uranium deposits based on geological and genetic characteristics. The system is based on the interrelation and interdependence of uranium ore formation processes and other geological phenomena including sedimentation, magmatism and tectonics, as well as the evolution of geotectonic structures. Using these aspects, deposits are classified in three categories: endogenic - predominately hydrothermal and hydrothermal-metasomatic; exogenic - sedimentary diagenetic, biogenic sorption, and infiltrational; and polygenetic or composite types. The latter complex types includes: sedimentary/metamorphic and metamorphic and sedimentary/hydrothermal, where different ore generating processes have prevailed over a rock unit at different times. The 3 page classification is given in both the English and Russian languages. (author). 3 tabs

  15. AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    CHANDRASEKAR RAVI

    2017-06-01

    Full Text Available Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes. Several researchers have proposed classification techniques but most of them did not emphasis much on the misclassified instances and storage space. In this paper, a classification model is proposed that takes into account the misclassified instances and storage space. The classification model is efficiently developed using a tree structure for reducing the storage complexity and uses single scan of the dataset. During the training phase, Class-based Closed Frequent ItemSets (CCFIS were mined from the training dataset in the form of a tree structure. The classification model has been developed using the CCFIS and a similarity measure based on Longest Common Subsequence (LCS. Further, the Particle Swarm Optimization algorithm is applied on the generated CCFIS, which assigns weights to the itemsets and their associated classes. Most of the classifiers are correctly classifying the common instances but they misclassify the rare instances. In view of that, AdaBoost algorithm has been used to boost the weights of the misclassified instances in the previous round so as to include them in the training phase to classify the rare instances. This improves the accuracy of the classification model. During the testing phase, the classification model is used to classify the instances of the test dataset. Breast Cancer dataset from UCI repository is used for experiment. Experimental analysis shows that the accuracy of the proposed classification model outperforms the PSOAdaBoost-Sequence classifier by 7% superior to other approaches like Naïve Bayes Classifier, Support Vector Machine Classifier, Instance Based Classifier, ID3 Classifier, J48 Classifier, etc.

  16. Representation Learning for Class C G Protein-Coupled Receptors Classification

    Directory of Open Access Journals (Sweden)

    Raúl Cruz-Barbosa

    2018-03-01

    Full Text Available G protein-coupled receptors (GPCRs are integral cell membrane proteins of relevance for pharmacology. The complete tertiary structure including both extracellular and transmembrane domains has not been determined for any member of class C GPCRs. An alternative way to work on GPCR structural models is the investigation of their functionality through the analysis of their primary structure. For this, sequence representation is a key factor for the GPCRs’ classification context, where usually, feature engineering is carried out. In this paper, we propose the use of representation learning to acquire the features that best represent the class C GPCR sequences and at the same time to obtain a model for classification automatically. Deep learning methods in conjunction with amino acid physicochemical property indices are then used for this purpose. Experimental results assessed by the classification accuracy, Matthews’ correlation coefficient and the balanced error rate show that using a hydrophobicity index and a restricted Boltzmann machine (RBM can achieve performance results (accuracy of 92.9% similar to those reported in the literature. As a second proposal, we combine two or more physicochemical property indices instead of only one as the input for a deep architecture in order to add information from the sequences. Experimental results show that using three hydrophobicity-related index combinations helps to improve the classification performance (accuracy of 94.1% of an RBM better than those reported in the literature for class C GPCRs without using feature selection methods.

  17. Classification of hydrocephalus: critical analysis of classification categories and advantages of "Multi-categorical Hydrocephalus Classification" (Mc HC).

    Science.gov (United States)

    Oi, Shizuo

    2011-10-01

    Hydrocephalus is a complex pathophysiology with disturbed cerebrospinal fluid (CSF) circulation. There are numerous numbers of classification trials published focusing on various criteria, such as associated anomalies/underlying lesions, CSF circulation/intracranial pressure patterns, clinical features, and other categories. However, no definitive classification exists comprehensively to cover the variety of these aspects. The new classification of hydrocephalus, "Multi-categorical Hydrocephalus Classification" (Mc HC), was invented and developed to cover the entire aspects of hydrocephalus with all considerable classification items and categories. Ten categories include "Mc HC" category I: onset (age, phase), II: cause, III: underlying lesion, IV: symptomatology, V: pathophysiology 1-CSF circulation, VI: pathophysiology 2-ICP dynamics, VII: chronology, VII: post-shunt, VIII: post-endoscopic third ventriculostomy, and X: others. From a 100-year search of publication related to the classification of hydrocephalus, 14 representative publications were reviewed and divided into the 10 categories. The Baumkuchen classification graph made from the round o'clock classification demonstrated the historical tendency of deviation to the categories in pathophysiology, either CSF or ICP dynamics. In the preliminary clinical application, it was concluded that "Mc HC" is extremely effective in expressing the individual state with various categories in the past and present condition or among the compatible cases of hydrocephalus along with the possible chronological change in the future.

  18. 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…

  19. Bookseller’s Classification: Classification Examples and Criteria of Croatian Booksellers in Sales Catalogs and Book Lists from the Beginning of the 20th Century

    Directory of Open Access Journals (Sweden)

    Nada Topić

    2012-12-01

    Full Text Available The aim of the paper is to conduct research on the topic of ways of bookstore (sales classification of Croatian bookstores from the beginning of the 20th century. By content analysis of the 17 sales lists/catalogs of books from Dubrovnik, Split, Zadar, Karlovac, Zagreb and Osijek, the classification structure has been reconstructed, and the criteria according to which the booksellers offerings have been classified in the early 20th century have been determined. Conducting of the analysis established the following criteria of the bookstore classification: topic/content, form/type of work, type of corpus, genre, language, purpose, publishing series, publisher, time of publication, (new edition, time of publication/purchase, customer's specific interests, number, letter and author. Order of enumeration within specific categories is mostly alphabetic, numeric or according to order of publication. Unlike the library classification and classification systems in general, the problematics of bookstore classification is not very present in the current existing sources. Research studies that focus on the history of bookselling, even if they reveal ways of classification of booksellers offers remain on a descriptive level without any deeper analysis of the criteria or possible reasons of such classification. Therefore, the contribution of the paper is a detailed analysis of a larger pattern of bookstore sales catalogs, and also an attempt of illuminating the criteria and reasons of creating a system of bookstore classification in the defined historical, spatial and time context.

  20. 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

  1. Medical X-ray Image Hierarchical Classification Using a Merging and Splitting Scheme in Feature Space.

    Science.gov (United States)

    Fesharaki, Nooshin Jafari; Pourghassem, Hossein

    2013-07-01

    Due to the daily mass production and the widespread variation of medical X-ray images, it is necessary to classify these for searching and retrieving proposes, especially for content-based medical image retrieval systems. In this paper, a medical X-ray image hierarchical classification structure based on a novel merging and splitting scheme and using shape and texture features is proposed. In the first level of the proposed structure, to improve the classification performance, similar classes with regard to shape contents are grouped based on merging measures and shape features into the general overlapped classes. In the next levels of this structure, the overlapped classes split in smaller classes based on the classification performance of combination of shape and texture features or texture features only. Ultimately, in the last levels, this procedure is also continued forming all the classes, separately. Moreover, to optimize the feature vector in the proposed structure, we use orthogonal forward selection algorithm according to Mahalanobis class separability measure as a feature selection and reduction algorithm. In other words, according to the complexity and inter-class distance of each class, a sub-space of the feature space is selected in each level and then a supervised merging and splitting scheme is applied to form the hierarchical classification. The proposed structure is evaluated on a database consisting of 2158 medical X-ray images of 18 classes (IMAGECLEF 2005 database) and accuracy rate of 93.6% in the last level of the hierarchical structure for an 18-class classification problem is obtained.

  2. Unsupervised classification of variable stars

    Science.gov (United States)

    Valenzuela, Lucas; Pichara, Karim

    2018-03-01

    During the past 10 years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric data sets where objects are represented as light curves. Classifiers require training sets to learn the underlying patterns that allow the separation among classes. Unfortunately, building training sets is an expensive process that demands a lot of human efforts. Every time data come from new surveys; the only available training instances are the ones that have a cross-match with previously labelled objects, consequently generating insufficient training sets compared with the large amounts of unlabelled sources. In this work, we present an algorithm that performs unsupervised classification of variable stars, relying only on the similarity among light curves. We tackle the unsupervised classification problem by proposing an untraditional approach. Instead of trying to match classes of stars with clusters found by a clustering algorithm, we propose a query-based method where astronomers can find groups of variable stars ranked by similarity. We also develop a fast similarity function specific for light curves, based on a novel data structure that allows scaling the search over the entire data set of unlabelled objects. Experiments show that our unsupervised model achieves high accuracy in the classification of different types of variable stars and that the proposed algorithm scales up to massive amounts of light curves.

  3. 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

  4. Boreal forest biomass classification with TanDEM-X

    OpenAIRE

    Torano Caicoya, Astor; Kugler, Florian; Papathanassiou, Kostas; Hajnsek, Irena

    2013-01-01

    High spatial resolution X-band interferometric SAR data from the TanDEM-X, in the operational DEM generation mode, are sensitive to forest structure and can therefore be used for thematic boreal forest classification of forest environments. The interferometric coherence in absence of temporal decorrelation depends strongly on forest height and structure. Due to the rather homogenous structure of boreal forest, forest biomass can be derived from forest height, on the basis of allometric equati...

  5. Deep learning for tumor classification in imaging mass spectrometry.

    Science.gov (United States)

    Behrmann, Jens; Etmann, Christian; Boskamp, Tobias; Casadonte, Rita; Kriegsmann, Jörg; Maaß, Peter

    2018-04-01

    Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to fully process the data. Since mass spectra exhibit certain structural similarities to image data, deep learning may offer a promising strategy for classification of IMS data as it has been successfully applied to image classification. Methodologically, we propose an adapted architecture based on deep convolutional networks to handle the characteristics of mass spectrometry data, as well as a strategy to interpret the learned model in the spectral domain based on a sensitivity analysis. The proposed methods are evaluated on two algorithmically challenging tumor classification tasks and compared to a baseline approach. Competitiveness of the proposed methods is shown on both tasks by studying the performance via cross-validation. Moreover, the learned models are analyzed by the proposed sensitivity analysis revealing biologically plausible effects as well as confounding factors of the considered tasks. Thus, this study may serve as a starting point for further development of deep learning approaches in IMS classification tasks. https://gitlab.informatik.uni-bremen.de/digipath/Deep_Learning_for_Tumor_Classification_in_IMS. jbehrmann@uni-bremen.de or christianetmann@uni-bremen.de. Supplementary data are available at Bioinformatics online.

  6. Classification of complex polynomial vector fields in one complex variable

    DEFF Research Database (Denmark)

    Branner, Bodil; Dias, Kealey

    2010-01-01

    This paper classifies the global structure of monic and centred one-variable complex polynomial vector fields. The classification is achieved by means of combinatorial and analytic data. More specifically, given a polynomial vector field, we construct a combinatorial invariant, describing...... the topology, and a set of analytic invariants, describing the geometry. Conversely, given admissible combinatorial and analytic data sets, we show using surgery the existence of a unique monic and centred polynomial vector field realizing the given invariants. This is the content of the Structure Theorem......, the main result of the paper. This result is an extension and refinement of Douady et al. (Champs de vecteurs polynomiaux sur C. Unpublished manuscript) classification of the structurally stable polynomial vector fields. We further review some general concepts for completeness and show that vector fields...

  7. Climatic classification of the Karst

    International Nuclear Information System (INIS)

    Eslava Ramirez Jesus Antonio; Bahamon Ayala, Sandra Marcela; Lopez Romero Maria Ines

    2000-01-01

    Climate is one the main factors in forming or modifying Karsts, or its resulting forms. The determining climatic elements of Karst characteristics are humidity, air circulation and temperature. Many Karstic processes show characteristics corresponding to a given climate sequence. In the present article we discuss the relation between climate and Karst as well as a climate classification based on the structure of the Karsts

  8. Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

    Science.gov (United States)

    Gholami, Raoof; Rasouli, Vamegh; Alimoradi, Andisheh

    2013-09-01

    Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.

  9. Trends and concepts in fern classification

    Science.gov (United States)

    Christenhusz, Maarten J. M.; Chase, Mark W.

    2014-01-01

    Background and Aims Throughout the history of fern classification, familial and generic concepts have been highly labile. Many classifications and evolutionary schemes have been proposed during the last two centuries, reflecting different interpretations of the available evidence. Knowledge of fern structure and life histories has increased through time, providing more evidence on which to base ideas of possible relationships, and classification has changed accordingly. This paper reviews previous classifications of ferns and presents ideas on how to achieve a more stable consensus. Scope An historical overview is provided from the first to the most recent fern classifications, from which conclusions are drawn on past changes and future trends. The problematic concept of family in ferns is discussed, with a particular focus on how this has changed over time. The history of molecular studies and the most recent findings are also presented. Key Results Fern classification generally shows a trend from highly artificial, based on an interpretation of a few extrinsic characters, via natural classifications derived from a multitude of intrinsic characters, towards more evolutionary circumscriptions of groups that do not in general align well with the distribution of these previously used characters. It also shows a progression from a few broad family concepts to systems that recognized many more narrowly and highly controversially circumscribed families; currently, the number of families recognized is stabilizing somewhere between these extremes. Placement of many genera was uncertain until the arrival of molecular phylogenetics, which has rapidly been improving our understanding of fern relationships. As a collective category, the so-called ‘fern allies’ (e.g. Lycopodiales, Psilotaceae, Equisetaceae) were unsurprisingly found to be polyphyletic, and the term should be abandoned. Lycopodiaceae, Selaginellaceae and Isoëtaceae form a clade (the lycopods) that is

  10. Trends and concepts in fern classification.

    Science.gov (United States)

    Christenhusz, Maarten J M; Chase, Mark W

    2014-03-01

    Throughout the history of fern classification, familial and generic concepts have been highly labile. Many classifications and evolutionary schemes have been proposed during the last two centuries, reflecting different interpretations of the available evidence. Knowledge of fern structure and life histories has increased through time, providing more evidence on which to base ideas of possible relationships, and classification has changed accordingly. This paper reviews previous classifications of ferns and presents ideas on how to achieve a more stable consensus. An historical overview is provided from the first to the most recent fern classifications, from which conclusions are drawn on past changes and future trends. The problematic concept of family in ferns is discussed, with a particular focus on how this has changed over time. The history of molecular studies and the most recent findings are also presented. Fern classification generally shows a trend from highly artificial, based on an interpretation of a few extrinsic characters, via natural classifications derived from a multitude of intrinsic characters, towards more evolutionary circumscriptions of groups that do not in general align well with the distribution of these previously used characters. It also shows a progression from a few broad family concepts to systems that recognized many more narrowly and highly controversially circumscribed families; currently, the number of families recognized is stabilizing somewhere between these extremes. Placement of many genera was uncertain until the arrival of molecular phylogenetics, which has rapidly been improving our understanding of fern relationships. As a collective category, the so-called 'fern allies' (e.g. Lycopodiales, Psilotaceae, Equisetaceae) were unsurprisingly found to be polyphyletic, and the term should be abandoned. Lycopodiaceae, Selaginellaceae and Isoëtaceae form a clade (the lycopods) that is sister to all other vascular plants, whereas

  11. Multi-information fusion sparse coding with preserving local structure for hyperspectral image classification

    Science.gov (United States)

    Wei, Xiaohui; Zhu, Wen; Liao, Bo; Gu, Changlong; Li, Weibiao

    2017-10-01

    The key question of sparse coding (SC) is how to exploit the information that already exists to acquire the robust sparse representations (SRs) of distinguishing different objects for hyperspectral image (HSI) classification. We propose a multi-information fusion SC framework, which fuses the spectral, spatial, and label information in the same level, to solve the above question. In particular, pixels from disjointed spatial clusters, which are obtained by cutting the given HSI in space, are individually and sparsely encoded. Then, due to the importance of spatial structure, graph- and hypergraph-based regularizers are enforced to motivate the obtained representations smoothness and to preserve the local consistency for each spatial cluster. The latter simultaneously considers the spectrum, spatial, and label information of multiple pixels that have a great probability with the same label. Finally, a linear support vector machine is selected as the final classifier with the learned SRs as input. Experiments conducted on three frequently used real HSIs show that our methods can achieve satisfactory results compared with other state-of-the-art methods.

  12. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  13. 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)

  14. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  15. Can high-energy proton events in solar wind be predicted via classification of precursory structures?

    Energy Technology Data Exchange (ETDEWEB)

    Hallerberg, Sarah [Chemnitz University of Technology (Germany); Ruzmaikin, Alexander; Feynman, Joan [Jet Propulsion Laboratory, California Institute of Technology (United States)

    2011-07-01

    Shock waves in the solar wind associated with solar coronal mass ejections produce fluxes of high-energy protons and ions with energies larger than 10 MeV. These fluxes present a danger to humans and electronic equipment in space, and also endanger passengers of over-pole air flights. The approaches that have been exploited for the prediction of high-energy particle events so far consist in training artificial neural networks on catalogues of events. Our approach towards this task is based on the identification of precursory structures in the fluxes of particles. In contrast to artificial neural networks that function as a ''black box'' transforming data into predictions, this classification approach can additionally provide information on relevant precursory events and thus might help to improve the understanding of underlying mechanisms of particle acceleration.

