Ageing and exercise: building body capital in old age.

Science.gov (United States)

Bergland, Astrid; Fougner, Marit; Lund, Anne; Debesay, Jonas

2018-01-01

Research that provides better understanding of the motivational processes in older age to maintain a healthy and active lifestyle is sought after. We apply theoretical approaches to cultural capital, active and healthy aging health to shed light on the women's experiences in maintaining physical capabilities through an active lifestyle, and thereby facilitating their own inclusion in society. Thus, the aim of this paper is to explore why older home dwelling women over the age of 70 years or more spend time in physical exercise and their experiences about the importance of participating in group exercise for their daily life.This paper reports on a qualitative study based on interviews with 16 older women aged 70 years or more and regularly attending group exercise classes in the community at an established workout center. The data were analyzed the data using an inductive content analysis approach. Three overreaching and interrelated themes emerged from the interviews: "Building body capital for independence", "Building body capital to maintain vitality and being in control" and "Building resources for social interaction". The findings suggest that group exercise is important for building body capital. The group exercise helped the women in building bodily ability to manage everyday life, maintain vitality, being in control, pursue social interaction and live independently. These body resources were important for these older women's experience of the manageability and meaningfulness of daily life. This study has provided insights into older women's understanding and experiences of the challenges of everyday life within a theoretical framework of cultural capital and health. The women acquired cultural health capital, and more specifically body capital, by participating in the group exercise classes. The women's investment in body capital through regular physical activity created resources which facilitated social participation. Therefore professionals need to be

Automated Classification of Heritage Buildings for As-Built Bim Using Machine Learning Techniques

Science.gov (United States)

Bassier, M.; Vergauwen, M.; Van Genechten, B.

2017-08-01

Semantically rich three dimensional models such as Building Information Models (BIMs) are increasingly used in digital heritage. They provide the required information to varying stakeholders during the different stages of the historic buildings life cyle which is crucial in the conservation process. The creation of as-built BIM models is based on point cloud data. However, manually interpreting this data is labour intensive and often leads to misinterpretations. By automatically classifying the point cloud, the information can be proccesed more effeciently. A key aspect in this automated scan-to-BIM process is the classification of building objects. In this research we look to automatically recognise elements in existing buildings to create compact semantic information models. Our algorithm efficiently extracts the main structural components such as floors, ceilings, roofs, walls and beams despite the presence of significant clutter and occlusions. More specifically, Support Vector Machines (SVM) are proposed for the classification. The algorithm is evaluated using real data of a variety of existing buildings. The results prove that the used classifier recognizes the objects with both high precision and recall. As a result, entire data sets are reliably labelled at once. The approach enables experts to better document and process heritage assets.

Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

Science.gov (United States)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2018-05-01

The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image

CLASSIFICATION OF THE MGR WASTE HANDLING BUILDING ELECTRICAL SYSTEM

International Nuclear Information System (INIS)

S.E. Salzman

1999-01-01

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

Activity identification using body-mounted sensors—a review of classification techniques

International Nuclear Information System (INIS)

Preece, Stephen J; Kenney, Laurence P J; Howard, Dave; Goulermas, John Y; Crompton, Robin; Meijer, Kenneth

2009-01-01

With the advent of miniaturized sensing technology, which can be body-worn, it is now possible to collect and store data on different aspects of human movement under the conditions of free living. This technology has the potential to be used in automated activity profiling systems which produce a continuous record of activity patterns over extended periods of time. Such activity profiling systems are dependent on classification algorithms which can effectively interpret body-worn sensor data and identify different activities. This article reviews the different techniques which have been used to classify normal activities and/or identify falls from body-worn sensor data. The review is structured according to the different analytical techniques and illustrates the variety of approaches which have previously been applied in this field. Although significant progress has been made in this important area, there is still significant scope for further work, particularly in the application of advanced classification techniques to problems involving many different activities. (topical review)

Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

Science.gov (United States)

Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

2013-04-01

In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check

Climate classification for the simulation of thermally activated building systems (TABS)

DEFF Research Database (Denmark)

Behrendt, Benjamin; Christensen, Jørgen Erik

2013-01-01

alternative (sustainable) energy sources that would otherwise be insufficient. The design of TABS is however challenging and most often requires a complete simulation of the building. The standard ISO 11855-4 (2011) suggests a simplified sizing method for TABS. The results however omit condensation risk...... entirely. The proposed climate classification should fill this gap by providing the missing data in a simple manner....