  16. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  17. A Study on Classification Cases in UAE BNPP Focused on Physical Breakdown Structure for the Establishment of Intelligent Export Control System

    International Nuclear Information System (INIS)

    Yang, Seung Hyo; Tae, Jae Woong; Shin, Dong Hoon

    2013-01-01

    NSG and the international society haven't suggested a clear standard for EDP, but recommended every member of NSG to establish their own standard and control strategic item export. As a result, it is hard to sustain objectivity and consistency in examining thousands of items and technologies related to nuclear power plants through the existing methods that classifies strategic items with limited human resources. Its long processing time may bring about a financial burden to the related companies as well. Accordingly, it is more required to establish Intelligent eXport Control System (IXCS) than ever before so that a great many of strategic items can be effectively processed. To provide basic data used to establish IXCS, this study analyzed classification cases of Braka Nuclear Power Plant (BNPP) in UAE mainly focusing on Physical Breakdown Structure (PBS). Due to commercial reactors exported to UAE and research reactors exported to Jordan, the number of classification requests is rapidly increasing in Korea. Therefore, it is required to develop IXCS that can assist an efficient and consistent decision on a great many classification request. This system will be developed to present the possibility that items could be strategic through analyzing characteristics (e.g. name, function, use, purpose, duplication, relation to nuclear activities, etc.). The result in this study that analyzed the linkage between PBS code and items, one of characteristics (use) cited above, will be used as weighting factor to classify items for developing the system. (e. g. PBS code 431 has weighting factor 0.7.) In addition, it can be more efficient to sort items which are likely to be strategic among all requests before processing classification requests growing exponentially. It is concluded that the linkage between PBS code and items will be used as filtering factor to select items which could be strategic accordingly. Henceforth, it is plan to derive highly reliable statistical results

  18. Advanced Steel Microstructural Classification by Deep Learning Methods.

    Science.gov (United States)

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

    2018-02-01

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

  19. Hierarchical vs non-hierarchical audio indexation and classification for video genres

    Science.gov (United States)

    Dammak, Nouha; BenAyed, Yassine

    2018-04-01

    In this paper, Support Vector Machines (SVMs) are used for segmenting and indexing video genres based on only audio features extracted at block level, which has a prominent asset by capturing local temporal information. The main contribution of our study is to show the wide effect on the classification accuracies while using an hierarchical categorization structure based on Mel Frequency Cepstral Coefficients (MFCC) audio descriptor. In fact, the classification consists in three common video genres: sports videos, music clips and news scenes. The sub-classification may divide each genre into several multi-speaker and multi-dialect sub-genres. The validation of this approach was carried out on over 360 minutes of video span yielding a classification accuracy of over 99%.

  20. Structural Analysis: Folds Classification of metasedimentary rock in the Peninsular Malaysia

    Science.gov (United States)

    Shamsuddin, A.

    2017-10-01

    Understanding shear zone characteristics of deformation are a crucial part in the oil and gas industry as it might increase the knowledge of the fracture characteristics and lead to the prediction of the location of fracture zones or fracture swarms. This zone might give high influence on reservoir performance. There are four general types of shear zones which are brittle, ductile, semibrittle and brittle-ductile transition zones. The objective of this study is to study and observe the structural geometry of the shear zones and its implication as there is a lack of understanding, especially in the subsurface area because of the limitation of seismic resolution. A field study was conducted on the metasedimentary rocks (shear zone) which are exposed along the coastal part of the Peninsular Malaysia as this type of rock resembles the types of rock in the subsurface. The analysis in this area shows three main types of rock which are non-foliated metaquartzite and foliated rock which can be divided into slate and phyllite. Two different fold classification can be determined in this study. Layer 1 with phyllite as the main type of rock can be classified in class 1C and layer 2 with slate as the main type of rock can be classified in class 1A. This study will benefit in predicting the characteristics of the fracture and fracture zones.

  1. Classification of domains of closed operators

    International Nuclear Information System (INIS)

    Lassner, G.; Timmermann, W.

    1975-01-01

    The structure of domains of determining closed operators in the Hilbert space by means of sequence spaces is investigated. The final classification provides three classes of these domains. Necessary and sufficient conditions of equivalence of these domains are obtained in the form of equivalency of corresponding sequences of natural numbers. Connection with the perturbation theory is mentioned [ru

  2. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  3. 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)

  4. A Comparative Analysis of Classification Algorithms on Diverse Datasets

    Directory of Open Access Journals (Sweden)

    M. Alghobiri

    2018-04-01

    Full Text Available Data mining involves the computational process to find patterns from large data sets. Classification, one of the main domains of data mining, involves known structure generalizing to apply to a new dataset and predict its class. There are various classification algorithms being used to classify various data sets. They are based on different methods such as probability, decision tree, neural network, nearest neighbor, boolean and fuzzy logic, kernel-based etc. In this paper, we apply three diverse classification algorithms on ten datasets. The datasets have been selected based on their size and/or number and nature of attributes. Results have been discussed using some performance evaluation measures like precision, accuracy, F-measure, Kappa statistics, mean absolute error, relative absolute error, ROC Area etc. Comparative analysis has been carried out using the performance evaluation measures of accuracy, precision, and F-measure. We specify features and limitations of the classification algorithms for the diverse nature datasets.

  5. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  6. Development of a definition, classification system, and model for cultural geology

    Science.gov (United States)

    Mitchell, Lloyd W., III

    The concept for this study is based upon a personal interest by the author, an American Indian, in promoting cultural perspectives in undergraduate college teaching and learning environments. Most academicians recognize that merged fields can enhance undergraduate curricula. However, conflict may occur when instructors attempt to merge social science fields such as history or philosophy with geoscience fields such as mining and geomorphology. For example, ideologies of Earth structures derived from scientific methodologies may conflict with historical and spiritual understandings of Earth structures held by American Indians. Specifically, this study addresses the problem of how to combine cultural studies with the geosciences into a new merged academic discipline called cultural geology. This study further attempts to develop the merged field of cultural geology using an approach consisting of three research foci: a definition, a classification system, and a model. Literature reviews were conducted for all three foci. Additionally, to better understand merged fields, a literature review was conducted specifically for academic fields that merged social and physical sciences. Methodologies concentrated on the three research foci: definition, classification system, and model. The definition was derived via a two-step process. The first step, developing keyword hierarchical ranking structures, was followed by creating and analyzing semantic word meaning lists. The classification system was developed by reviewing 102 classification systems and incorporating selected components into a system framework. The cultural geology model was created also utilizing a two-step process. A literature review of scientific models was conducted. Then, the definition and classification system were incorporated into a model felt to reflect the realm of cultural geology. A course syllabus was then developed that incorporated the resulting definition, classification system, and model. This

  7. Classification of childhood epilepsies in a tertiary pediatric neurology clinic using a customized classification scheme from the international league against epilepsy 2010 report.

    Science.gov (United States)

    Khoo, Teik-Beng

    2013-01-01

    In its 2010 report, the International League Against Epilepsy Commission on Classification and Terminology had made a number of changes to the organization, terminology, and classification of seizures and epilepsies. This study aims to test the usefulness of this revised classification scheme on children with epilepsies aged between 0 and 18 years old. Of 527 patients, 75.1% only had 1 type of seizure and the commonest was focal seizure (61.9%). A specific electroclinical syndrome diagnosis could be made in 27.5%. Only 2.1% had a distinctive constellation. In this cohort, 46.9% had an underlying structural, metabolic, or genetic etiology. Among the important causes were pre-/perinatal insults, malformation of cortical development, intracranial infections, and neurocutaneous syndromes. However, 23.5% of the patients in our cohort were classified as having "epilepsies of unknown cause." The revised classification scheme is generally useful for pediatric patients. To make it more inclusive and clinically meaningful, some local customizations are required.

  8. Solid state conformational classification of eight-membered rings

    DEFF Research Database (Denmark)

    Pérez, J.; García, L.; Kessler, M.

    2005-01-01

    A statistical classification of the solid state conformation in the title complexes using data retrieved from the Cambridge Structural Database (CSD) has been made. Phosphate and phosphinate complexes show a chair conformation preferably. In phosphonate complexes, the most frequent conformations...

  9. Subordinate-level object classification reexamined.

    Science.gov (United States)

    Biederman, I; Subramaniam, S; Bar, M; Kalocsai, P; Fiser, J

    1999-01-01

    The classification of a table as round rather than square, a car as a Mazda rather than a Ford, a drill bit as 3/8-inch rather than 1/4-inch, and a face as Tom have all been regarded as a single process termed "subordinate classification." Despite the common label, the considerable heterogeneity of the perceptual processing required to achieve such classifications requires, minimally, a more detailed taxonomy. Perceptual information relevant to subordinate-level shape classifications can be presumed to vary on continua of (a) the type of distinctive information that is present, nonaccidental or metric, (b) the size of the relevant contours or surfaces, and (c) the similarity of the to-be-discriminated features, such as whether a straight contour has to be distinguished from a contour of low curvature versus high curvature. We consider three, relatively pure cases. Case 1 subordinates may be distinguished by a representation, a geon structural description (GSD), specifying a nonaccidental characterization of an object's large parts and the relations among these parts, such as a round table versus a square table. Case 2 subordinates are also distinguished by GSDs, except that the distinctive GSDs are present at a small scale in a complex object so the location and mapping of the GSDs are contingent on an initial basic-level classification, such as when we use a logo to distinguish various makes of cars. Expertise for Cases 1 and 2 can be easily achieved through specification, often verbal, of the GSDs. Case 3 subordinates, which have furnished much of the grist for theorizing with "view-based" template models, require fine metric discriminations. Cases 1 and 2 account for the overwhelming majority of shape-based basic- and subordinate-level object classifications that people can and do make in their everyday lives. These classifications are typically made quickly, accurately, and with only modest costs of viewpoint changes. Whereas the activation of an array of

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

    Science.gov (United States)

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

    2011-01-01

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

  11. Significance of perceptually relevant image decolorization for scene classification

    Science.gov (United States)

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

    2017-11-01

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

  12. A classification scheme for risk assessment methods.

    Energy Technology Data Exchange (ETDEWEB)

    Stamp, Jason Edwin; Campbell, Philip LaRoche

    2004-08-01

    This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In

  13. PASTEC: an automatic transposable element classification tool.

    Directory of Open Access Journals (Sweden)

    Claire Hoede

    Full Text Available SUMMARY: The classification of transposable elements (TEs is key step towards deciphering their potential impact on the genome. However, this process is often based on manual sequence inspection by TE experts. With the wealth of genomic sequences now available, this task requires automation, making it accessible to most scientists. We propose a new tool, PASTEC, which classifies TEs by searching for structural features and similarities. This tool outperforms currently available software for TE classification. The main innovation of PASTEC is the search for HMM profiles, which is useful for inferring the classification of unknown TE on the basis of conserved functional domains of the proteins. In addition, PASTEC is the only tool providing an exhaustive spectrum of possible classifications to the order level of the Wicker hierarchical TE classification system. It can also automatically classify other repeated elements, such as SSR (Simple Sequence Repeats, rDNA or potential repeated host genes. Finally, the output of this new tool is designed to facilitate manual curation by providing to biologists with all the evidence accumulated for each TE consensus. AVAILABILITY: PASTEC is available as a REPET module or standalone software (http://urgi.versailles.inra.fr/download/repet/REPET_linux-x64-2.2.tar.gz. It requires a Unix-like system. There are two standalone versions: one of which is parallelized (requiring Sun grid Engine or Torque, and the other of which is not.

  14. 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.

  15. 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.

  16. Using ecological zones to increase the detail of Landsat classifications

    Science.gov (United States)

    Fox, L., III; Mayer, K. E.

    1981-01-01

    Changes in classification detail of forest species descriptions were made for Landsat data on 2.2 million acres in northwestern California. Because basic forest canopy structures may exhibit very similar E-M energy reflectance patterns in different environmental regions, classification labels based on Landsat spectral signatures alone become very generalized when mapping large heterogeneous ecological regions. By adding a seven ecological zone stratification, a 167% improvement in classification detail was made over the results achieved without it. The seven zone stratification is a less costly alternative to the inclusion of complex collateral information, such as terrain data and soil type, into the Landsat data base when making inventories of areas greater than 500,000 acres.

  17. Standard classification: Physics

    International Nuclear Information System (INIS)

    1977-01-01

    This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

  18. Progress in the diagnosis and classification of pituitary adenomas

    Directory of Open Access Journals (Sweden)

    Luis V Syro

    2015-06-01

    Full Text Available Pituitary adenomas are common neoplasms. Their classification is based upon size, invasion of adjacent structures, sporadic or familial cases, biochemical activity, clinical manifestations, morphological characteristics, response to treatment and recurrence. Although they are considered benign tumors, some of them are difficult to treat due to their tendency to recur, despite standardized treatment. Functional tumors present other challenges for normalizing their biochemical activity. Novel approaches for early diagnosis as well as different perspectives on classification may help to identify subgroups of patients with similar characteristics, creating opportunities to match each patient with the best personalized treatment option. In this paper we present the progress in the diagnosis and classification of different subgroups of patients with pituitary tumors that may be managed with specific considerations according to their tumor subtype.

  19. Classification and clinical features of primary headache in Akaki ...

    African Journals Online (AJOL)

    Classification and clinical features of primary headache in Akaki Textile Mill workers, ... study wherein data collection and examination of cases using a structured and ... like pressure or tightness with a mild to moderate intensity and anorexia.

  20. Structural classification of endogenous regulatory oligopeptides.

    Science.gov (United States)

    Zamyatnin, A A

    1991-07-01

    Based on the criteria of 50% identity in the amino acid sequence, a new method for grouping endogenous regulatory oligopeptides into structural families is presented. Data from the EROP-Moscow data bank on 579 oligopeptides fitting a preset spectrum of functional activities revealed 73 structural oligopeptide groups, 36 of which were called families.

  1. Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

    Directory of Open Access Journals (Sweden)

    Vasiliki eFolia

    2014-02-01

    Full Text Available In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45 and the medial prefrontal regions (centered on BA 8/32. Importantly, and central to this study, the inclusion of a naive preference FMRI baseline measurement allowed us to conclude that these FMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax in unsupervised AGL paradigms with proper learning designs.

  2. A novel approach to internal crown characterization for coniferous tree species classification

    Science.gov (United States)

    Harikumar, A.; Bovolo, F.; Bruzzone, L.

    2016-10-01

    The knowledge about individual trees in forest is highly beneficial in forest management. High density small foot- print multi-return airborne Light Detection and Ranging (LiDAR) data can provide a very accurate information about the structural properties of individual trees in forests. Every tree species has a unique set of crown structural characteristics that can be used for tree species classification. In this paper, we use both the internal and external crown structural information of a conifer tree crown, derived from a high density small foot-print multi-return LiDAR data acquisition for species classification. Considering the fact that branches are the major building blocks of a conifer tree crown, we obtain the internal crown structural information using a branch level analysis. The structure of each conifer branch is represented using clusters in the LiDAR point cloud. We propose the joint use of the k-means clustering and geometric shape fitting, on the LiDAR data projected onto a novel 3-dimensional space, to identify branch clusters. After mapping the identified clusters back to the original space, six internal geometric features are estimated using a branch-level analysis. The external crown characteristics are modeled by using six least correlated features based on cone fitting and convex hull. Species classification is performed using a sparse Support Vector Machines (sparse SVM) classifier.

  3. Internal representations for face detection: an application of noise-based image classification to BOLD responses.

    Science.gov (United States)

    Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

    2013-11-01

    What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.

  4. What are genres good for? Divisions, demarcations and classifications in structural and cognitive anthropology, on the example of music culture

    Directory of Open Access Journals (Sweden)

    Bojan Žikić

    2016-02-01

    Full Text Available Levi-Strauss’s theoretical-methodological "legatee" – anthropological structuralism was one of the most important theoretical frameworks used in cognitive anthropology. Since it was sometimes too abstract for ‘practical’ minds, trained in British-American empirical traditions, Levi-Strauss thought was mediated through the works of British structural-functionalist, particularly those of Mary Douglas and Edmund Leach, who established its premises as a kind of contextualised particularism of the unquestioned universalism. Ideas about the way in which human cultural mind functions, is one of the corner stones of cognitive anthropology, which cognitive anthropology shares with structural anthropology, and from which cognitive anthropology actually inherits what it shares with structural anthropology – this sounds properly structural – that is: an interest in the processes of division, demarcation and classification in a sense of cultural management of a perceived surrounding reality. An example for such analysis, that I use in this paper, is music, or more precisely music culture, an expression that I use in order to imply that the affinity to a type of music, or musical genre should be understood in a sense of a particular cultural way of thinking and acting.

  5. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

  6. 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)...

  7. Classification of protein fold classes by knot theory and prediction of folds by neural networks: A combined theoretical and experimental approach

    DEFF Research Database (Denmark)

    Ramnarayan, K.; Bohr, Henrik; Jalkanen, Karl J.

    2008-01-01

    We present different means of classifying protein structure. One is made rigorous by mathematical knot invariants that coincide reasonably well with ordinary graphical fold classification and another classification is by packing analysis. Furthermore when constructing our mathematical fold...... classifications, we utilize standard neural network methods for predicting protein fold classes from amino acid sequences. We also make an analysis of the redundancy of the structural classifications in relation to function and ligand binding. Finally we advocate the use of combining the measurement of the VA...