Body Percussion and Team Building through the BAPNE Method

Directory of Open Access Journals (Sweden)

Romero-Naranjo A.A.

2016-01-01

Full Text Available BAPNE Method is a method based on cognitive stimulation integrating music and movement through body percussion. The aim of this research is to explore its whole potential as a tool to build teams. Team building is a philosophy for work design, and since over two decades ago, it defends that obtaining a high performance and organizing efficiency is more useful to perceive employees as interdependent members in a team of work than individuals ones. From this viewpoint, this research advocates that BAPNE Method’s body percussion practice will have an impact on this vision of team work directly. For its own characteristics, body percussion stimulates ways of contact in movement, which ease social ties and, especially, promote group cohesion. Through social, body and, affective dimension; BAPNE Method is capable of developing a shared vision and a single aim, to stimulate team work identity and an atmosphere of trust; and finally, to improve individual communication and satisfaction levels in group tasks.

Classification of Obesity Varies between Body Mass Index and Direct Measures of Body Fat in Boys and Girls of Asian and European Ancestry

Science.gov (United States)

McConnell-Nzunga, J.; Naylor, P. J.; Macdonald, H.; Rhodes, R. E.; Hofer, S. M.; McKay, H.

2018-01-01

Body mass index is a common proxy for proportion of body fat. However, body mass index may not classify youth similarly across ages and ethnicities. We used sex- and ethnic-specific receiver operating characteristic curves to determine how obesity classifications compared between body mass index and dual energy x-ray absorptiometry-based body fat…

Exploring point-cloud features from partial body views for gender classification

Science.gov (United States)

Fouts, Aaron; McCoppin, Ryan; Rizki, Mateen; Tamburino, Louis; Mendoza-Schrock, Olga

2012-06-01

In this paper we extend a previous exploration of histogram features extracted from 3D point cloud images of human subjects for gender discrimination. Feature extraction used a collection of concentric cylinders to define volumes for counting 3D points. The histogram features are characterized by a rotational axis and a selected set of volumes derived from the concentric cylinders. The point cloud images are drawn from the CAESAR anthropometric database provided by the Air Force Research Laboratory (AFRL) Human Effectiveness Directorate and SAE International. This database contains approximately 4400 high resolution LIDAR whole body scans of carefully posed human subjects. Success from our previous investigation was based on extracting features from full body coverage which required integration of multiple camera images. With the full body coverage, the central vertical body axis and orientation are readily obtainable; however, this is not the case with a one camera view providing less than one half body coverage. Assuming that the subjects are upright, we need to determine or estimate the position of the vertical axis and the orientation of the body about this axis relative to the camera. In past experiments the vertical axis was located through the center of mass of torso points projected on the ground plane and the body orientation derived using principle component analysis. In a natural extension of our previous work to partial body views, the absence of rotational invariance about the cylindrical axis greatly increases the difficulty for gender classification. Even the problem of estimating the axis is no longer simple. We describe some simple feasibility experiments that use partial image histograms. Here, the cylindrical axis is assumed to be known. We also discuss experiments with full body images that explore the sensitivity of classification accuracy relative to displacements of the cylindrical axis. Our initial results provide the basis for further

Classification of High-Rise Residential Building Facilities: A Descriptive Survey on 170 Housing Scheme in Klang Valley

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Abd Wahab Siti Rashidah Hanum

2016-01-01

Full Text Available High-rise residential building is a type of housing that has multi-dwelling units built on the same land. This type of housing has become popular each year in urban area due to the increasing cost of land. There are several common facilities provided in high-rise residential building. For example playground, swimming pool, gymnasium, 24 hours security system such as CCTV, access card and so on. Thus, maintenance works of the common facilities must be well organised. The purpose of this paper is to identify the classification of facilities provided at high rise residential building. The survey was done on 170 high-rise residential schemes by using stratified random sampling technique. The scope of this research is within Klang Valley area. This area is rapidly developed with high-rise residential building. The objective of this survey is to list down all the facilities provided in each sample of the schemes. The result, there are nine classification of facilities provided for high-rise residential building.