  8. Tree Classification with Fused Mobile Laser Scanning and Hyperspectral Data

    Science.gov (United States)

    Puttonen, Eetu; Jaakkola, Anttoni; Litkey, Paula; Hyyppä, Juha

    2011-01-01

    Mobile Laser Scanning data were collected simultaneously with hyperspectral data using the Finnish Geodetic Institute Sensei system. The data were tested for tree species classification. The test area was an urban garden in the City of Espoo, Finland. Point clouds representing 168 individual tree specimens of 23 tree species were determined manually. The classification of the trees was done using first only the spatial data from point clouds, then with only the spectral data obtained with a spectrometer, and finally with the combined spatial and hyperspectral data from both sensors. Two classification tests were performed: the separation of coniferous and deciduous trees, and the identification of individual tree species. All determined tree specimens were used in distinguishing coniferous and deciduous trees. A subset of 133 trees and 10 tree species was used in the tree species classification. The best classification results for the fused data were 95.8% for the separation of the coniferous and deciduous classes. The best overall tree species classification succeeded with 83.5% accuracy for the best tested fused data feature combination. The respective results for paired structural features derived from the laser point cloud were 90.5% for the separation of the coniferous and deciduous classes and 65.4% for the species classification. Classification accuracies with paired hyperspectral reflectance value data were 90.5% for the separation of coniferous and deciduous classes and 62.4% for different species. The results are among the first of their kind and they show that mobile collected fused data outperformed single-sensor data in both classification tests and by a significant margin. PMID:22163894

  9. IMPROVING CLASSIFICATIONS OF ECONOMIC SCIENCES IN A THESAURUS

    Directory of Open Access Journals (Sweden)

    Sergey Vladimirovich Lesnikov

    2013-09-01

    Full Text Available The goal is to study thesaurus as an instrument to define the classification of economic sciences, to adapt their classification to the increased information flow, to increase accuracy of allocation of information resources with consideration of the users’ needs, to suggest making alterations in the classification of economic sciences made by the Institute of Scientific Information for Social Sciences of the Russian Academy of Sciences (INION RAN in 2001.The authors see the classification of economic sciences as a product of social communications theory – a differentiated aspect of social research. Modern science is subdivided into various aspects with varied subjects and methods. The latter overlap and form a hierarchy of concepts in science within the same research subject. The authors stress the importance of information retrieval systems for developing scientific knowledge. Information retrieval systems can immediately deliver data from different areas of science to the user who can then integrate the information and obtain a vivid picture of the research subject. Search engines and rubricators are becoming increasingly important as there is a tendency to isolated thinking with many Internet users.The authors have devised a certain approach to using the thesaurus as the means of sciences classification and as a hyper language of science. The suggested methodological approach to structuring terms and notions via thesaurus have been tested at Syktyvkar State University and Syktyvkar branch of Saint-Petersburg Economic University.Methods: deduction, induction, analysis, synthesis, abstraction technique, classification.Results: there have been defined stages and main sections of the information-retrieval thesaurus of the hyperlanguage of economic science on the basis of existing classification systems of scientific knowledge.Scope of application of results: library services, information technology, education.DOI: http://dx.doi.org/10.12731/2218-7405-2013-8-22

  10. Classification of non-performing loans portfolio using Multilayer Perceptron artificial neural networks

    Directory of Open Access Journals (Sweden)

    Flávio Clésio Silva de Souza

    2014-06-01

    Full Text Available The purpose of the present research is to apply a Multilayer Perceptron (MLP neural network technique to create classification models from a portfolio of Non-Performing Loans (NPLs to classify this type of credit derivative. These credit derivatives are characterized as the amount of loans that were not paid and are already overdue more than 90 days. Since these titles are, because of legislative motives, moved by losses, Credit Rights Investment Funds (FDIC performs the purchase of these debts and the recovery of the credits. Using the Multilayer Perceptron (MLP architecture of Artificial Neural Network (ANN, classification models regarding the posterior recovery of these debts were created. To evaluate the performance of the models, evaluation metrics of classification relating to the neural networks with different architectures were presented. The results of the classifications were satisfactory, given the classification models were successful in the presented economics costs structure.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jürgens, Björn, E-mail: bjurgens@agenciaidea.es [Agency of Innovation and Development of Andalusia, CITPIA PATLIB Centre (Spain); Herrero-Solana, Victor, E-mail: victorhs@ugr.es [University of Granada, SCImago-UGR (SEJ036) (Spain)

    2017-04-15

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

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

    International Nuclear Information System (INIS)

    Jürgens, Björn; Herrero-Solana, Victor

    2017-01-01

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

  13. Domain Adaptation for Opinion Classification: A Self-Training Approach

    Directory of Open Access Journals (Sweden)

    Yu, Ning

    2013-03-01

    Full Text Available Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

  14. Semi-Supervised Learning for Classification of Protein Sequence Data

    Directory of Open Access Journals (Sweden)

    Brian R. King

    2008-01-01

    Full Text Available Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.

  15. Low-Rank Sparse Coding for Image Classification

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Xu, Changsheng; Ahuja, Narendra

    2013-01-01

    In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

  16. Low-Rank Sparse Coding for Image Classification

    KAUST Repository

    Zhang, Tianzhu

    2013-12-01

    In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local structure information among features in an image for the purpose of image-level classification. LRSC represents densely sampled SIFT descriptors, in a spatial neighborhood, collectively as low-rank, sparse linear combinations of code words. As such, it casts the feature coding problem as a low-rank matrix learning problem, which is different from previous methods that encode features independently. This LRSC has a number of attractive properties. (1) It encourages sparsity in feature codes, locality in codebook construction, and low-rankness for spatial consistency. (2) LRSC encodes local features jointly by considering their low-rank structure information, and is computationally attractive. We evaluate the LRSC by comparing its performance on a set of challenging benchmarks with that of 7 popular coding and other state-of-the-art methods. Our experiments show that by representing local features jointly, LRSC not only outperforms the state-of-the-art in classification accuracy but also improves the time complexity of methods that use a similar sparse linear representation model for feature coding.

  17. New Course Design: Classification Schemes and Information Architecture.

    Science.gov (United States)

    Weinberg, Bella Hass

    2002-01-01

    Describes a course developed at St. John's University (New York) in the Division of Library and Information Science that relates traditional classification schemes to information architecture and Web sites. Highlights include functional aspects of information architecture, that is, the way content is structured; assignments; student reactions; and…

  18. Optimized Neural Network for Fault Diagnosis and Classification

    International Nuclear Information System (INIS)

    Elaraby, S.M.

    2005-01-01

    This paper presents a developed and implemented toolbox for optimizing neural network structure of fault diagnosis and classification. Evolutionary algorithm based on hierarchical genetic algorithm structure is used for optimization. The simplest feed-forward neural network architecture is selected. Developed toolbox has friendly user interface. Multiple solutions are generated. The performance and applicability of the proposed toolbox is verified with benchmark data patterns and accident diagnosis of Egyptian Second research reactor (ETRR-2)

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

    Science.gov (United States)

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

    1990-01-01

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

  20. A renewed perspective on agroforestry concepts and classification.

    Science.gov (United States)

    Torquebiau, E F

    2000-11-01

    Agroforestry, the association of trees with farming practices, is progressively becoming a recognized land-use discipline. However, it is still perceived by some scientists, technicians and farmers as a sort of environmental fashion which does not deserve credit. The peculiar history of agroforestry and the complex relationships between agriculture and forestry explain some misunderstandings about the concepts and classification of agroforestry and reveal that, contrarily to common perception, agroforestry is closer to agriculture than to forestry. Based on field experience from several countries, a structural classification of agroforestry into six simple categories is proposed: crops under tree cover, agroforests, agroforestry in a linear arrangement, animal agroforestry, sequential agroforestry and minor agroforestry techniques. It is argued that this pragmatic classification encompasses all major agroforestry associations and allows simultaneous agroforestry to be clearly differentiated from sequential agroforestry, two categories showing contrasting ecological tree-crop interactions. It can also contribute to a betterment of the image of agroforestry and lead to a simplification of its definition.

  1. Underwater object classification using scattering transform of sonar signals

    Science.gov (United States)

    Saito, Naoki; Weber, David S.

    2017-08-01

    In this paper, we apply the scattering transform (ST)-a nonlinear map based off of a convolutional neural network (CNN)-to classification of underwater objects using sonar signals. The ST formalizes the observation that the filters learned by a CNN have wavelet-like structure. We achieve effective binary classification both on a real dataset of Unexploded Ordinance (UXOs), as well as synthetically generated examples. We also explore the effects on the waveforms with respect to changes in the object domain (e.g., translation, rotation, and acoustic impedance, etc.), and examine the consequences coming from theoretical results for the scattering transform. We show that the scattering transform is capable of excellent classification on both the synthetic and real problems, thanks to having more quasi-invariance properties that are well-suited to translation and rotation of the object.

  2. HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Vestergaard, Jacob Schack; Larsen, Rasmus

    2014-01-01

    We present a new method for automatic classification of indirect immunoflourescence images of HEp-2 cells into different staining pattern classes. Our method is based on a new texture measure called shape index histograms that captures second-order image structure at multiple scales. Moreover, we...... datasets. Our results show that shape index histograms are superior to other popular texture descriptors for HEp-2 cell classification. Moreover, when comparing to other automated systems for HEp-2 cell classification we show that shape index histograms are very competitive; especially considering...

  3. Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel based ‘mouse pup syllable classification calculator’

    Directory of Open Access Journals (Sweden)

    Jasmine eGrimsley

    2013-01-01

    Full Text Available Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified ten syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

  4. Introduction of a methodology for visualization and graphical interpretation of Bayesian classification models.

    Science.gov (United States)

    Balfer, Jenny; Bajorath, Jürgen

    2014-09-22

    Supervised machine learning models are widely used in chemoinformatics, especially for the prediction of new active compounds or targets of known actives. Bayesian classification methods are among the most popular machine learning approaches for the prediction of activity from chemical structure. Much work has focused on predicting structure-activity relationships (SARs) on the basis of experimental training data. By contrast, only a few efforts have thus far been made to rationalize the performance of Bayesian or other supervised machine learning models and better understand why they might succeed or fail. In this study, we introduce an intuitive approach for the visualization and graphical interpretation of naïve Bayesian classification models. Parameters derived during supervised learning are visualized and interactively analyzed to gain insights into model performance and identify features that determine predictions. The methodology is introduced in detail and applied to assess Bayesian modeling efforts and predictions on compound data sets of varying structural complexity. Different classification models and features determining their performance are characterized in detail. A prototypic implementation of the approach is provided.

  5. Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

    Science.gov (United States)

    Folia, Vasiliki; Petersson, Karl Magnus

    2014-01-01

    In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

  6. Classification of Region’s Municipalities by Structure and Level of Incomes and Consumer Spending

    Directory of Open Access Journals (Sweden)

    Vladislav Yakovlevich Fokin

    2015-11-01

    Full Text Available The paper presents a classification of region’s municipalities that differ according to two criteria – the structure and level of incomes, and the level of consumer spending. The author investigated the combination of income sources (wages, pensions and unemployment benefits that form in the aggregate the amount of disposable money income of the people who live in the administrative-territorial units of Perm Krai. The author also analyzed the influence of people’s incomes on retail trade turnover in the region’s municipalities. The data were collected, grouped and analyzed; they show that the level of people’s income in large and medium cities, which are industrial centers, exceeds considerably the values of these indicators registered in rural municipalities, single-industry settlements and depressed areas. The reason for this lies in low wages of working population, a large proportion of retirees and the unemployed in the rural areas, single-industry settlements and depressed areas. The article defines nine types of territorial entities in the region that differ in level and structure of income and consumer spending in the municipalities. The author concludes that the territorial differentiation of municipal formations influences the formation of stratified population groups distinguished by the level of income and consumption. The solution to this problem requires joint efforts by the regional administration and municipal authorities to develop management actions with regard to specific features of each municipality

  7. 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.

  8. Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder.

    Science.gov (United States)

    Mwangi, Benson; Ebmeier, Klaus P; Matthews, Keith; Steele, J Douglas

    2012-05-01

    Quantitative abnormalities of brain structure in patients with major depressive disorder have been reported at a group level for decades. However, these structural differences appear subtle in comparison with conventional radiologically defined abnormalities, with considerable inter-subject variability. Consequently, it has not been possible to readily identify scans from patients with major depressive disorder at an individual level. Recently, machine learning techniques such as relevance vector machines and support vector machines have been applied to predictive classification of individual scans with variable success. Here we describe a novel hybrid method, which combines machine learning with feature selection and characterization, with the latter aimed at maximizing the accuracy of machine learning prediction. The method was tested using a multi-centre dataset of T(1)-weighted 'structural' scans. A total of 62 patients with major depressive disorder and matched controls were recruited from referred secondary care clinical populations in Aberdeen and Edinburgh, UK. The generalization ability and predictive accuracy of the classifiers was tested using data left out of the training process. High prediction accuracy was achieved (~90%). While feature selection was important for maximizing high predictive accuracy with machine learning, feature characterization contributed only a modest improvement to relevance vector machine-based prediction (~5%). Notably, while the only information provided for training the classifiers was T(1)-weighted scans plus a categorical label (major depressive disorder versus controls), both relevance vector machine and support vector machine 'weighting factors' (used for making predictions) correlated strongly with subjective ratings of illness severity. These results indicate that machine learning techniques have the potential to inform clinical practice and research, as they can make accurate predictions about brain scan data from

  9. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

    Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

  10. Classification and expression analyses of homeobox genes from ...

    Indian Academy of Sciences (India)

    We present here the first genome-wide classification and comparative genomic analysis of the 14 homeobox genes present in D. discoideum. Based on the structural alignment of the homeodomains, they can be broadly divided into TALE and non-TALE classes. When individual homeobox genes were compared with ...

  11. A Structural and Functional Acromegaly Classification

    Science.gov (United States)

    Cuevas-Ramos, Daniel; Carmichael, John D.; Cooper, Odelia; Bonert, Vivien S.; Gertych, Arkadiusz; Mamelak, Adam N.

    2015-01-01

    Context: GH-secreting pituitary adenomas exhibit heterogeneous natural history ranging from small tumors to large aggressive adenomas. Objective: To rigorously classify an acromegaly patient cohort defined by clinical, radiological, histopathological, and outcome characteristics. Design: Cross-sectional study. Setting: Tertiary referral pituitary center. Patients: Subjects were selected from a pituitary tumor research registry that includes 1178 patients with pituitary disease. Cluster analysis was performed on 338 acromegaly patients. Interventions: None. Main Outcome Measures: Biochemically active disease with elevated IGF-1 levels at follow-up. Results: Cluster analysis of all patients yielded 292 who were rigorously classified to three acromegaly types. Type 1 (50%) comprised older patients with the longest follow-up and most favorable outcomes, characterized by densely granulated, nonaggressive microadenomas and macroadenomas. Type 1 tumors extend to the sphenoid sinus more frequently than suprasellar extension (concave tumor image) and express abundant immunoreactive p21 and somatostatin receptor 2. Type 2 (19%) comprised noninvasive, densely or sparsely granulated macroadenomas, without significant extension (flat tumor image), with intermediate biochemical outcome. Type 3 (31%) was characterized by sparsely granulated aggressive macroadenomas and comprised patients with adverse therapeutic outcomes, despite receiving more treatments. These tumors extend to both the sphenoid sinus and suprasellar regions with commonly encountered optic chiasm compression (“peanut” magnetic resonance image), with low tumor p21 and somatostatin receptor 2 expression. Conclusions: After validation, this classification may be useful to accurately identify acromegaly patients with distinctive patterns of disease aggressiveness and outcome, as well as to provide an accurate tool for selection criteria in clinical studies. PMID:25250634

  12. Dimensional Representation and Gradient Boosting for Seismic Event Classification

    Science.gov (United States)

    Semmelmayer, F. C.; Kappedal, R. D.; Magana-Zook, S. A.

    2017-12-01

    In this research, we conducted experiments of representational structures on 5009 seismic signals with the intent of finding a method to classify signals as either an explosion or an earthquake in an automated fashion. We also applied a gradient boosted classifier. While perfect classification was not attained (approximately 88% was our best model), some cases demonstrate that many events can be filtered out as very high probability being explosions or earthquakes, diminishing subject-matter experts'(SME) workload for first stage analysis. It is our hope that these methods can be refined, further increasing the classification probability.

  13. Supervised Self-Organizing Classification of Superresolution ISAR Images: An Anechoic Chamber Experiment

    Directory of Open Access Journals (Sweden)

    Radoi Emanuel

    2006-01-01

    Full Text Available The problem of the automatic classification of superresolution ISAR images is addressed in the paper. We describe an anechoic chamber experiment involving ten-scale-reduced aircraft models. The radar images of these targets are reconstructed using MUSIC-2D (multiple signal classification method coupled with two additional processing steps: phase unwrapping and symmetry enhancement. A feature vector is then proposed including Fourier descriptors and moment invariants, which are calculated from the target shape and the scattering center distribution extracted from each reconstructed image. The classification is finally performed by a new self-organizing neural network called SART (supervised ART, which is compared to two standard classifiers, MLP (multilayer perceptron and fuzzy KNN ( nearest neighbors. While the classification accuracy is similar, SART is shown to outperform the two other classifiers in terms of training speed and classification speed, especially for large databases. It is also easier to use since it does not require any input parameter related to its structure.

  14. Enhanced manifold regularization for semi-supervised classification.

    Science.gov (United States)

    Gan, Haitao; Luo, Zhizeng; Fan, Yingle; Sang, Nong

    2016-06-01

    Manifold regularization (MR) has become one of the most widely used approaches in the semi-supervised learning field. It has shown superiority by exploiting the local manifold structure of both labeled and unlabeled data. The manifold structure is modeled by constructing a Laplacian graph and then incorporated in learning through a smoothness regularization term. Hence the labels of labeled and unlabeled data vary smoothly along the geodesics on the manifold. However, MR has ignored the discriminative ability of the labeled and unlabeled data. To address the problem, we propose an enhanced MR framework for semi-supervised classification in which the local discriminative information of the labeled and unlabeled data is explicitly exploited. To make full use of labeled data, we firstly employ a semi-supervised clustering method to discover the underlying data space structure of the whole dataset. Then we construct a local discrimination graph to model the discriminative information of labeled and unlabeled data according to the discovered intrinsic structure. Therefore, the data points that may be from different clusters, though similar on the manifold, are enforced far away from each other. Finally, the discrimination graph is incorporated into the MR framework. In particular, we utilize semi-supervised fuzzy c-means and Laplacian regularized Kernel minimum squared error for semi-supervised clustering and classification, respectively. Experimental results on several benchmark datasets and face recognition demonstrate the effectiveness of our proposed method.

  15. Classification of maxillectomy defects: a systematic review and criteria necessary for a universal description.

    Science.gov (United States)

    Bidra, Avinash S; Jacob, Rhonda F; Taylor, Thomas D

    2012-04-01

    Maxillectomy defects are complex and involve a number of anatomic structures. Several maxillectomy defect classifications have been proposed with no universal acceptance among surgeons and prosthodontists. Established criteria for describing the maxillectomy defect are lacking. This systematic review aimed to evaluate classification systems in the available literature, to provide a critical appraisal, and to identify the criteria necessary for a universal description of maxillectomy and midfacial defects. An electronic search of the English language literature between the periods of 1974 and June 2011 was performed by using PubMed, Scopus, and Cochrane databases with predetermined inclusion criteria. Key terms included in the search were maxillectomy classification, maxillary resection classification, maxillary removal classification, maxillary reconstruction classification, midfacial defect classification, and midfacial reconstruction classification. This was supplemented by a manual search of selected journals. After application of predetermined exclusion criteria, the final list of articles was reviewed in-depth to provide a critical appraisal and identify criteria for a universal description of a maxillectomy defect. The electronic database search yielded 261 titles. Systematic application of inclusion and exclusion criteria resulted in identification of 14 maxillectomy and midfacial defect classification systems. From these articles, 6 different criteria were identified as necessary for a universal description of a maxillectomy defect. Multiple deficiencies were noted in each classification system. Though most articles described the superior-inferior extent of the defect, only a small number of articles described the anterior-posterior and medial-lateral extent of the defect. Few articles listed dental status and soft palate involvement when describing maxillectomy defects. No classification system has accurately described the maxillectomy defect, based on

  16. Sound classification of dwellings in the Nordic countries – Differences and similarities between the five national schemes

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    having several similarities. In 2012, status is that number and denotations of classes for dwellings are identical in the Nordic countries, but the structures of the standards and several details are quite different. Also the issues dealt with are different. Examples of differences are sound insulation...... for classification of such buildings. This paper presents and compares the main class criteria for sound insulation of dwellings and summarizes differences and similarities in criteria and in structures of standards. Classification schemes for dwellings also exist in several other countries in Europe......In all five Nordic countries, sound classification schemes for dwellings have been published in national standards being implemented and revised gradually since the late 1990s. The national classification criteria for dwellings originate from a common Nordic INSTA-B proposal from the 1990s, thus...