PROCESSING OF CRAWLED URBAN IMAGERY FOR BUILDING USE CLASSIFICATION

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P. Tutzauer

2017-05-01

Full Text Available Recent years have shown a shift from pure geometric 3D city models to data with semantics. This is induced by new applications (e.g. Virtual/Augmented Reality and also a requirement for concepts like Smart Cities. However, essential urban semantic data like building use categories is often not available. We present a first step in bridging this gap by proposing a pipeline to use crawled urban imagery and link it with ground truth cadastral data as an input for automatic building use classification. We aim to extract this city-relevant semantic information automatically from Street View (SV imagery. Convolutional Neural Networks (CNNs proved to be extremely successful for image interpretation, however, require a huge amount of training data. Main contribution of the paper is the automatic provision of such training datasets by linking semantic information as already available from databases provided from national mapping agencies or city administrations to the corresponding façade images extracted from SV. Finally, we present first investigations with a CNN and an alternative classifier as a proof of concept.

Relationship of body build and development of pulmonary tuberculosis

Energy Technology Data Exchange (ETDEWEB)

Nakamura, K

1974-01-01

Height, weight, Body Build Index (relative body weight), sub-scapular skinfold thickness, serum cholesterol level, hemoglobin concentration, and serum uric acid level immediately preceding detection of tuberculosis were compared between index and control cases on 145 pairs, by sex and age group (49 or under and 50 or over). Average height of index cases was greater than that of the control cases. Control cases were heavier than index cases for both sexes and age groups. Comparison of Body Build Index exhibited more distinct differences between the two groups, which were more remarkable in the older age group. Significantly thicker skinfold was demonstrated only among the female control cases. Serum cholesterol and uric acid level were significantly higher among the male control cases. No difference in hemoglobin concentration was observed between the index and control cases. Results not only support previous studies which had shown higher morbidity of tuberculosis among underweight persons, but also suggest that nutritional factors might be important in lowering the susceptibility to development of tuberculosis. (DLC)

Body building, travestismo e feminilidade

OpenAIRE

Próchno, Caio César Sousa Camargo; Nascimento, Maria José de Castro; Romera, Maria Lúcia Castilho

2009-01-01

Neste artigo, parte-se da ideia de corpo virtual, de sexualidade e das histórias do travestismo e transexualismo. Aborda-se a busca pelo feminino por alguns homens e também por mulheres. Para tanto, utiliza-se o conceito de body building, um fenômeno que começou no pós-guerra e vem se solidificando na atualidade devido ao desenvolvimento da ciência na área de cirurgia plástica e outros métodos de construção do corpo. Discute-se a inadequação do termo travestismo, uma vez que a caracterização ...

Modernism in Belgrade: Classification of Modernist Housing Buildings 1919-1980

Science.gov (United States)