  17. Predicting allergic contact dermatitis: a hierarchical structure activity relationship (SAR) approach to chemical classification using topological and quantum chemical descriptors

    Science.gov (United States)

    Basak, Subhash C.; Mills, Denise; Hawkins, Douglas M.

    2008-06-01

    A hierarchical classification study was carried out based on a set of 70 chemicals—35 which produce allergic contact dermatitis (ACD) and 35 which do not. This approach was implemented using a regular ridge regression computer code, followed by conversion of regression output to binary data values. The hierarchical descriptor classes used in the modeling include topostructural (TS), topochemical (TC), and quantum chemical (QC), all of which are based solely on chemical structure. The concordance, sensitivity, and specificity are reported. The model based on the TC descriptors was found to be the best, while the TS model was extremely poor.

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

    Science.gov (United States)

    Soergel, Dagobert

    2001-01-01

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

  19. Couinaud's classification v.s. Cho's classification. Their feasibility in the right hepatic lobe

    International Nuclear Information System (INIS)

    Shioyama, Yasukazu; Ikeda, Hiroaki; Sato, Motohito; Yoshimi, Fuyo; Kishi, Kazushi; Sato, Morio; Kimura, Masashi

    2008-01-01

    The objective of this study was to investigate if the new classification system proposed by Cho is feasible to clinical usage comparing with the classical Couinaud's one. One hundred consecutive cases of abdominal CT were studied using a 64 or an 8 slice multislice CT and created three dimensional portal vein images for analysis by the Workstation. We applied both Cho's classification and the classical Couinaud's one for each cases according to their definitions. Three diagnostic radiologists assessed their feasibility as category one (unable to classify) to five (clear to classify with total suit with the original classification criteria). And in each cases, we tried to judge whether Cho's or the classical Couinaud' classification could more easily transmit anatomical information. Analyzers could classified portal veins clearly (category 5) in 77 to 80% of cases and clearly (category 5) or almost clearly (category 4) in 86-93% along with both classifications. In the feasibility of classification, there was no statistically significant difference between two classifications. In 15 cases we felt that using Couinaud's classification is more convenient for us to transmit anatomical information to physicians than using Cho's one, because in these cases we noticed two large portal veins ramify from right main portal vein cranialy and caudaly and then we could not classify P5 as a branch of antero-ventral segment (AVS). Conversely in 17 cases we felt Cho's classification is more convenient because we could not divide right posterior branch as P6 and P7 and in these cases the right posterior portal vein ramified to several small branches. The anterior fissure vein was clearly noticed in only 60 cases. Comparing the classical Couinaud's classification and Cho's one in feasility of classification, there was no statistically significant difference. We propose we routinely report hepatic anatomy with the classical Couinauds classification and in the preoperative cases we

  20. Algorithms and data structures for automated change detection and classification of sidescan sonar imagery

    Science.gov (United States)

    Gendron, Marlin Lee

    During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author's Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3--48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author's repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the

  1. Some Issues in the Automatic Classification of U.S. Patents Working Notes for the AAAI-98 Workshop on Learning for Text Categorization

    National Research Council Canada - National Science Library

    Larkey, Leah

    1998-01-01

    The classification of U.S. patents poses some special problems due to the enormous size of the corpus, the size and complex hierarchical structure of the classification system, and the size and structure of patent documents...

  2. Classification with support hyperplanes

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

    2006-01-01

    textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

  3. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

    Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

  4. DOE LLW classification rationale

    International Nuclear Information System (INIS)

    Flores, A.Y.

    1991-01-01

    This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems

  5. Multi-Cohort Stand Structural Classification: Ground- and LiDAR-based Approaches for Boreal Mixedwood and Black Spruce Forest Types of Northeastern Ontario

    Science.gov (United States)

    Kuttner, Benjamin George

    Natural fire return intervals are relatively long in eastern Canadian boreal forests and often allow for the development of stands with multiple, successive cohorts of trees. Multi-cohort forest management (MCM) provides a strategy to maintain such multi-cohort stands that focuses on three broad phases of increasingly complex, post-fire stand development, termed "cohorts", and recommends different silvicultural approaches be applied to emulate different cohort types. Previous research on structural cohort typing has relied upon primarily subjective classification methods; in this thesis, I develop more comprehensive and objective methods for three common boreal mixedwood and black spruce forest types in northeastern Ontario. Additionally, I examine relationships between cohort types and stand age, productivity, and disturbance history and the utility of airborne LiDAR to retrieve ground-based classifications and to extend structural cohort typing from plot- to stand-levels. In both mixedwood and black spruce forest types, stand age and age-related deadwood features varied systematically with cohort classes in support of an age-based interpretation of increasing cohort complexity. However, correlations of stand age with cohort classes were surprisingly weak. Differences in site productivity had a significant effect on the accrual of increasingly complex multi-cohort stand structure in both forest types, especially in black spruce stands. The effects of past harvesting in predictive models of class membership were only significant when considered in isolation of age. As an age-emulation strategy, the three cohort model appeared to be poorly suited to black spruce forests where the accrual of structural complexity appeared to be more a function of site productivity than age. Airborne LiDAR data appear to be particularly useful in recovering plot-based cohort types and extending them to the stand-level. The main gradients of structural variability detected using Li

  6. Post-industrial landscape - its identification and classification as contemporary challenges faced by geographic research

    Czech Academy of Sciences Publication Activity Database

    Kolejka, Jaromír

    2010-01-01

    Roč. 14, č. 2 (2010), s. 67-78 ISSN 1842-5135 Institutional research plan: CEZ:AV0Z30860518 Keywords : classification * geographical research * identification method * landscape structure Subject RIV: DE - Earth Magnetism, Geodesy, Geography http://studiacrescent.com/images/02_2010/09_jaromir_kolejka_post_industrial_landscape_its_identification_and_classification_as_contemporary_challenges_faced_by_geographic_.pdf

  7. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  8. Fluorescently labeled bevacizumab in human breast cancer: defining the classification threshold

    Science.gov (United States)

    Koch, Maximilian; de Jong, Johannes S.; Glatz, Jürgen; Symvoulidis, Panagiotis; Lamberts, Laetitia E.; Adams, Arthur L. L.; Kranendonk, Mariëtte E. G.; Terwisscha van Scheltinga, Anton G. T.; Aichler, Michaela; Jansen, Liesbeth; de Vries, Jakob; Lub-de Hooge, Marjolijn N.; Schröder, Carolien P.; Jorritsma-Smit, Annelies; Linssen, Matthijs D.; de Boer, Esther; van der Vegt, Bert; Nagengast, Wouter B.; Elias, Sjoerd G.; Oliveira, Sabrina; Witkamp, Arjen J.; Mali, Willem P. Th. M.; Van der Wall, Elsken; Garcia-Allende, P. Beatriz; van Diest, Paul J.; de Vries, Elisabeth G. E.; Walch, Axel; van Dam, Gooitzen M.; Ntziachristos, Vasilis

    2017-07-01

    In-vivo fluorescently labelled drug (bevacizumab) breast cancer specimen where obtained from patients. We propose a new structured method to determine the optimal classification threshold in targeted fluorescence intra-operative imaging.

  9. Improving Hyperspectral Image Classification Method for Fine Land Use Assessment Application Using Semisupervised Machine Learning

    Directory of Open Access Journals (Sweden)

    Chunyang Wang

    2015-01-01

    Full Text Available Study on land use/cover can reflect changing rules of population, economy, agricultural structure adjustment, policy, and traffic and provide better service for the regional economic development and urban evolution. The study on fine land use/cover assessment using hyperspectral image classification is a focal growing area in many fields. Semisupervised learning method which takes a large number of unlabeled samples and minority labeled samples, improving classification and predicting the accuracy effectively, has been a new research direction. In this paper, we proposed improving fine land use/cover assessment based on semisupervised hyperspectral classification method. The test analysis of study area showed that the advantages of semisupervised classification method could improve the high precision overall classification and objective assessment of land use/cover results.

  10. Decomposition and classification of electroencephalography data

    DEFF Research Database (Denmark)

    Frølich, Laura

    . To enforce orthonormality of projection matrices, objective functions quantifying class discrimination were optimised on a cross-product of Stiefel (orthonormal matrix) manifolds. Supervised feature extraction outperformed unsupervised methods, but the choice of supervised method mattered less. We suggested......_MARC was also used to inspect effects of artefacts on motor imagery based Brain-Computer Interfaces (BCIs) in two studies, where removing artefactual ICs had little performance impact. Finally, we investigated multi-linear classification on single trials of EEG data, proposing a rigorous optimisation approach...... completions of methods to include both PARAFAC and Tucker structures. The two structures provided similar performances, making the more interpretable PARAFAC models appealing....

  11. [Classification of gamblers from self-help groups using cluster analysis].

    Science.gov (United States)

    Meyer, G

    1991-01-01

    In an empirically based classification by cluster analysis of 437 gamblers from self-help groups five distinct homogeneous subgroups were determined on the basis of such characteristics as frequency of gambling of various kinds, function of gambling and sensation during gambling, symptoms of pathological gambling as well as personality characteristics. These can be characterized as: Pathological slot-machine gamblers with 1) an emotionally instable, depressive-aggressive personality structure and 2) an emotionally instable, depressive personality structure; 3) pathological gamblers on German-style slot-machines and 4) pathological gamblers on classical games of chance--both without conspicuous personality, and 5) gamblers on German-style slot-machines under a subjective strain. On the whole, the distinctions are due to psychological variables, the social data hardly differ. A comparison of the subgroups on the basis of variables regarding the course and result of treatment shows that the pathological gamblers with a conspicuous personality structure more often failed to reach, the goal of abstinence set by "Gamblers Anonymous" and instead report about an improvement of their gambling behaviour. On the other hand, the gamblers on German-style slot-machines who were under a subjective strain more often found it easier to stop gambling completely. The results of the cluster analysis are compared with clinical diagnostic classifications of gamblers who received out-patient or in-patient treatment as well as with empirical classifications of addicts, and first hypotheses of a differential therapy indication are being discussed.

  12. 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 ...

  13. Relation Classification via Recurrent Neural Network

    OpenAIRE

    Zhang, Dongxu; Wang, Dong

    2015-01-01

    Deep learning has gained much success in sentence-level relation classification. For example, convolutional neural networks (CNN) have delivered competitive performance without much effort on feature engineering as the conventional pattern-based methods. Thus a lot of works have been produced based on CNN structures. However, a key issue that has not been well addressed by the CNN-based method is the lack of capability to learn temporal features, especially long-distance dependency between no...

  14. The classification of finite simple groups groups of characteristic 2 type

    CERN Document Server

    Aschbacher, Michael; Smith, Stephen D; Solomon, Ronald

    2011-01-01

    The book provides an outline and modern overview of the classification of the finite simple groups. It primarily covers the "even case", where the main groups arising are Lie-type (matrix) groups over a field of characteristic 2. The book thus completes a project begun by Daniel Gorenstein's 1983 book, which outlined the classification of groups of "noncharacteristic 2 type". However, this book provides much more. Chapter 0 is a modern overview of the logical structure of the entire classification. Chapter 1 is a concise but complete outline of the "odd case" with updated references, while Chapter 2 sets the stage for the remainder of the book with a similar outline of the "even case". The remaining six chapters describe in detail the fundamental results whose union completes the proof of the classification theorem. Several important subsidiary results are also discussed. In addition, there is a comprehensive listing of the large number of papers referenced from the literature. Appendices provide a brief but ...

  15. Cancer classification in the genomic era: five contemporary problems.

    Science.gov (United States)

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

    2015-10-19

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

  16. Analysis of costs structure of the industrial enterprise

    Directory of Open Access Journals (Sweden)

    Yuriy V. Kovtunenko

    2014-12-01

    Full Text Available Costs are an important factor that affects the economic activities of an industrial enterprise, because they affect the profits of the enterprise on production efficiency and competitiveness. The article aims to summarize approaches of the definition of “costs”, classification costs of the enterprise according to different characteristics and cost structure of industrial enterprises. Each scientist has his own opinion on the choice of the structure and classification of costs, which is based on his own experience and experience of other scientists. Economically justified classification of costs is an important factor for analysis and costs accounting. This paper examines the concept of “costs” in the interpretation of various authors based on research of scientists that highlight the main features of the classification of costs, give the cost structure of industrial enterprises. Based on the study it can be concluded that the standard classification of costs is not for all companies. Therefore, it is necessary to develop a classification of costs according to the main features of the company.

  17. Observation versus classification in supervised category learning.

    Science.gov (United States)

    Levering, Kimery R; Kurtz, Kenneth J

    2015-02-01

    The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

  18. [Guidelines for hygienic classification of learning technologies].

    Science.gov (United States)

    Kuchma, V R; Teksheva, L M; Milushkina, O Iu

    2008-01-01

    Optimization of the educational environment under the present-day conditions has been in progress, by using learning techwares (LTW) without fail. To organize and regulate an academic process in terms of the safety of applied LTW, there is a need for their classification. The currently existing attempts to structure LTW disregard hygienically significant aspects. The task of the present study was to substantiate a LTW safety criterion ensuring a universal approach to working out regulations. This criterion may be the exposure intensity determined by the form of organization of education and its pattern, by the procedure of information presentation, and the age-related peculiarities of a pupil, i.e. by the actual load that is presented by the product of the intensity exposure and its time. The hygienic classification of LTW may be used to evaluate their negative effect in an educational process on the health status of children and adolescents, to regulate hazardous factors and training modes, to design and introduce new learning complexes. The structuring of a LTW system allows one to define possible deleterious actions and the possibilities of preventing this action on the basis of strictly established regulations.

  19. Vibração transversal: um método eficiente para classificação de peças estruturais de madeira Transverse vibration: an efficient method for structural timber classification

    Directory of Open Access Journals (Sweden)

    Carlito Calil Júnior

    2003-08-01

    Full Text Available A classificação de peças estruturais de madeira é uma tendência mundial, mas ainda deficiente no Brasil. O uso de métodos não-destrutivos para classificação e, conseqüentemente, para racionalização do uso de madeira em estruturas, melhora a posição da madeira quando em competição com materiais estruturais mais uniformes. Este trabalho mostra a existência de forte correlação linear entre o módulo de elasticidade estático e o módulo de elasticidade dinâmico, obtidos a partir de testes de flexão estática e de vibração transversal, em 326 peças estruturais de madeira da espécie Southern Pine, e indica a eficiência do método de vibração transversal para determinação do módulo de elasticidade e para classificação de peças estruturais de madeira.The classification of structural components of timber is a worldwide tendency but is still deficient in Brazil. The application of nondestructive methods for classification and consequently, optimization of the use of timber in structures improves the position of the timber in comparison to more uniform structural materials. This work shows the existence of high linear correlation between the static elasticity modulus and the dynamic elasticity modulus, obtained from flexion static test and from transverse vibration test, in 326 structural pieces of Southern Pine specie, and indicates the efficiency of the transverse vibration test for elasticity modulus determination and for classification of structural pieces of timber.

  20. The value of laparoscopic classifications in decision on definitive ...

    African Journals Online (AJOL)

    The value of laparoscopic classifications in decision on definitive surgery in patients ... was to present our clinical experience with the laparoscopic approach in patients ... in 10 cases in whom cord structures were seen entering the internal inguinal ring. ... Four canalicular testes (peeping) were treated with open orchiopexy.

  1. 32 CFR 2001.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

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

  2. Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

    Science.gov (United States)

    Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

    2014-04-01

    In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

  3. Maxillectomy defects: a suggested classification scheme.

    Science.gov (United States)

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

    2013-06-01

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

  4. Hierarchical classification with a competitive evolutionary neural tree.

    Science.gov (United States)

    Adams, R G.; Butchart, K; Davey, N

    1999-04-01

    A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT offers over other hierarchical competitive networks is its ability to self determine the number, and structure, of the competitive nodes in the network, without the need for externally set parameters. The network produces stable classificatory structures by halting its growth using locally calculated heuristics. The results of network simulations are presented over a range of data sets, including Anderson's IRIS data set. The CENT network demonstrates its ability to produce a representative hierarchical structure to classify a broad range of data sets.

  5. Constructing criticality by classification

    DEFF Research Database (Denmark)

    Machacek, Erika

    2017-01-01

    " in the bureaucratic practice of classification: Experts construct material criticality in assessments as they allot information on the materials to the parameters of the assessment framework. In so doing, they ascribe a new set of connotations to the materials, namely supply risk, and their importance to clean energy......, legitimizing a criticality discourse.Specifically, the paper introduces a typology delineating the inferences made by the experts from their produced recommendations in the classification of rare earth element criticality. The paper argues that the classification is a specific process of constructing risk....... It proposes that the expert bureaucratic practice of classification legitimizes (i) the valorisation that was made in the drafting of the assessment framework for the classification, and (ii) political operationalization when enacted that might have (non-)distributive implications for the allocation of public...

  6. 12 CFR 403.4 - Derivative classification.

    Science.gov (United States)

    2010-01-01

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

  7. Supernova Photometric Lightcurve Classification

    Science.gov (United States)

    Zaidi, Tayeb; Narayan, Gautham

    2016-01-01

    This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

  8. IR-360 nuclear power plant safety functions and component classification

    International Nuclear Information System (INIS)

    Yousefpour, F.; Shokri, F.; Soltani, H.

    2010-01-01

    The IR-360 nuclear power plant as a 2-loop PWR of 360 MWe power generation capacity is under design in MASNA Company. For design of the IR-360 structures, systems and components (SSCs), the codes and standards and their design requirements must be determined. It is a prerequisite to classify the IR-360 safety functions and safety grade of structures, systems and components correctly for selecting and adopting the suitable design codes and standards. This paper refers to the IAEA nuclear safety codes and standards as well as USNRC standard system to determine the IR-360 safety functions and to formulate the principles of the IR-360 component classification in accordance with the safety philosophy and feature of the IR-360. By implementation of defined classification procedures for the IR-360 SSCs, the appropriate design codes and standards are specified. The requirements of specific codes and standards are used in design process of IR-360 SSCs by design engineers of MASNA Company. In this paper, individual determination of the IR-360 safety functions and definition of the classification procedures and roles are presented. Implementation of this work which is described with example ensures the safety and reliability of the IR-360 nuclear power plant.