Dragutinovic, Anica; Pottgiesser, Uta; De Vos, Els; Melenhorst, Michel

2017-10-01

Yugoslavian Modernist Architecture, although part of a larger cultural phenomenon, received hardly any international attention, since there are only a few internationally published studies about it. Nevertheless, Modernist Architecture of the Inter-war Yugoslavia (Kingdom of Yugoslavia), and specially Modernist Architecture of the Post-war Yugoslavia (Socialist Federal Republic of Yugoslavia under the “reign” of Tito), represents the most important architectural heritage of the 20th century in former Yugoslavian countries. Belgrade, as the capital city of both newly founded Yugoslavia(s), experienced an immediate economic, political and cultural expansion after the both wars, as well as a large population increase. The construction of sufficient and appropriate new housing was a major undertaking in both periods (1919-1940 and 1948-1980), however conceived and realized with deeply diverging views. The transition from villas and modest apartment buildings, as main housing typologies in the Inter-war period, to the mass housing of the Post-war period, was not only a result of the different socio-political context of the two Yugoslavia(s), but also the country’s industrialization, modernization and technological development. Through the classification of Modernist housing buildings in Belgrade, this paper will investigate on relations between the transformations of the main housing typologies executed under different socio-political contexts on the one side, and development of building technologies, construction systems and materials applied on those buildings on the other side. The paper wants to shed light on the Yugoslavian Modernist Architecture in order to increase the international awareness on its architectural and heritage values. The aim is an integrated re-evaluation of the buildings, presentation of their current condition and potentials for future (re)use with a specific focus on building envelopes and construction.

Discussion on building safety culture inside a nuclear safety regulatory body

International Nuclear Information System (INIS)

Fan Yumao

2013-01-01

A strong internal safety culture plays a key role in improving the performance of a nuclear regulatory body. This paper discusses the definition of internal safety culture of nuclear regulatory bodies, and explains the functions that the safety culture to facilitate the nuclear safety regulation and finally puts forward some thoughts about building internal safety culture inside regulatory bodies. (author)

Novel Unsupervised Classification of Collapsed Buildings Using Satellite Imagery, Hazard Scenarios and Fragility Functions

Directory of Open Access Journals (Sweden)

Luis Moya

2018-02-01

Full Text Available Although supervised machine learning classification techniques have been successfully applied to detect collapsed buildings, there is still a major problem that few publications have addressed. The success of supervised machine learning strongly depends on the availability of training samples. Unfortunately, in the aftermath of a large-scale disaster, training samples become available only after several weeks or even months. However, following a disaster, information on the damage situation is one of the most important necessities for rapid search-and-rescue efforts and relief distribution. In this paper, a modification of the supervised machine learning classification technique called logistic regression is presented. Here, the training samples are replaced with probabilistic information, which is calculated from the spatial distribution of the hazard under consideration and one or more fragility functions. Such damage probabilities can be collected almost in real time for specific disasters such as earthquakes and/or tsunamis. We present the application of the proposed method to the 2011 Great East Japan Earthquake and Tsunami for collapsed building detection. The results show good agreement with a field survey performed by the Ministry of Land, Infrastructure, Transport and Tourism, with an overall accuracy of over 80%. Thus, the proposed method can significantly contribute to a rapid estimation of the number and locations of collapsed buildings.

BODY BUILD AND BODY COMPOSITION VS. PHYSICAL CAPACITY IN YOUNG JUDO CONTESTANTS COMPARED TO UNTRAINED SUBJECTS

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G. Lech

2011-11-01

Full Text Available The aim of the present study was to (1 find differences in body build and aerobic and anaerobic capacity between young judoists and untrained peers; (2 compare correlations for indicators of body build with indicators of aerobic and anaerobic capacity among the group of trained and untrained subjects. The study group comprised 18 subjects selected during a competitive period, who had taken at least fifth place in national judo tournaments. Their training experience ranged from 6 to 11 years, 8 to 10 hours a week. The control group was composed of 18 untrained students from one of the schools included in the study. Their body height and mass (BM did not differ compared to judoists. A body composition chart was employed for analysis of body build and body composition. Physiological investigations encompassed measurements of anaerobic (Wingate test and aerobic (graded exercise test on cycle ergometer capacity. Judo contestants are typically characterized by higher BMI, fat-free mass and fat-free mass index compared to the untrained. Compared to the group of untrained peers, young athletes in this sport are distinguished by the time needed to generate peak power. This difference is not observed in the indices characterising aerobic capacity. The level of the indices of body build and composition in young judo contestants shows a moderate and strong correlation with indices of anaerobic and aerobic capacity. The amount of total work in the Wingate test was positively correlated with BMI (r=0.65, p<0.01, fat-free mass index (r=0.63, p<0.01, body mass (r=0.49, p<0.05, fat mass index (r=0.49, p<0.05 and percentage of fat (r=0.48, p<0.05. Maximal peak anaerobic power was positively correlated with fat-free mass index (r=0.48, p<0.05 and percentage of fat (r=0.50, p<0.05. A strong negative correlation between ·VO2max with body mass (r=-0.75, p<0.001, BMI (r=-0.72, p<0.001, moderate correlation with PF%(r=-0.64, p<0.01, fat-free mass index (r=-0.52, p<0

Overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three body mass index classification systems

OpenAIRE

St-Jean, Audray; Meziou, Salma; Ayotte, Pierre; Lucas, Michel

2017-01-01

Background Little is known about the suitability of three commonly used body mass index (BMI) classification systems for Indigenous youth. We estimated overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three BMI classification systems, assessed the level of agreement between them, and evaluated their accuracy through body fat and cardiometabolic risk factors. Methods Data on 288 youth (aged 8–17 years) were collected. Overweight and obesity prevalence were estim...

Neural Networks for the Classification of Building Use from Street-View Imagery

Science.gov (United States)

Laupheimer, D.; Tutzauer, P.; Haala, N.; Spicker, M.

2018-05-01

Within this paper we propose an end-to-end approach for classifying terrestrial images of building facades into five different utility classes (commercial, hybrid, residential, specialUse, underConstruction) by using Convolutional Neural Networks (CNNs). For our examples we use images provided by Google Street View. These images are automatically linked to a coarse city model, including the outlines of the buildings as well as their respective use classes. By these means an extensive dataset is available for training and evaluation of our Deep Learning pipeline. The paper describes the implemented end-to-end approach for classifying street-level images of building facades and discusses our experiments with various CNNs. In addition to the classification results, so-called Class Activation Maps (CAMs) are evaluated. These maps give further insights into decisive facade parts that are learned as features during the training process. Furthermore, they can be used for the generation of abstract presentations which facilitate the comprehension of semantic image content. The abstract representations are a result of the stippling method, an importance-based image rendering.

PATTERN CLASSIFICATION APPROACHES TO MATCHING BUILDING POLYGONS AT MULTIPLE SCALES

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X. Zhang

2012-07-01

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

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

Science.gov (United States)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

Final hazard classification and auditable safety analysis for the 308 Building Complex during post-deactivation surveillance and maintenance mode

International Nuclear Information System (INIS)

Dexheimer, D.

1996-11-01

This document summarizes the inventories of radioactive and hazardous materials present within the 308 Building Complex, and presents the hazard evaluation methodology used to prepare the hazard classification for the Complex. The complex includes the 308 Building (process area and office facilities) and the 308 Building Annex, which includes the former Neutron Radiography Facility containing a shutdown (and partially decommissioned) reactor. This document applies to the post-deactivation surveillance and maintenance mode only, and provides an authorization basis limited to surveillance and maintenance activities. This document does not authorize decommissioning and decontamination activities, movement of fissile materials, modification to facility confinement structures, nor the introduction or storage of additional radionuclides in the 308 Building Complex. This document established a final hazard classification and identifies appropriate and adequate safety functions and controls to reduce or mitigate the risk associated with the surveillance and maintenance mode. The most consequential hazard event scenario is a postulated unmitigated release from an earthquake event involving the entire complex. That release is equivalent to 30% of the Nuclear Category 3 threshold adjusted as allowed by DOE-STD-1027-92 (DOE 1992). The dominant isotopes are 239 Pu, 240 Pu, and 241 Am in the gloveboxes

Topological classification of the Goryachev integrable case in rigid body dynamics

International Nuclear Information System (INIS)