  9. IR-360 nuclear power plant safety functions and component classification

    Energy Technology Data Exchange (ETDEWEB)

    Yousefpour, F., E-mail: fyousefpour@snira.co [Management of Nuclear Power Plant Construction Company (MASNA) (Iran, Islamic Republic of); Shokri, F.; Soltani, H. [Management of Nuclear Power Plant Construction Company (MASNA) (Iran, Islamic Republic of)

    2010-10-15

    The IR-360 nuclear power plant as a 2-loop PWR of 360 MWe power generation capacity is under design in MASNA Company. For design of the IR-360 structures, systems and components (SSCs), the codes and standards and their design requirements must be determined. It is a prerequisite to classify the IR-360 safety functions and safety grade of structures, systems and components correctly for selecting and adopting the suitable design codes and standards. This paper refers to the IAEA nuclear safety codes and standards as well as USNRC standard system to determine the IR-360 safety functions and to formulate the principles of the IR-360 component classification in accordance with the safety philosophy and feature of the IR-360. By implementation of defined classification procedures for the IR-360 SSCs, the appropriate design codes and standards are specified. The requirements of specific codes and standards are used in design process of IR-360 SSCs by design engineers of MASNA Company. In this paper, individual determination of the IR-360 safety functions and definition of the classification procedures and roles are presented. Implementation of this work which is described with example ensures the safety and reliability of the IR-360 nuclear power plant.

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

    Science.gov (United States)

    2012-09-01

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

  11. 45 CFR 601.5 - Derivative classification.

    Science.gov (United States)

    2010-10-01

    ... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... classification guide, need not possess original classification authority. (a) If a person who applies derivative...

  12. A phytosociological classification of the Hlane Wildlife Sanctuary, Swaziland

    Directory of Open Access Journals (Sweden)

    W.P.D. Gertenbach

    1978-09-01

    Full Text Available A phytosociological classification of the vegetation of the Hiane Wildlife Sanctuary was undertaken, with special reference to the vegetation structure and the correlation between plant communities and the biotic and abiotic environment. This study contributes to the drafting of a management plan for the sanctuary.

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

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2014-01-01

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

  14. Classification of projection images of proteins with structural polymorphism by manifold: A simulation study for x-ray free-electron laser diffraction imaging

    Science.gov (United States)

    Yoshidome, Takashi; Oroguchi, Tomotaka; Nakasako, Masayoshi; Ikeguchi, Mitsunori

    2015-09-01

    Coherent x-ray diffraction imaging (CXDI) enables us to visualize noncrystalline sample particles with micrometer to submicrometer dimensions. Using x-ray free-electron laser (XFEL) sources, two-dimensional diffraction patterns are collected from fresh samples supplied to the irradiation area in the "diffraction-before-destruction" scheme. A recent significant increase in the intensity of the XFEL pulse is promising and will allow us to visualize the three-dimensional structures of proteins using XFEL-CXDI in the future. For the protocol proposed for molecular structure determination using future XFEL-CXDI [T. Oroguchi and M. Nakasako, Phys. Rev. E 87, 022712 (2013), 10.1103/PhysRevE.87.022712], we require an algorithm that can classify the data in accordance with the structural polymorphism of proteins arising from their conformational dynamics. However, most of the algorithms proposed primarily require the numbers of conformational classes, and then the results are biased by the numbers. To improve this point, here we examine whether a method based on the manifold concept can classify simulated XFEL-CXDI data with respect to the structural polymorphism of a protein that predominantly adopts two states. After random sampling of the conformations of the two states and in-between states from the trajectories of molecular dynamics simulations, a diffraction pattern is calculated from each conformation. Classification was performed by using our custom-made program suite named enma, in which the diffusion map (DM) method developed based on the manifold concept was implemented. We successfully classify most of the projection electron density maps phase retrieved from diffraction patterns into each of the two states and in-between conformations without the knowledge of the number of conformational classes. We also examined the classification of the projection electron density maps of each of the three states with respect to the Euler angle. The present results suggest

  15. Application of wavelet transform for PDZ domain classification.

    Directory of Open Access Journals (Sweden)

    Khaled Daqrouq

    Full Text Available PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III, that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain's primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT and Shannon entropy denoted by wavelet entropy (WE feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%, which outperformed our occurrence rearrangements based method. The recognition rate was (81.41% with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification.

  16. [Classification of organisms and structuralism in biology].

    Science.gov (United States)

    Vasil'eva, L I

    2001-01-01

    Structuralism in biology is the oldest trend oriented to the search for natural "laws of forms" comparable with laws of growth of crystal, was revived at the end of 20th century on the basis of structuralist thought in socio-humanitarian sciences. The development of principal ideas of the linguistic structuralism in some aspects is similar to that of biological systematics, especially concerning the relationships between "system" and "evolution". However, apart from this general similarity, biological structuralism is strongly focused on familiar problems of the origin of diversity in nature. In their striving for the renovation of existing views, biological structuralists oppose the neo-darwinism emphasizing the existence of "law of forms", that are independent on heredity and genetic "determinism". The trend to develop so-called "rational taxonomy" is also characteristic of biological structuralism but this attempt failed being connected neither with Darwin's historicism nor with Plato's typology.

  17. Measuring Success: Metrics that Link Supply Chain Management to Aircraft Readiness

    National Research Council Canada - National Science Library

    Balestreri, William

    2002-01-01

    ... Aviation Logistics Squadron Utilizing the Logistics Management Institute's DoD Supply Chain Implementation Guide and adapted SCOR model, we applied the six step process for developing a strategic...

  18. Machine learning and dyslexia: Classification of individual structural neuro-imaging scans of students with and without dyslexia

    Directory of Open Access Journals (Sweden)

    P. Tamboer

    2016-01-01

    In a second and independent sample of 876 young adults of a general population, the trained classifier of the first sample was tested, resulting in a classification performance of 59% (p = 0.07; d-prime = 0.65. This decline in classification performance resulted from a large percentage of false alarms. This study provided support for the use of machine learning in anatomical brain imaging.

  19. The Structure of Affine Buildings

    CERN Document Server

    Weiss, Richard M

    2009-01-01

    In The Structure of Affine Buildings, Richard Weiss gives a detailed presentation of the complete proof of the classification of Bruhat-Tits buildings first completed by Jacques Tits in 1986. The book includes numerous results about automorphisms, completions, and residues of these buildings. It also includes tables correlating the results in the locally finite case with the results of Tits's classification of absolutely simple algebraic groups defined over a local field. A companion to Weiss's The Structure of Spherical Buildings, The Structure of Affine Buildings is organized around the clas

  20. Accurate Classification of Chronic Migraine via Brain Magnetic Resonance Imaging

    Science.gov (United States)

    Schwedt, Todd J.; Chong, Catherine D.; Wu, Teresa; Gaw, Nathan; Fu, Yinlin; Li, Jing

    2015-01-01

    Background The International Classification of Headache Disorders provides criteria for the diagnosis and subclassification of migraine. Since there is no objective gold standard by which to test these diagnostic criteria, the criteria are based on the consensus opinion of content experts. Accurate migraine classifiers consisting of brain structural measures could serve as an objective gold standard by which to test and revise diagnostic criteria. The objectives of this study were to utilize magnetic resonance imaging measures of brain structure for constructing classifiers: 1) that accurately identify individuals as having chronic vs. episodic migraine vs. being a healthy control; and 2) that test the currently used threshold of 15 headache days/month for differentiating chronic migraine from episodic migraine. Methods Study participants underwent magnetic resonance imaging for determination of regional cortical thickness, cortical surface area, and volume. Principal components analysis combined structural measurements into principal components accounting for 85% of variability in brain structure. Models consisting of these principal components were developed to achieve the classification objectives. Ten-fold cross validation assessed classification accuracy within each of the ten runs, with data from 90% of participants randomly selected for classifier development and data from the remaining 10% of participants used to test classification performance. Headache frequency thresholds ranging from 5–15 headache days/month were evaluated to determine the threshold allowing for the most accurate subclassification of individuals into lower and higher frequency subgroups. Results Participants were 66 migraineurs and 54 healthy controls, 75.8% female, with an average age of 36 +/− 11 years. Average classifier accuracies were: a) 68% for migraine (episodic + chronic) vs. healthy controls; b) 67.2% for episodic migraine vs. healthy controls; c) 86.3% for chronic

  1. Classification of smooth Fano polytopes

    DEFF Research Database (Denmark)

    Øbro, Mikkel

    A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

  2. Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Mei Zhan

    2015-04-01

    Full Text Available Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM. These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a

  3. Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

    Science.gov (United States)

    Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

    2015-04-01

    Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision

  4. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  5. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

    2014-01-01

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  6. Usefulness of the classification technique of cerebral artery for 2D/3D registration

    International Nuclear Information System (INIS)

    Takemura, Akihiro; Suzuki, Masayuki; Kikuchi, Yuzo; Okumura, Yusuke; Harauchi, Hajime

    2007-01-01

    Several papers have proposed 2D/3D registration methods of the cerebral artery using magnetic resonance angiography (MRA) and digital subtraction angiography (DSA). Since differences between vessels in a DSA image and MRA volume data cause registration failure, we previously proposed a method to extract vessels from MRA volume data using a technique based on classification of the cerebral artery. In this paper, we evaluated the usefulness of this classification technique by evaluating the reliability of this 2D/3D registration method. This classification method divides the cerebral artery in MRA volume data into 12 segments. According to the results of the classification, structures corresponding to vessels on a DSA image can then be extracted. We applied the 2D/3D registration with/without classification to 16 pairs of MRA volume data and DSA images obtained from six patients. The registration results were scored into four levels (Excellent, Good, Fair and Poor). The rates of successful registration (>fair) were 37.5% for registration without classification and 81.3% for that with classification. These findings suggested that there was a low percentage of incorrectly extracted voxels and we could facilitate reliable registration. Thus, the classification technique was shown to be useful for feature-based 2D/3D registration. (author)

  7. Structural-semantic characteristic of phraseologisms in modern German language

    Directory of Open Access Journals (Sweden)

    Abramova Natalya Viktorovna

    2015-03-01

    Full Text Available The article is devoted to the structural and semantic characteristics of phraseology of the modern German language. It reveals the essence of the concept of “idioms”, discusses various classification of phraseological units in German. Many linguists offer a variety of phraseological units classification. It is studied in detailed the classification by B. Fleischer, where the following types of phraseological units are distinguished: nominative collocations, communication idioms, phrasal templates. V.V. Vinogradov classified phraseological units according to their degree of semantic fusion. He identified three major types of phraseological units: phraseological seam, phraseological unity and phraseological (non-free combination. M.D. Stepanova and I.I. Chernyshev worked out structural and semantic classification of phraseological units, consisting of three groups: phraseological units, phraseological combinations, phraseological expressions. A special group of phraseological combinations is of E. Agricola - stable phrases. H. Burger classifies idioms according to their function in the communication process: reference idioms, structural phraseological units, communication idioms. Each classification is provided with vivid examples that characterize the structure and semantics of phraseological units of modern German language.

  8. Automated Feature Design for Time Series Classification by Genetic Programming

    OpenAIRE

    Harvey, Dustin Yewell

    2014-01-01

    Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...

  9. Study on the Safety Classification Criteria of Mechanical Systems and Components for Open Pool-Type Research Reactors

    International Nuclear Information System (INIS)

    Belal, Al Momani; Jo, Jong Chull

    2013-01-01

    This paper describes a new compromised safety classification approach based on the comparative study of the different practices in safety classification of mechanical systems and components of open pool-type RRs, which have been adopted by several developed countries in the nuclear power area. It is hoped that the proposed safety classification criteria will be used to develop a harmonized consensus international standard. Different safety classification criteria for systems, structures, and components (SSCs) of nuclear reactors are used among the countries that export or import nuclear reactor technology, which may make the nuclear technology trade and exchange difficult. Thus, such various different approaches of safety classification need to be compromised to establish a global standard. This article proposes practicable optimized criteria for safety classification of SSCs for open pool-type research reactors (RRs)

  10. Study on the Safety Classification Criteria of Mechanical Systems and Components for Open Pool-Type Research Reactors

    Energy Technology Data Exchange (ETDEWEB)

    Belal, Al Momani [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Jo, Jong Chull [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2013-10-15

    This paper describes a new compromised safety classification approach based on the comparative study of the different practices in safety classification of mechanical systems and components of open pool-type RRs, which have been adopted by several developed countries in the nuclear power area. It is hoped that the proposed safety classification criteria will be used to develop a harmonized consensus international standard. Different safety classification criteria for systems, structures, and components (SSCs) of nuclear reactors are used among the countries that export or import nuclear reactor technology, which may make the nuclear technology trade and exchange difficult. Thus, such various different approaches of safety classification need to be compromised to establish a global standard. This article proposes practicable optimized criteria for safety classification of SSCs for open pool-type research reactors (RRs)

  11. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  12. Electronic Nose Odor Classification with Advanced Decision Tree Structures

    Directory of Open Access Journals (Sweden)

    S. Guney

    2013-09-01

    Full Text Available Electronic nose (e-nose is an electronic device which can measure chemical compounds in air and consequently classify different odors. In this paper, an e-nose device consisting of 8 different gas sensors was designed and constructed. Using this device, 104 different experiments involving 11 different odor classes (moth, angelica root, rose, mint, polis, lemon, rotten egg, egg, garlic, grass, and acetone were performed. The main contribution of this paper is the finding that using the chemical domain knowledge it is possible to train an accurate odor classification system. The domain knowledge about chemical compounds is represented by a decision tree whose nodes are composed of classifiers such as Support Vector Machines and k-Nearest Neighbor. The overall accuracy achieved with the proposed algorithm and the constructed e-nose device was 97.18 %. Training and testing data sets used in this paper are published online.

  13. 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....

  14. Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

    Science.gov (United States)

    Hoover, Richard B.; Storrie-Lombardi, Michael C.

    2004-01-01

    Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

  15. Waste classification sampling plan

    International Nuclear Information System (INIS)

    Landsman, S.D.

    1998-01-01

    The purpose of this sampling is to explain the method used to collect and analyze data necessary to verify and/or determine the radionuclide content of the B-Cell decontamination and decommissioning waste stream so that the correct waste classification for the waste stream can be made, and to collect samples for studies of decontamination methods that could be used to remove fixed contamination present on the waste. The scope of this plan is to establish the technical basis for collecting samples and compiling quantitative data on the radioactive constituents present in waste generated during deactivation activities in B-Cell. Sampling and radioisotopic analysis will be performed on the fixed layers of contamination present on structural material and internal surfaces of process piping and tanks. In addition, dose rate measurements on existing waste material will be performed to determine the fraction of dose rate attributable to both removable and fixed contamination. Samples will also be collected to support studies of decontamination methods that are effective in removing the fixed contamination present on the waste. Sampling performed under this plan will meet criteria established in BNF-2596, Data Quality Objectives for the B-Cell Waste Stream Classification Sampling, J. M. Barnett, May 1998

  16. Contraction-based classification of supersymmetric extensions of kinematical lie algebras

    International Nuclear Information System (INIS)

    Campoamor-Stursberg, R.; Rausch de Traubenberg, M.

    2010-01-01

    We study supersymmetric extensions of classical kinematical algebras from the point of view of contraction theory. It is shown that contracting the supersymmetric extension of the anti-de Sitter algebra leads to a hierarchy similar in structure to the classical Bacry-Levy-Leblond classification.

  17. Automatic Parallelization Tool: Classification of Program Code for Parallel Computing

    Directory of Open Access Journals (Sweden)

    Mustafa Basthikodi

    2016-04-01

    Full Text Available Performance growth of single-core processors has come to a halt in the past decade, but was re-enabled by the introduction of parallelism in processors. Multicore frameworks along with Graphical Processing Units empowered to enhance parallelism broadly. Couples of compilers are updated to developing challenges forsynchronization and threading issues. Appropriate program and algorithm classifications will have advantage to a great extent to the group of software engineers to get opportunities for effective parallelization. In present work we investigated current species for classification of algorithms, in that related work on classification is discussed along with the comparison of issues that challenges the classification. The set of algorithms are chosen which matches the structure with different issues and perform given task. We have tested these algorithms utilizing existing automatic species extraction toolsalong with Bones compiler. We have added functionalities to existing tool, providing a more detailed characterization. The contributions of our work include support for pointer arithmetic, conditional and incremental statements, user defined types, constants and mathematical functions. With this, we can retain significant data which is not captured by original speciesof algorithms. We executed new theories into the device, empowering automatic characterization of program code.

  18. Out-of-Sample Generalizations for Supervised Manifold Learning for Classification.

    Science.gov (United States)

    Vural, Elif; Guillemot, Christine

    2016-03-01

    Supervised manifold learning methods for data classification map high-dimensional data samples to a lower dimensional domain in a structure-preserving way while increasing the separation between different classes. Most manifold learning methods compute the embedding only of the initially available data; however, the generalization of the embedding to novel points, i.e., the out-of-sample extension problem, becomes especially important in classification applications. In this paper, we propose a semi-supervised method for building an interpolation function that provides an out-of-sample extension for general supervised manifold learning algorithms studied in the context of classification. The proposed algorithm computes a radial basis function interpolator that minimizes an objective function consisting of the total embedding error of unlabeled test samples, defined as their distance to the embeddings of the manifolds of their own class, as well as a regularization term that controls the smoothness of the interpolation function in a direction-dependent way. The class labels of test data and the interpolation function parameters are estimated jointly with an iterative process. Experimental results on face and object images demonstrate the potential of the proposed out-of-sample extension algorithm for the classification of manifold-modeled data sets.

  19. Classification Formula and Generation Algorithm of Cycle Decomposition Expression for Dihedral Groups

    Directory of Open Access Journals (Sweden)

    Dakun Zhang

    2013-01-01

    Full Text Available The necessary of classification research on common formula of group (dihedral group cycle decomposition expression is illustrated. It includes the reflection and rotation conversion, which derived six common formulae on cycle decomposition expressions of group; it designed the generation algorithm on the cycle decomposition expressions of group, which is based on the method of replacement conversion and the classification formula; algorithm analysis and the results of the process show that the generation algorithm which is based on the classification formula is outperformed by the general algorithm which is based on replacement conversion; it has great significance to solve the enumeration of the necklace combinational scheme, especially the structural problems of combinational scheme, by using group theory and computer.