Nikolaenko, S S

2016-01-01

A topological analysis of the Goryachev integrable case in rigid body dynamics is made on the basis of the Fomenko-Zieschang theory. The invariants (marked molecules) which are obtained give a complete description, from the standpoint of Liouville classification, of the systems of Goryachev type on various level sets of the energy. It turns out that on appropriate energy levels the Goryachev case is Liouville equivalent to many classical integrable systems and, in particular, the Joukowski, Clebsch, Sokolov and Kovalevskaya-Yehia cases in rigid body dynamics, as well as to some integrable billiards in plane domains bounded by confocal quadrics -- in other words, the foliations given by the closures of generic solutions of these systems have the same structure. Bibliography: 15 titles

Early classification of pathological heartbeats on wireless body sensor nodes.

Science.gov (United States)

Braojos, Rubén; Beretta, Ivan; Ansaloni, Giovanni; Atienza, David

2014-11-27

Smart Wireless Body Sensor Nodes (WBSNs) are a novel class of unobtrusive, battery-powered devices allowing the continuous monitoring and real-time interpretation of a subject's bio-signals, such as the electrocardiogram (ECG). These low-power platforms, while able to perform advanced signal processing to extract information on heart conditions, are usually constrained in terms of computational power and transmission bandwidth. It is therefore essential to identify in the early stages which parts of an ECG are critical for the diagnosis and, only in these cases, activate on demand more detailed and computationally intensive analysis algorithms. In this work, we present a comprehensive framework for real-time automatic classification of normal and abnormal heartbeats, targeting embedded and resource-constrained WBSNs. In particular, we provide a comparative analysis of different strategies to reduce the heartbeat representation dimensionality, and therefore the required computational effort. We then combine these techniques with a neuro-fuzzy classification strategy, which effectively discerns normal and pathological heartbeats with a minimal run time and memory overhead. We prove that, by performing a detailed analysis only on the heartbeats that our classifier identifies as abnormal, a WBSN system can drastically reduce its overall energy consumption. Finally, we assess the choice of neuro-fuzzy classification by comparing its performance and workload with respect to other state-of-the-art strategies. Experimental results using the MIT-BIH Arrhythmia database show energy savings of as much as 60% in the signal processing stage, and 63% in the subsequent wireless transmission, when a neuro-fuzzy classification structure is employed, coupled with a dimensionality reduction technique based on random projections.

A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

Directory of Open Access Journals (Sweden)

H. Y. Gu

2017-09-01

Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

Building Nuclear Safety and Security Culture Within Regulatory Body

International Nuclear Information System (INIS)

Huda, K.

2016-01-01

To achieve a higher level of nuclear safety and security, it needs to develop the safety and security culture not only in the facility but also in the regulatory body. The regulatory body, especially needs to develop the safety and security culture within the organization, because it has a function to promote and oversee the culture in the facilities. In this sense, the regulatory body should become a role model. Development of the nuclear safety and security culture should be started by properly understanding its concept and awakening the awareness of individual and organization on the importance of nuclear safety and security. For effectiveness of the culture development in the regulatory body, the following steps are suggested to be taken: setting up of the regulatory requirements, self-assessment, independent assessment review, communication with the licensee, oversight of management system implementation, and integration with regulatory activities. The paper discusses those steps in the framework of development of nuclear safety and security culture in the regulatory body, as well as some important elements in building of the culture in the nuclear facilities. (author)

Structural Health Monitoring of Tall Buildings with Numerical Integrator and Convex-Concave Hull Classification

Directory of Open Access Journals (Sweden)

Suresh Thenozhi

2012-01-01

Full Text Available An important objective of health monitoring systems for tall buildings is to diagnose the state of the building and to evaluate its possible damage. In this paper, we use our prototype to evaluate our data-mining approach for the fault monitoring. The offset cancellation and high-pass filtering techniques are combined effectively to solve common problems in numerical integration of acceleration signals in real-time applications. The integration accuracy is improved compared with other numerical integrators. Then we introduce a novel method for support vector machine (SVM classification, called convex-concave hull. We use the Jarvis march method to decide the concave (nonconvex hull for the inseparable points. Finally the vertices of the convex-concave hull are applied for SVM training.