  20. A fingerprint classification algorithm based on combination of local and global information

    Science.gov (United States)

    Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

    2011-12-01

    Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

  1. The book classification of William Torrey Harris: influences of Bacon and Hegel in library classification

    Directory of Open Access Journals (Sweden)

    Rodrigo de Sales

    2017-09-01

    Full Text Available The studies of library classification generally interact with the historical contextualization approach and with the classification ideas typical of Philosophy. In the 19th century, the North-American philosopher and educator William Torrey Harris developed a book classification at the St. Louis Public School, based on Francis Bacon and Georg Wilhelm Friedrich Hegel. The objective of this essay is to analyze Harris’s classification, reflecting upon his theoretical and philosophical backgrounds. To achieve such objective, this essay adopts a critical-descriptive approach for analysis. Results show some influences of Bacon and Hegel in Harris’s classification.

  2. Classification of integrable Volterra-type lattices on the sphere: isotropic case

    International Nuclear Information System (INIS)

    Adler, V E

    2008-01-01

    The symmetry approach is used for classification of integrable isotropic vector Volterra lattices on the sphere. The list of integrable lattices consists mainly of new equations. Their symplectic structure and associated PDE of vector NLS type are discussed

  3. Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

    Science.gov (United States)

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

    2014-01-01

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

  4. A kernel-based multi-feature image representation for histopathology image classification

    International Nuclear Information System (INIS)

    Moreno J; Caicedo J Gonzalez F

    2010-01-01

    This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  5. A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    J Carlos Moreno

    2010-09-01

    Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  6. Reliability of Oronasal Fistula Classification.

    Science.gov (United States)

    Sitzman, Thomas J; Allori, Alexander C; Matic, Damir B; Beals, Stephen P; Fisher, David M; Samson, Thomas D; Marcus, Jeffrey R; Tse, Raymond W

    2018-01-01

    Objective Oronasal fistula is an important complication of cleft palate repair that is frequently used to evaluate surgical quality, yet reliability of fistula classification has never been examined. The objective of this study was to determine the reliability of oronasal fistula classification both within individual surgeons and between multiple surgeons. Design Using intraoral photographs of children with repaired cleft palate, surgeons rated the location of palatal fistulae using the Pittsburgh Fistula Classification System. Intrarater and interrater reliability scores were calculated for each region of the palate. Participants Eight cleft surgeons rated photographs obtained from 29 children. Results Within individual surgeons reliability for each region of the Pittsburgh classification ranged from moderate to almost perfect (κ = .60-.96). By contrast, reliability between surgeons was lower, ranging from fair to substantial (κ = .23-.70). Between-surgeon reliability was lowest for the junction of the soft and hard palates (κ = .23). Within-surgeon and between-surgeon reliability were almost perfect for the more general classification of fistula in the secondary palate (κ = .95 and κ = .83, respectively). Conclusions This is the first reliability study of fistula classification. We show that the Pittsburgh Fistula Classification System is reliable when used by an individual surgeon, but less reliable when used among multiple surgeons. Comparisons of fistula occurrence among surgeons may be subject to less bias if they use the more general classification of "presence or absence of fistula of the secondary palate" rather than the Pittsburgh Fistula Classification System.

  7. 5 CFR 1312.7 - Derivative classification.

    Science.gov (United States)

    2010-01-01

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

  8. A hierarchical inferential method for indoor scene classification

    Directory of Open Access Journals (Sweden)

    Jiang Jingzhe

    2017-12-01

    Full Text Available Indoor scene classification forms a basis for scene interaction for service robots. The task is challenging because the layout and decoration of a scene vary considerably. Previous studies on knowledge-based methods commonly ignore the importance of visual attributes when constructing the knowledge base. These shortcomings restrict the performance of classification. The structure of a semantic hierarchy was proposed to describe similarities of different parts of scenes in a fine-grained way. Besides the commonly used semantic features, visual attributes were also introduced to construct the knowledge base. Inspired by the processes of human cognition and the characteristics of indoor scenes, we proposed an inferential framework based on the Markov logic network. The framework is evaluated on a popular indoor scene dataset, and the experimental results demonstrate its effectiveness.

  9. Munitions Classification Library

    Science.gov (United States)

    2016-04-04

    members of the community to make their own additions to any, or all, of the classification libraries . The next phase entailed data collection over less......Include area code) 04/04/2016 Final Report August 2014 - August 2015 MUNITIONS CLASSIFICATION LIBRARY Mr. Craig Murray, Parsons Dr. Thomas H. Bell, Leidos

  10. IAEA Classification of Uranium Deposits

    International Nuclear Information System (INIS)

    Bruneton, Patrice

    2014-01-01

    Classifications of uranium deposits follow two general approaches, focusing on: • descriptive features such as the geotectonic position, the host rock type, the orebody morphology, …… : « geologic classification »; • or on genetic aspects: « genetic classification »

  11. SoFoCles: feature filtering for microarray classification based on gene ontology.

    Science.gov (United States)

    Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

    2010-02-01

    Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

  12. FPGA-Based Online PQD Detection and Classification through DWT, Mathematical Morphology and SVD

    Directory of Open Access Journals (Sweden)

    Misael Lopez-Ramirez

    2018-03-01

    Full Text Available Power quality disturbances (PQD in electric distribution systems can be produced by the utilization of non-linear loads or environmental circumstances, causing electrical equipment malfunction and reduction of its useful life. Detecting and classifying different PQDs implies great efforts in planning and structuring the monitoring system. The main disadvantage of most works in the literature is that they treat a limited number of electrical disturbances through personal computer (PC-based computation techniques, which makes it difficult to perform an online PQD classification. In this work, the novel contribution is a methodology for PQD recognition and classification through discrete wavelet transform, mathematical morphology, decomposition of singular values, and statistical analysis. Furthermore, the timely and reliable classification of different disturbances is necessary; hence, a field programmable gate array (FPGA-based integrated circuit is developed to offer a portable hardware processing unit to perform fast, online PQD classification. The obtained numerical and experimental results demonstrate that the proposed method guarantees high effectiveness during online PQD detection and classification of real voltage/current signals.

  13. Application of ant colony optimization in NPP classification fault location

    International Nuclear Information System (INIS)

    Xie Chunli; Liu Yongkuo; Xia Hong

    2009-01-01

    Nuclear Power Plant is a highly complex structural system with high safety requirements. Fault location appears to be particularly important to enhance its safety. Ant Colony Optimization is a new type of optimization algorithm, which is used in the fault location and classification of nuclear power plants in this paper. Taking the main coolant system of the first loop as the study object, using VB6.0 programming technology, the NPP fault location system is designed, and is tested against the related data in the literature. Test results show that the ant colony optimization can be used in the accurate classification fault location in the nuclear power plants. (authors)

  14. 32 CFR 2400.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... REGULATIONS TO IMPLEMENT E.O. 12356; OFFICE OF SCIENCE AND TECHNOLOGY POLICY INFORMATION SECURITY PROGRAM Derivative Classification § 2400.15 Classification guides. (a) OSTP shall issue and maintain classification guides to facilitate the proper and uniform derivative classification of information. These guides shall...

  15. The Cool and Belkin Faceted Classification of Information Interactions Revisited

    Science.gov (United States)

    Huvila, Isto

    2010-01-01

    Introduction: The complexity of human information activity is a challenge for both practice and research in information sciences and information management. Literature presents a wealth of approaches to analytically structure and make sense of human information activity including a faceted classification model of information interactions published…

  16. Improved Management of Part Safety Classification System for Nuclear Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jin Young; Park, Youn Won; Park, Heung Gyu; Park, Hyo Chan [BEES Inc., Daejeon (Korea, Republic of)

    2016-10-15

    As, in recent years, many quality assurance (QA) related incidents, such as falsely-certified parts and forged documentation, etc., were reported in association with the supply of structures, systems, components and parts to nuclear power plants, a need for a better management of safety classification system was addressed so that it would be based more on the level of parts . Presently, the Korean nuclear power plants do not develop and apply relevant procedures for safety classifications, but rather the safety classes of parts are determined solely based on the experience of equipment designers. So proposed in this paper is a better management plan for safety equipment classification system with an aim to strengthen the quality management for parts. The plan was developed through the analysis of newly introduced technical criteria to be applied to parts of nuclear power plant.

  17. 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.

  18. 7 CFR 28.911 - Review classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Review classification. 28.911 Section 28.911... REGULATIONS COTTON CLASSING, TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification § 28.911 Review classification. (a) A producer may request one review...

  19. Packet Classification by Multilevel Cutting of the Classification Space: An Algorithmic-Architectural Solution for IP Packet Classification in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Motasem Aldiab

    2008-01-01

    Full Text Available Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

  20. 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)

  1. 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)

  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 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)

  4. 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)

  5. 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)

  6. 7 CFR 1794.31 - Classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 12 2010-01-01 2010-01-01 false Classification. 1794.31 Section 1794.31 Agriculture... Classification. (a) Electric and telecommunications programs. RUS will normally determine the proper environmental classification of projects based on its evaluation of the project description set forth in the...

  7. 32 CFR 2400.34 - Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification. 2400.34 Section 2400.34 National... Government Information § 2400.34 Classification. (a) Foreign government information classified by a foreign government or international organization of governments shall retain its original classification designation...

  8. A Pruning Neural Network Model in Credit Classification Analysis

    Directory of Open Access Journals (Sweden)

    Yajiao Tang

    2018-01-01

    Full Text Available Nowadays, credit classification models are widely applied because they can help financial decision-makers to handle credit classification issues. Among them, artificial neural networks (ANNs have been widely accepted as the convincing methods in the credit industry. In this paper, we propose a pruning neural network (PNN and apply it to solve credit classification problem by adopting the well-known Australian and Japanese credit datasets. The model is inspired by synaptic nonlinearity of a dendritic tree in a biological neural model. And it is trained by an error back-propagation algorithm. The model is capable of realizing a neuronal pruning function by removing the superfluous synapses and useless dendrites and forms a tidy dendritic morphology at the end of learning. Furthermore, we utilize logic circuits (LCs to simulate the dendritic structures successfully which makes PNN be implemented on the hardware effectively. The statistical results of our experiments have verified that PNN obtains superior performance in comparison with other classical algorithms in terms of accuracy and computational efficiency.

  9. Classification of ADHD children through multimodal Magnetic Resonance Imaging

    Directory of Open Access Journals (Sweden)

    Dai eDai

    2012-09-01

    Full Text Available Attention deficit/hyperactivity disorder (ADHD is one of the most common diseases in school-age children. To date, the diagnosis of ADHD is mainly subjective and studies of objective diagnostic method are of great importance. Although many efforts have been made recently to investigate the use of structural and functional brain images for the diagnosis purpose, few of them are related to ADHD. In this paper, we introduce an automatic classification framework based on brain imaging features of ADHD patients, and present in detail the feature extraction, feature selection and classifier training methods. The effects of using different features are compared against each other. In addition, we integrate multimodal image features using multi-kernel learning (MKL. The performance of our framework has been validated in the ADHD-200 Global Competition, which is a world-wide classification contest on the ADHD-200 datasets. In this competition, our classification framework using features of resting-state functional connectivity was ranked the 6th out of 21 participants under the competition scoring policy, and performed the best in terms of sensitivity and J-statistic.

  10. 28 CFR 345.20 - Position classification.

    Science.gov (United States)

    2010-07-01

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

  11. 7 CFR 51.2284 - Size classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Size classification. 51.2284 Section 51.2284... Size classification. The following classifications are provided to describe the size of any lot... shall conform to the requirements of the specified classification as defined below: (a) Halves. Lot...

  12. 22 CFR 9.8 - Classification challenges.

    Science.gov (United States)

    2010-04-01

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

  13. 32 CFR 2001.21 - Original classification.

    Science.gov (United States)

    2010-07-01

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

  14. Poststernotomy mediastinitis: a classification to initiate and evaluate reconstructive management based on evidence from a structured review.

    Science.gov (United States)

    van Wingerden, Jan J; Ubbink, Dirk T; van der Horst, Chantal M A M; de Mol, Bas A J M

    2014-11-23

    Early recognition and, where possible, avoidance of risk factors that contribute to the development of poststernotomy mediastinitis (PSM) form the basis for successful prevention. Once the presence of PSM is diagnosed, the known risk factors have been shown to have limited influence on management decisions. Evidence-based knowledge on treatment decisions, which include the extent and type of surgical intervention (other than debridement), timing and others is available but has not yet been incorporated into a classification on management decisions regarding PSM. Ours is a first attempt at developing a classification system for management of PSM, taking the various evidence-based reconstructive options into consideration. The classification is simple to introduce (there are four Types) and relies on the careful establishment of two variables (sternal stability and sternal bone viability and stock) prior to deciding on the best available reconstructive option. It should allow better insight into why treatment decisions fail or have to be altered and will allow better comparison of treatment outcomes between various institutions.

  15. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  16. The history of transdisciplinary race classification: methods, politics and institutions, 1840s-1940s.

    Science.gov (United States)

    McMahon, Richard

    2018-03-01

    A recently blossoming historiographical literature recognizes that physical anthropologists allied with scholars of diverse aspects of society and history to racially classify European peoples over a period of about a hundred years. They created three successive race classification coalitions - ethnology, from around 1840; anthropology, from the 1850s; and interwar raciology - each of which successively disintegrated. The present genealogical study argues that representing these coalitions as 'transdisciplinary' can enrich our understanding of challenges to disciplinary specialization. This is especially the case for the less well-studied nineteenth century, when disciplines and challenges to disciplinary specialization were both gradually emerging. Like Marxism or structuralism, race classification was a holistic interpretive framework, which, at its most ambitious, aimed to structure the human sciences as a whole. It resisted the organization of academia and knowledge into disciplines with separate organizational institutions and research practices. However, the 'transdisciplinarity' of this nationalistic project also bridged emerging borderlines between science and politics. I ascribe race classification's simultaneous longevity and instability to its complex and intricately entwined processes of political and interdisciplinary coalition building. Race classification's politically useful conclusions helped secure public support for institutionalizing the coalition's component disciplines. Institutionalization in turn stimulated disciplines to professionalize. They emphasized disciplinary boundaries and insisted on apolitical science, thus ultimately undermining the 'transdisciplinary' project.

  17. 7 CFR 51.1860 - Color classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Color classification. 51.1860 Section 51.1860... STANDARDS) United States Standards for Fresh Tomatoes 1 Color Classification § 51.1860 Color classification... illustrating the color classification requirements, as set forth in this section. This visual aid may be...

  18. 22 CFR 42.11 - Classification symbols.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Classification symbols. 42.11 Section 42.11... NATIONALITY ACT, AS AMENDED Classification and Foreign State Chargeability § 42.11 Classification symbols. A... visa symbol to show the classification of the alien. Immigrants Symbol Class Section of law Immediate...

  19. 46 CFR 503.54 - Original classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 9 2010-10-01 2010-10-01 false Original classification. 503.54 Section 503.54 Shipping... Program § 503.54 Original classification. (a) No Commission Member or employee has the authority to... classification, it shall be sent to the appropriate agency with original classification authority over the...

  20. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  1. A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

    Directory of Open Access Journals (Sweden)

    Jiuqi Han

    2018-04-01

    Full Text Available Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods.

  2. What lies beneath: detecting sub-canopy changes in savanna woodlands using a three-dimensional classification method

    CSIR Research Space (South Africa)

    Fisher, JT

    2015-07-01

    Full Text Available structural diversity. A 3D classification approach was successful in detecting fine-scale, short-term changes between land uses, and can thus be used as amonitoring tool for savannawoody vegetation structure....

  3. A structuralist approach in the study of evolution and classification

    NARCIS (Netherlands)

    Hammen, van der L.

    1985-01-01

    A survey is given of structuralism as a method that can be applied in the study of evolution and classification. The results of a structuralist approach are illustrated by examples from the laws underlying numerical changes, from the laws underlying changes in the chelicerate life-cycle, and from

  4. Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

    Science.gov (United States)

    Emond, Bruno; Buffett, Scott

    2015-01-01

    This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

  5. Graph Theory-Based Brain Connectivity for Automatic Classification of Multiple Sclerosis Clinical Courses

    Directory of Open Access Journals (Sweden)

    Gabriel Kocevar

    2016-10-01

    Full Text Available Purpose: In this work, we introduce a method to classify Multiple Sclerosis (MS patients into four clinical profiles using structural connectivity information. For the first time, we try to solve this question in a fully automated way using a computer-based method. The main goal is to show how the combination of graph-derived metrics with machine learning techniques constitutes a powerful tool for a better characterization and classification of MS clinical profiles.Materials and methods: Sixty-four MS patients (12 Clinical Isolated Syndrome (CIS, 24 Relapsing Remitting (RR, 24 Secondary Progressive (SP, and 17 Primary Progressive (PP along with 26 healthy controls (HC underwent MR examination. T1 and diffusion tensor imaging (DTI were used to obtain structural connectivity matrices for each subject. Global graph metrics, such as density and modularity, were estimated and compared between subjects’ groups. These metrics were further used to classify patients using tuned Support Vector Machine (SVM combined with Radial Basic Function (RBF kernel.Results: When comparing MS patients to HC subjects, a greater assortativity, transitivity and characteristic path length as well as a lower global efficiency were found. Using all graph metrics, the best F-Measures (91.8%, 91.8%, 75.6% and 70.6% were obtained for binary (HC-CIS, CIS-RR, RR-PP and multi-class (CIS-RR-SP classification tasks, respectively. When using only one graph metric, the best F-Measures (83.6%, 88.9% and 70.7% were achieved for modularity with previous binary classification tasks.Conclusion: Based on a simple DTI acquisition associated with structural brain connectivity analysis, this automatic method allowed an accurate classification of different MS patients’ clinical profiles.

  6. Classification of Osteogenesis Imperfecta revisited

    NARCIS (Netherlands)

    van Dijk, F. S.; Pals, G.; van Rijn, R. R.; Nikkels, P. G. J.; Cobben, J. M.

    2010-01-01

    In 1979 Sillence proposed a classification of Osteogenesis Imperfecta (OI) in OI types I, II, III and IV. In 2004 and 2007 this classification was expanded with OI types V-VIII because of distinct clinical features and/or different causative gene mutations. We propose a revised classification of OI

  7. 14 CFR 1203.701 - Classification.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

  8. 32 CFR 1602.7 - Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification. 1602.7 Section 1602.7 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.7 Classification. Classification is the exercise of the power to determine claims or questions with respect to...

  9. 32 CFR 644.426 - Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 4 2010-07-01 2010-07-01 true Classification. 644.426 Section 644.426 National... HANDBOOK Disposal Disposal of Fee-Owned Real Property and Easement Interests § 644.426 Classification... required by the special acts, classification will be coordinated with the interested Federal agency. The...

  10. 46 CFR 132.210 - Classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Classification. 132.210 Section 132.210 Shipping COAST... Portable and Semiportable Fire Extinguishers § 132.210 Classification. (a) Each portable fire extinguisher... Classification Type Size Halon 1211, 1301, and 1211-1301 mixtures kgs. (lbs.) Foam, liters (gallons) Carbon...

  11. Elman RNN based classification of proteins sequences on account of their mutual information.

    Science.gov (United States)

    Mishra, Pooja; Nath Pandey, Paras

    2012-10-21

    In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Wavelet-based multicomponent denoising on GPU to improve the classification of hyperspectral images

    Science.gov (United States)

    Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco; Mouriño, J. C.

    2017-10-01

    Supervised classification allows handling a wide range of remote sensing hyperspectral applications. Enhancing the spatial organization of the pixels over the image has proven to be beneficial for the interpretation of the image content, thus increasing the classification accuracy. Denoising in the spatial domain of the image has been shown as a technique that enhances the structures in the image. This paper proposes a multi-component denoising approach in order to increase the classification accuracy when a classification method is applied. It is computed on multicore CPUs and NVIDIA GPUs. The method combines feature extraction based on a 1Ddiscrete wavelet transform (DWT) applied in the spectral dimension followed by an Extended Morphological Profile (EMP) and a classifier (SVM or ELM). The multi-component noise reduction is applied to the EMP just before the classification. The denoising recursively applies a separable 2D DWT after which the number of wavelet coefficients is reduced by using a threshold. Finally, inverse 2D-DWT filters are applied to reconstruct the noise free original component. The computational cost of the classifiers as well as the cost of the whole classification chain is high but it is reduced achieving real-time behavior for some applications through their computation on NVIDIA multi-GPU platforms.

  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. 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

  15. False-positive reduction in CAD mass detection using a competitive classification strategy

    International Nuclear Information System (INIS)

    Li Lihua; Zheng Yang; Zhang Lei; Clark, Robert A.

    2001-01-01

    High false-positive (FP) rate remains to be one of the major problems to be solved in CAD study because too many false-positively cued signals will potentially degrade the performance of detecting true-positive regions and increase the call-back rate in CAD environment. In this paper, we proposed a novel classification method for FP reduction, where the conventional 'hard' decision classifier is cascaded with a 'soft' decision classification with the objective to reduce false-positives in the cases with multiple FPs retained after the 'hard' decision classification. The 'soft' classification takes a competitive classification strategy in which only the 'best' ones are selected from the pre-classified suspicious regions as the true mass in each case. A neural network structure is designed to implement the proposed competitive classification. Comparative studies of FP reduction on a database of 79 images by a 'hard' decision classification and a combined 'hard'-'soft' classification method demonstrated the efficiency of the proposed classification strategy. For example, for the high FP sub-database which has only 31.7% of total images but accounts for 63.5% of whole FPs generated in single 'hard' classification, the FPs can be reduced for 56% (from 8.36 to 3.72 per image) by using the proposed method at the cost of 1% TP loss (from 69% to 68%) in whole database, while it can only be reduced for 27% (from 8.36 to 6.08 per image) by simply increasing the threshold of 'hard' classifier with a cost of TP loss as high as 14% (from 69% to 55%). On the average in whole database, the FP reduction by hybrid 'hard'-'soft' classification is 1.58 per image as compared to 1.11 by 'hard' classification at the TP costs described above. Because the cases with high dense tissue are of higher risk of cancer incidence and false-negative detection in mammogram screening, and usually generate more FPs in CAD detection, the method proposed in this paper will be very helpful in improving

  16. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

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

    Science.gov (United States)

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

    2013-01-01

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

  18. 14 CFR 298.3 - Classification.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Classification. 298.3 Section 298.3... REGULATIONS EXEMPTIONS FOR AIR TAXI AND COMMUTER AIR CARRIER OPERATIONS General § 298.3 Classification. (a) There is hereby established a classification of air carriers, designated as “air taxi operators,” which...

  19. Vessel-guided airway segmentation based on voxel classification

    DEFF Research Database (Denmark)

    Lo, Pechin Chien Pau; Sporring, Jon; Ashraf, Haseem

    2008-01-01

    This paper presents a method for improving airway tree segmentation using vessel orientation information. We use the fact that an airway branch is always accompanied by an artery, with both structures having similar orientations. This work is based on a  voxel classification airway segmentation...... method proposed previously. The probability of a voxel belonging to the airway, from the voxel classification method, is augmented with an orientation similarity measure as a criterion for region growing. The orientation similarity measure of a voxel indicates how similar is the orientation...... of the surroundings of a voxel, estimated based on a tube model, is to that of a neighboring vessel. The proposed method is tested on 20 CT images from different subjects selected randomly from a lung cancer screening study. Length of the airway branches from the results of the proposed method are significantly...

  20. “The Naming of Cats”: Automated Genre Classification

    Directory of Open Access Journals (Sweden)

    Yunhyong Kim

    2007-07-01

    Full Text Available This paper builds on the work presented at the ECDL 2006 in automated genre classification as a step toward automating metadata extraction from digital documents for ingest into digital repositories such as those run by archives, libraries and eprint services (Kim & Ross, 2006b. We have previously proposed dividing features of a document into five types (features for visual layout, language model features, stylometric features, features for semantic structure, and contextual features as an object linked to previously classified objects and other external sources and have examined visual and language model features. The current paper compares results from testing classifiers based on image and stylometric features in a binary classification to show that certain genres have strong image features which enable effective separation of documents belonging to the genre from a large pool of other documents.

  1. 32 CFR 2700.22 - Classification guides.

    Science.gov (United States)

    2010-07-01

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

  2. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. 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.

  4. Classification and description of world formation types. Part. I (Introduction)

    Science.gov (United States)

    D. Faber-Langendoen; T. Keeler-Wolf; D. Meidinger; C. Josse; A. Weakley; D. Tart; G. Navarro; B. Hoagland; S. Ponomarenko; J.-P. Saucier; G. Fults; E. Helmer

    2012-01-01

    A vegetation-ecologic classification approach has been developed in which a combination of vegetation attributes (physiognomy, structure, and floristics) and their response to ecological and biogeographic factors are used as the basis for classifying vegetation types (Faber-Langendoen et al. 2012). This approach can help support international, national and subnational...

  5. 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.

  6. 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)

  7. 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)

  8. Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

    Science.gov (United States)

    Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

    2013-01-01

    Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

  9. Border Lakes land-cover classification

    Science.gov (United States)

    Marvin Bauer; Brian Loeffelholz; Doug. Shinneman

    2009-01-01

    This document contains metadata and description of land-cover classification of approximately 5.1 million acres of land bordering Minnesota, U.S.A. and Ontario, Canada. The classification focused on the separation and identification of specific forest-cover types. Some separation of the nonforest classes also was performed. The classification was derived from multi-...

  10. The reliability and reproducibility of the Hertel classification for comminuted proximal humeral fractures compared with the Neer classification

    NARCIS (Netherlands)

    Iordens, Gijs I. T.; Mahabier, Kiran C.; Buisman, Florian E.; Schep, Niels W. L.; Muradin, Galied S. R.; Beenen, Ludo F. M.; Patka, Peter; van Lieshout, Esther M. M.; den Hartog, Dennis

    2016-01-01

    The Neer classification is the most commonly used fracture classification system for proximal humeral fractures. Inter- and intra-observer agreement is limited, especially for comminuted fractures. A possibly more straightforward and reliable classification system is the Hertel classification. The

  11. Classification of movement disorders.

    Science.gov (United States)

    Fahn, Stanley

    2011-05-01

    The classification of movement disorders has evolved. Even the terminology has shifted, from an anatomical one of extrapyramidal disorders to a phenomenological one of movement disorders. The history of how this shift came about is described. The history of both the definitions and the classifications of the various neurologic conditions is then reviewed. First is a review of movement disorders as a group; then, the evolving classifications for 3 of them--parkinsonism, dystonia, and tremor--are covered in detail. Copyright © 2011 Movement Disorder Society.

  12. Colombia: Territorial classification

    International Nuclear Information System (INIS)

    Mendoza Morales, Alberto

    1998-01-01

    The article is about the approaches of territorial classification, thematic axes, handling principles and territorial occupation, politician and administrative units and administration regions among other topics. Understanding as Territorial Classification the space distribution on the territory of the country, of the geographical configurations, the human communities, the political-administrative units and the uses of the soil, urban and rural, existent and proposed

  13. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  14. Natural Language Processing Based Instrument for Classification of Free Text Medical Records

    Directory of Open Access Journals (Sweden)

    Manana Khachidze

    2016-01-01

    Full Text Available According to the Ministry of Labor, Health and Social Affairs of Georgia a new health management system has to be introduced in the nearest future. In this context arises the problem of structuring and classifying documents containing all the history of medical services provided. The present work introduces the instrument for classification of medical records based on the Georgian language. It is the first attempt of such classification of the Georgian language based medical records. On the whole 24.855 examination records have been studied. The documents were classified into three main groups (ultrasonography, endoscopy, and X-ray and 13 subgroups using two well-known methods: Support Vector Machine (SVM and K-Nearest Neighbor (KNN. The results obtained demonstrated that both machine learning methods performed successfully, with a little supremacy of SVM. In the process of classification a “shrink” method, based on features selection, was introduced and applied. At the first stage of classification the results of the “shrink” case were better; however, on the second stage of classification into subclasses 23% of all documents could not be linked to only one definite individual subclass (liver or binary system due to common features characterizing these subclasses. The overall results of the study were successful.

  15. Arabic text classification using Polynomial Networks

    Directory of Open Access Journals (Sweden)

    Mayy M. Al-Tahrawi

    2015-10-01

    Full Text Available In this paper, an Arabic statistical learning-based text classification system has been developed using Polynomial Neural Networks. Polynomial Networks have been recently applied to English text classification, but they were never used for Arabic text classification. In this research, we investigate the performance of Polynomial Networks in classifying Arabic texts. Experiments are conducted on a widely used Arabic dataset in text classification: Al-Jazeera News dataset. We chose this dataset to enable direct comparisons of the performance of Polynomial Networks classifier versus other well-known classifiers on this dataset in the literature of Arabic text classification. Results of experiments show that Polynomial Networks classifier is a competitive algorithm to the state-of-the-art ones in the field of Arabic text classification.

  16. Angle′s Molar Classification Revisited

    Directory of Open Access Journals (Sweden)

    Devanshi Yadav

    2014-01-01

    Results: Of the 500 pretreatment study casts assessed 52.4% were definitive Class I, 23.6% were Class II, 2.6% were Class III and the ambiguous cases were 21%. These could be easily classified with our method of classification. Conclusion: This improvised classification technique will help orthodontists in making classification of malocclusion accurate and simple.

  17. 3D representations of amino acids—applications to protein sequence comparison and classification

    Directory of Open Access Journals (Sweden)

    Jie Li

    2014-08-01

    Full Text Available The amino acid sequence of a protein is the key to understanding its structure and ultimately its function in the cell. This paper addresses the fundamental issue of encoding amino acids in ways that the representation of such a protein sequence facilitates the decoding of its information content. We show that a feature-based representation in a three-dimensional (3D space derived from amino acid substitution matrices provides an adequate representation that can be used for direct comparison of protein sequences based on geometry. We measure the performance of such a representation in the context of the protein structural fold prediction problem. We compare the results of classifying different sets of proteins belonging to distinct structural folds against classifications of the same proteins obtained from sequence alone or directly from structural information. We find that sequence alone performs poorly as a structure classifier. We show in contrast that the use of the three dimensional representation of the sequences significantly improves the classification accuracy. We conclude with a discussion of the current limitations of such a representation and with a description of potential improvements.

  18. The Oxford classification of IgA nephropathy: rationale, clinicopathological correlations, and classification

    NARCIS (Netherlands)

    Cattran, Daniel C.; Coppo, Rosanna; Cook, H. Terence; Feehally, John; Roberts, Ian S. D.; Troyanov, Stéphan; Alpers, Charles E.; Amore, Alessandro; Barratt, Jonathan; Berthoux, Francois; Bonsib, Stephen; Bruijn, Jan A.; D'Agati, Vivette; D'Amico, Giuseppe; Emancipator, Steven; Emma, Francesco; Ferrario, Franco; Fervenza, Fernando C.; Florquin, Sandrine; Fogo, Agnes; Geddes, Colin C.; Groene, Hermann-Josef; Haas, Mark; Herzenberg, Andrew M.; Hill, Prue A.; Hogg, Ronald J.; Hsu, Stephen I.; Jennette, J. Charles; Joh, Kensuke; Julian, Bruce A.; Kawamura, Tetsuya; Lai, Fernand M.; Leung, Chi Bon; Li, Lei-Shi; Li, Philip K. T.; Liu, Zhi-Hong; Mackinnon, Bruce; Mezzano, Sergio; Schena, F. Paolo; Tomino, Yasuhiko; Walker, Patrick D.; Wang, Haiyan; Weening, Jan J.; Yoshikawa, Nori; Zhang, Hong

    2009-01-01

    IgA nephropathy is the most common glomerular disease worldwide, yet there is no international consensus for its pathological or clinical classification. Here a new classification for IgA nephropathy is presented by an international consensus working group. The goal of this new system was to

  19. The eighth TNM classification system for lung cancer: A consideration based on the degree of pleural invasion and involved neighboring structures.

    Science.gov (United States)

    Sakakura, Noriaki; Mizuno, Tetsuya; Kuroda, Hiroaki; Arimura, Takaaki; Yatabe, Yasushi; Yoshimura, Kenichi; Sakao, Yukinori

    2018-04-01

    The eighth tumor-node-metastasis (TNM) classification system for lung cancer has been used since January 2017 and must be applied to an individual institution's database. We analyzed pathological stage data of 2756 patients who underwent resection of non-small-cell lung cancer, particularly in terms of the degree of visceral pleural invasion and involved neighboring structures. Few patients had stage IIA disease (103, 4%); stratification between stages IB and IIA was insufficient (p = 0.129). When T2a tumors were divided into PL1 and PL2 subgroups based on the degree of pleural invasion, there was a significant prognostic difference between the subgroups (p consideration. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. An edit script for taxonomic classifications

    Directory of Open Access Journals (Sweden)

    Valiente Gabriel

    2005-08-01

    Full Text Available Abstract Background The NCBI taxonomy provides one of the most powerful ways to navigate sequence data bases but currently users are forced to formulate queries according to a single taxonomic classification. Given that there is not universal agreement on the classification of organisms, providing a single classification places constraints on the questions biologists can ask. However, maintaining multiple classifications is burdensome in the face of a constantly growing NCBI classification. Results In this paper, we present a solution to the problem of generating modifications of the NCBI taxonomy, based on the computation of an edit script that summarises the differences between two classification trees. Our algorithms find the shortest possible edit script based on the identification of all shared subtrees, and only take time quasi linear in the size of the trees because classification trees have unique node labels. Conclusion These algorithms have been recently implemented, and the software is freely available for download from http://darwin.zoology.gla.ac.uk/~rpage/forest/.

  1. 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.

  2. SVM classification model in depression recognition based on mutation PSO parameter optimization

    Directory of Open Access Journals (Sweden)

    Zhang Ming

    2017-01-01

    Full Text Available At present, the clinical diagnosis of depression is mainly through structured interviews by psychiatrists, which is lack of objective diagnostic methods, so it causes the higher rate of misdiagnosis. In this paper, a method of depression recognition based on SVM and particle swarm optimization algorithm mutation is proposed. To address on the problem that particle swarm optimization (PSO algorithm easily trap in local optima, we propose a feedback mutation PSO algorithm (FBPSO to balance the local search and global exploration ability, so that the parameters of the classification model is optimal. We compared different PSO mutation algorithms about classification accuracy for depression, and found the classification accuracy of support vector machine (SVM classifier based on feedback mutation PSO algorithm is the highest. Our study promotes important reference value for establishing auxiliary diagnostic used in depression recognition of clinical diagnosis.

  3. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  4. Source Classification Framework for an optimized European wide Emission Control Strategy

    DEFF Research Database (Denmark)

    Lützhøft, Hans-Christian Holten; Donner, Erica; Ledin, Anna

    2011-01-01

    of the PS environmental emission. The SCF also provides a well structured approach for European pollutant source and release classification and management. With further European wide implementation, the SCF has the potential or an optimized ECS in order to obtain good chemical status of European water...

  5. 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.

  6. Soil classification using CPTu in Fort McMurray

    Energy Technology Data Exchange (ETDEWEB)

    Elbanna, M. [AMEC Earth and Environmental, Nanaimo, BC (Canada); El Sabbagh, M. [AMEC Earth and Environmental, Burnaby, BC (Canada); Sharp, J. [ConeTec Investigations Ltd., Richmond, BC (Canada)

    2009-07-01

    This paper evaluated 4 piezocone penetration testing (CPTu) classification methods using data from 3 different sites near Fort McMurray in northern Alberta. For comparative purposes, other in-situ tests, field observations, and laboratory tests were performed at all sites in close proximity to the CPTu soundings. The study evaluated pleistocene sand and sand till deposits with low fines content. Profiling these deposits is necessary because they are often used as filler material for earth retaining structures in many oilsands projects. The study also evaluated pleistocene clay and clay tills that are often used as low permeability material for seepage control. In thick layers, pleistocene clay is known to cause foundation problems. CPTu with dissipation data was shown to be a useful tool in geotechnical engineering practice to provide near continuous soil profiling and material properties. CPTu tip resistance and sleeve friction combined with pore pressure measurement provided useful evaluation of subsurface soil types. It was concluded that although all of the CPTu classification charts provided reasonable soil classification in typical soil conditions, local experience and understanding of soil behaviour is needed to make an appropriate selection of the most applicable charts in a given geological condition. 7 refs., 11 figs.

  7. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally....

  8. A comprehensive simulation study on classification of RNA-Seq data.

    Directory of Open Access Journals (Sweden)

    Gökmen Zararsız

    Full Text Available RNA sequencing (RNA-Seq is a powerful technique for the gene-expression profiling of organisms that uses the capabilities of next-generation sequencing technologies. Developing gene-expression-based classification algorithms is an emerging powerful method for diagnosis, disease classification and monitoring at molecular level, as well as providing potential markers of diseases. Most of the statistical methods proposed for the classification of gene-expression data are either based on a continuous scale (eg. microarray data or require a normal distribution assumption. Hence, these methods cannot be directly applied to RNA-Seq data since they violate both data structure and distributional assumptions. However, it is possible to apply these algorithms with appropriate modifications to RNA-Seq data. One way is to develop count-based classifiers, such as Poisson linear discriminant analysis and negative binomial linear discriminant analysis. Another way is to bring the data closer to microarrays and apply microarray-based classifiers. In this study, we compared several classifiers including PLDA with and without power transformation, NBLDA, single SVM, bagging SVM (bagSVM, classification and regression trees (CART, and random forests (RF. We also examined the effect of several parameters such as overdispersion, sample size, number of genes, number of classes, differential-expression rate, and the transformation method on model performances. A comprehensive simulation study is conducted and the results are compared with the results of two miRNA and two mRNA experimental datasets. The results revealed that increasing the sample size, differential-expression rate and decreasing the dispersion parameter and number of groups lead to an increase in classification accuracy. Similar with differential-expression studies, the classification of RNA-Seq data requires careful attention when handling data overdispersion. We conclude that, as a count

  9. Quality Evaluation of Land-Cover Classification Using Convolutional Neural Network

    Science.gov (United States)

    Dang, Y.; Zhang, J.; Zhao, Y.; Luo, F.; Ma, W.; Yu, F.

    2018-04-01

    Land-cover classification is one of the most important products of earth observation, which focuses mainly on profiling the physical characters of the land surface with temporal and distribution attributes and contains the information of both natural and man-made coverage elements, such as vegetation, soil, glaciers, rivers, lakes, marsh wetlands and various man-made structures. In recent years, the amount of high-resolution remote sensing data has increased sharply. Accordingly, the volume of land-cover classification products increases, as well as the need to evaluate such frequently updated products that is a big challenge. Conventionally, the automatic quality evaluation of land-cover classification is made through pixel-based classifying algorithms, which lead to a much trickier task and consequently hard to keep peace with the required updating frequency. In this paper, we propose a novel quality evaluation approach for evaluating the land-cover classification by a scene classification method Convolutional Neural Network (CNN) model. By learning from remote sensing data, those randomly generated kernels that serve as filter matrixes evolved to some operators that has similar functions to man-crafted operators, like Sobel operator or Canny operator, and there are other kernels learned by the CNN model that are much more complex and can't be understood as existing filters. The method using CNN approach as the core algorithm serves quality-evaluation tasks well since it calculates a bunch of outputs which directly represent the image's membership grade to certain classes. An automatic quality evaluation approach for the land-cover DLG-DOM coupling data (DLG for Digital Line Graphic, DOM for Digital Orthophoto Map) will be introduced in this paper. The CNN model as an robustness method for image evaluation, then brought out the idea of an automatic quality evaluation approach for land-cover classification. Based on this experiment, new ideas of quality evaluation

  10. Interactive Classification of Construction Materials: Feedback Driven Framework for Annotation and Analysis of 3d Point Clouds

    Science.gov (United States)

    Hess, M. R.; Petrovic, V.; Kuester, F.

    2017-08-01

    Digital documentation of cultural heritage structures is increasingly more common through the application of different imaging techniques. Many works have focused on the application of laser scanning and photogrammetry techniques for the acquisition of threedimensional (3D) geometry detailing cultural heritage sites and structures. With an abundance of these 3D data assets, there must be a digital environment where these data can be visualized and analyzed. Presented here is a feedback driven visualization framework that seamlessly enables interactive exploration and manipulation of massive point cloud data. The focus of this work is on the classification of different building materials with the goal of building more accurate as-built information models of historical structures. User defined functions have been tested within the interactive point cloud visualization framework to evaluate automated and semi-automated classification of 3D point data. These functions include decisions based on observed color, laser intensity, normal vector or local surface geometry. Multiple case studies are presented here to demonstrate the flexibility and utility of the presented point cloud visualization framework to achieve classification objectives.

  11. Classification of Patient Care Complexity: Cloud Technology.

    Science.gov (United States)

    de Oliveira Riboldi, Caren; Macedo, Andrea Barcellos Teixeira; Mergen, Thiane; Dias, Vera Lúcia Mendes; da Costa, Diovane Ghignatti; Malvezzi, Maria Luiza Falsarella; Magalhães, Ana Maria Muller; Silveira, Denise Tolfo

    2016-01-01

    Presentation of the computerized structure to implement, in a university hospital in the South of Brazil, the Patients Classification System of Perroca, which categorizes patients according to the care complexity. This solution also aims to corroborate a recent study at the hospital, which evidenced that the increasing workload presents a direct relation with the institutional quality indicators. The tools used were the Google applications with high productivity interconnecting the topic knowledge on behalf of the nursing professionals and information technology professionals.

  12. 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...

  13. Classification of Land Cover and Land Use Based on Convolutional Neural Networks

    Science.gov (United States)

    Yang, Chun; Rottensteiner, Franz; Heipke, Christian

    2018-04-01

    Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

  14. Dimensionality-varied deep convolutional neural network for spectral-spatial classification of hyperspectral data

    Science.gov (United States)

    Qu, Haicheng; Liang, Xuejian; Liang, Shichao; Liu, Wanjun

    2018-01-01

    Many methods of hyperspectral image classification have been proposed recently, and the convolutional neural network (CNN) achieves outstanding performance. However, spectral-spatial classification of CNN requires an excessively large model, tremendous computations, and complex network, and CNN is generally unable to use the noisy bands caused by water-vapor absorption. A dimensionality-varied CNN (DV-CNN) is proposed to address these issues. There are four stages in DV-CNN and the dimensionalities of spectral-spatial feature maps vary with the stages. DV-CNN can reduce the computation and simplify the structure of the network. All feature maps are processed by more kernels in higher stages to extract more precise features. DV-CNN also improves the classification accuracy and enhances the robustness to water-vapor absorption bands. The experiments are performed on data sets of Indian Pines and Pavia University scene. The classification performance of DV-CNN is compared with state-of-the-art methods, which contain the variations of CNN, traditional, and other deep learning methods. The experiment of performance analysis about DV-CNN itself is also carried out. The experimental results demonstrate that DV-CNN outperforms state-of-the-art methods for spectral-spatial classification and it is also robust to water-vapor absorption bands. Moreover, reasonable parameters selection is effective to improve classification accuracy.

  15. Definition and classification of epilepsy. Classification of epileptic seizures 2016

    Directory of Open Access Journals (Sweden)

    K. Yu. Mukhin

    2017-01-01

    Full Text Available Epilepsy is one of the most common neurological diseases, especially in childhood and adolescence. The incidence varies from 15 to 113 cases per 100 000 population with the maximum among children under 1 year old. The prevalence of epilepsy is high, ranging from 5 to 8 cases (in some regions – 10 cases per 1000 children under 15 years old. Classification of the disease has great importance for diagnosis, treatment and prognosis. The article presents a novel strategy for classification of epileptic seizures, developed in 2016. It contains a number of brand new concepts, including a very important one, saying that some seizures, previously considered as generalized or focal only, can be, in fact, both focal and generalized. They include tonic, atonic, myoclonic seizures and epileptic spasms. The term “secondarily generalized seizure” is replace by the term “bilateral tonic-clonic seizure” (as soon as it is not a separate type of epileptic seizures, and the term reflects the spread of discharge from any area of cerebral cortex and evolution of any types of focal seizures. International League Against Epilepsy recommends to abandon the term “pseudo-epileptic seizures” and replace it by the term “psychogenic non-epileptic seizures”. If a doctor is not sure that seizures have epileptic nature, the term “paroxysmal event” should be used without specifying the disease. The conception of childhood epileptic encephalopathies, developed within this novel classification project, is one of the most significant achievements, since in this case not only the seizures, but even epileptiform activity can induce severe disorders of higher mental functions. In addition to detailed description of the new strategy for classification of epileptic seizures, the article contains a comprehensive review of the existing principles of epilepsy and epileptic seizures classification.

  16. Topological Classification of Morse Functions and Generalisations of Hilbert's 16-th Problem

    International Nuclear Information System (INIS)

    Arnold, Vladimir I.

    2007-01-01

    The topological structures of the generic smooth functions on a smooth manifold belong to the small quantity of the most fundamental objects of study both in pure and applied mathematics. The problem of their study has been formulated by A. Cayley in 1868, who required the classification of the possible configurations of the horizontal lines on the topographical maps of mountain regions, and created the first elements of what is called today 'Morse Theory' and 'Catastrophes Theory'. In the paper we describe this problem, and in particular describe the classification of Morse functions on the 2 sphere and on the torus

  17. The Design of Cluster Randomized Trials with Random Cross-Classifications

    Science.gov (United States)

    Moerbeek, Mirjam; Safarkhani, Maryam

    2018-01-01

    Data from cluster randomized trials do not always have a pure hierarchical structure. For instance, students are nested within schools that may be crossed by neighborhoods, and soldiers are nested within army units that may be crossed by mental health-care professionals. It is important that the random cross-classification is taken into account…

  18. Business process modelling in demand-driven agri-food supply chains : a reference framework

    NARCIS (Netherlands)

    Verdouw, C.N.

    2010-01-01

    Keywords: Business process models; Supply chain management; Information systems; Reference information models; Market orientation; Mass customisation; Configuration; Coordination; Control; SCOR; Pot plants; Fruit industry

    Abstract

    The increasing volatility and diversity of

  19. Nutrient profile data collected by R/V Nathaniel B. Palmer on the western Antarctic shelf in support of the GLOBEC project, 2001-04 to 2001-06 (NODC Accession 0000786)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GLOBEC (Global Ocean Ecosystem Dynamics) was initiated by SCOR and the IOC of UNESCO in 1991, to understand how global change will affect the abundance, diversity...

  20. Chlorophyll data were collected by R/V Nathaniel B. Palmer on the western Antarctic shelf in support of the GLOBEC project, 2001-04 to 2001-06 (NODC Accession 0000787)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GLOBEC (Global Ocean Ecosystem Dynamics) was initiated by SCOR and the IOC of UNESCO in 1991, to understand how global change will affect the abundance, diversity...

  1. Classification of heterogeneous electron microscopic projections into homogeneous subsets

    International Nuclear Information System (INIS)

    Herman, G.T.; Kalinowski, M.

    2008-01-01

    The co-existence of different states of a macromolecular complex in samples used by three-dimensional electron microscopy (3D-EM) constitutes a serious challenge. The single particle method applied directly to such heterogeneous sets is unable to provide useful information about the encountered conformational diversity and produces reconstructions with severely reduced resolution. One approach to solving this problem is to partition heterogeneous projection set into homogeneous components and apply existing reconstruction techniques to each of them. Due to the nature of the projection images and the high noise level present in them, this classification task is difficult. A method is presented to achieve the desired classification by using a novel image similarity measure and solving the corresponding optimization problem. Unlike the majority of competing approaches, the presented method employs unsupervised classification (it does not require any prior knowledge about the objects being classified) and does not involve a 3D reconstruction procedure. We demonstrate a fast implementation of this method, capable of classifying projection sets that originate from 3D-EM. The method's performance is evaluated on synthetically generated data sets produced by projecting 3D objects that resemble biological structures

  2. Classification of high-resolution remote sensing images based on multi-scale superposition

    Science.gov (United States)

    Wang, Jinliang; Gao, Wenjie; Liu, Guangjie

    2017-07-01

    Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

  3. Data classification and MTBF prediction with a multivariate analysis approach

    International Nuclear Information System (INIS)

    Braglia, Marcello; Carmignani, Gionata; Frosolini, Marco; Zammori, Francesco

    2012-01-01

    The paper presents a multivariate statistical approach that supports the classification of mechanical components, subjected to specific operating conditions, in terms of the Mean Time Between Failure (MTBF). Assessing the influence of working conditions and/or environmental factors on the MTBF is a prerequisite for the development of an effective preventive maintenance plan. However, this task may be demanding and it is generally performed with ad-hoc experimental methods, lacking of statistical rigor. To solve this common problem, a step by step multivariate data classification technique is proposed. Specifically, a set of structured failure data are classified in a meaningful way by means of: (i) cluster analysis, (ii) multivariate analysis of variance, (iii) feature extraction and (iv) predictive discriminant analysis. This makes it possible not only to define the MTBF of the analyzed components, but also to identify the working parameters that explain most of the variability of the observed data. The approach is finally demonstrated on 126 centrifugal pumps installed in an oil refinery plant; obtained results demonstrate the quality of the final discrimination, in terms of data classification and failure prediction.

  4. 5 CFR 2500.3 - Original classification.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Original classification. 2500.3 Section... SECURITY REGULATION § 2500.3 Original classification. No one in the Office of Administration has been granted authority for original classification of information. ...

  5. 10 CFR 61.55 - Waste classification.

    Science.gov (United States)

    2010-01-01

    ... REGULATORY COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.55 Waste classification. (a) Classification of waste for near surface disposal—(1) Considerations. Determination of the classification of radioactive waste involves two...

  6. A classification plan of design class for systems of an advanced research reactor

    International Nuclear Information System (INIS)

    Yoon, Doo Byung; Ryu, Jeong Soo

    2005-01-01

    Advanced Research Reactor(ARR) is being designed by KAERI since 2002. The final goal of the project is to develop a new and unique research reactor model which is superior in safety and economical aspects. The conceptual design for systems, structures, and components of the ARR will be completed by 2005. The basic design for the systems, structures, and components of the ARR will be performed from 2006. Based on the technical experiences on the design and operation of the HANARO, the ARR will be designed. It is necessary to classify the safety class, quality class, and seismic category for the systems, structures, and components. The objective of this work is to propose a classification plan of design class for systems, structures, and components of the ARR. To achieve this purpose, the revision status of the regulations that used as criteria for determining the design class of the systems, structures, and components of the HANARO were investigated. In addition, the present revision status of the codes and the standards that utilized for the design of the HANARO were investigated. Based on these investigations, the codes and the standards for the design of the systems, structures, and components of the ARR were proposed. The feasibility of the proposed classification plan will be verified by performing the conceptual and basic design of the systems, structures, and components of the ARR

  7. Vietnamese Document Representation and Classification

    Science.gov (United States)

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  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. 46 CFR Sec. 18 - Group classification.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false Group classification. Sec. 18 Section 18 Shipping... Sec. 18 Group classification. In the preparation of specifications, Job Orders, Supplemental Job... inserted thereon: Number Classification 41 Maintenance Repairs (deck, engine and stewards department...

  10. 22 CFR 9.6 - Derivative classification.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Derivative classification. 9.6 Section 9.6 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.6 Derivative classification. (a) Definition. Derivative classification is the incorporating, paraphrasing, restating or...

  11. 22 CFR 9.4 - Original classification.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Original classification. 9.4 Section 9.4 Foreign Relations DEPARTMENT OF STATE GENERAL SECURITY INFORMATION REGULATIONS § 9.4 Original classification. (a) Definition. Original classification is the initial determination that certain information...

  12. 28 CFR 524.73 - Classification procedures.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Classification procedures. 524.73 Section 524.73 Judicial Administration BUREAU OF PRISONS, DEPARTMENT OF JUSTICE INMATE ADMISSION, CLASSIFICATION, AND TRANSFER CLASSIFICATION OF INMATES Central Inmate Monitoring (CIM) System § 524.73...

  13. Gender classification under extended operating conditions

    Science.gov (United States)

    Rude, Howard N.; Rizki, Mateen

    2014-06-01

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

  14. 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

  15. Revisiting Classification of Eating Disorders-toward Diagnostic and Statistical Manual of Mental Disorders-5 and International Statistical Classification of Diseases and Related Health Problems-11.

    Science.gov (United States)

    Goyal, Shrigopal; Balhara, Yatan Pal Singh; Khandelwal, S K

    2012-07-01

    Two of the most commonly used nosological systems- International Statistical Classification of Diseases and Related Health Problems (ICD)-10 and Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV are under revision. This process has generated a lot of interesting debates with regards to future of the current diagnostic categories. In fact, the status of categorical approach in the upcoming versions of ICD and DSM is also being debated. The current article focuses on the debate with regards to the eating disorders. The existing classification of eating disorders has been criticized for its limitations. A host of new diagnostic categories have been recommended for inclusion in the upcoming revisions. Also the structure of the existing categories has also been put under scrutiny.

  16. Ototoxicity (cochleotoxicity) classifications: A review.

    Science.gov (United States)

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

    2016-01-01

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

  17. 10 CFR 1045.37 - Classification guides.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 4 2010-01-01 2010-01-01 false Classification guides. 1045.37 Section 1045.37 Energy DEPARTMENT OF ENERGY (GENERAL PROVISIONS) NUCLEAR CLASSIFICATION AND DECLASSIFICATION Generation and Review of Documents Containing Restricted Data and Formerly Restricted Data § 1045.37 Classification guides...

  18. 75 FR 10529 - Mail Classification Change

    Science.gov (United States)

    2010-03-08

    ... POSTAL REGULATORY COMMISSION [Docket Nos. MC2010-19; Order No. 415] Mail Classification Change...-filed Postal Service request to make a minor modification to the Mail Classification Schedule. The.... concerning a change in classification which reflects a change in terminology from Bulk Mailing Center (BMC...

  19. 32 CFR 1602.13 - Judgmental Classification.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Judgmental Classification. 1602.13 Section 1602.13 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM DEFINITIONS § 1602.13 Judgmental Classification. A classification action relating to a registrant's claim for...

  20. 6 CFR 7.26 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... 6 Domestic Security 1 2010-01-01 2010-01-01 false Derivative classification. 7.26 Section 7.26 Domestic Security DEPARTMENT OF HOMELAND SECURITY, OFFICE OF THE SECRETARY CLASSIFIED NATIONAL SECURITY INFORMATION Classified Information § 7.26 Derivative classification. (a) Derivative classification is defined...