HYBRID OPTIMIZATION OF OBJECT-BASED CLASSIFICATION IN HIGH-RESOLUTION IMAGES USING CONTINOUS ANT COLONY ALGORITHM WITH EMPHASIS ON BUILDING DETECTION

Directory of Open Access Journals (Sweden)

E. Tamimi

2017-09-01

Full Text Available Automatic building detection from High Spatial Resolution (HSR images is one of the most important issues in Remote Sensing (RS. Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object. These showed the superiority of the proposed method in terms of time and accuracy.

Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.

Science.gov (United States)

Huan, Er-Yang; Wen, Gui-Hua; Zhang, Shi-Jun; Li, Dan-Yang; Hu, Yang; Chang, Tian-Yuan; Wang, Qing; Huang, Bing-Lin

2017-01-01

Body constitution classification is the basis and core content of traditional Chinese medicine constitution research. It is to extract the relevant laws from the complex constitution phenomenon and finally build the constitution classification system. Traditional identification methods have the disadvantages of inefficiency and low accuracy, for instance, questionnaires. This paper proposed a body constitution recognition algorithm based on deep convolutional neural network, which can classify individual constitution types according to face images. The proposed model first uses the convolutional neural network to extract the features of face image and then combines the extracted features with the color features. Finally, the fusion features are input to the Softmax classifier to get the classification result. Different comparison experiments show that the algorithm proposed in this paper can achieve the accuracy of 65.29% about the constitution classification. And its performance was accepted by Chinese medicine practitioners.

Detection and Classification of Human Body Odor Using an Electronic Nose

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Teerakiat Kerdcharoen

2009-09-01

Full Text Available An electronic nose (E-nose has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.

Detection and classification of human body odor using an electronic nose.

Science.gov (United States)

Wongchoosuk, Chatchawal; Lutz, Mario; Kerdcharoen, Teerakiat

2009-01-01

An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.

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.

A methodology for energy performance classification of residential building stock of Hamirpur

Directory of Open Access Journals (Sweden)

Aniket Sharma

2017-12-01

Full Text Available In India, there are various codes, standards, guidelines and rating systems launched to make energy intensive and large sized buildings energy efficient whereas independent residential buildings are not covered even though they exist most in numbers of total housing stock. This paper presents a case study methodology for energy performance assessment of existing residential stock of Hamirpur that can be used to develop suitable energy efficiency regulations. The paper discusses the trend of residential development in Hamirpur followed by classification based on usage, condition, predominant material use, ownership size and number of rooms, source of lighting, assets available, number of storey and plot sizes using primary and secondary data. It results in identification of predominant materials used and other characteristics in each of urban and rural area. Further cradle to site embodied energy index of various dominant building materials and their market available alternative materials is calculated from secondary literature and by calculating transportation energy. One representative existing building is selected in each of urban and rural area and their energy performance is evaluated for material embodied energy and operational energy using simulation. Further alternatives are developed based on other dominant materials in each area and evaluated for change in embodied and operational energy. This paper identifies the energy performance of representative houses for both areas and in no way advocates the preference of one type over another. The paper demonstrates a methodology by which energy performance assessment of houses shall be done and also highlights further research.

Final Hazard Classification and Auditable Safety Analysis for the 105-F Building Interim Safe Storage Project

International Nuclear Information System (INIS)

Rodovsky, T.J.; Bond, S.L.

1998-07-01

The auditable safety analysis (ASA) documents the authorization basis for the partial decommissioning and facility modifications to place the 105-F Building into interim safe storage (ISS). Placement into the ISS is consistent with the preferred alternative identified in the Record of Decision (58 FR). Modifications will reduce the potential for release and worker exposure to hazardous and radioactive materials, as well as lower surveillance and maintenance (S ampersand M) costs. This analysis includes the following: A description of the activities to be performed in the course of the 105-F Building ISS Project. An assessment of the inventory of radioactive and other hazardous materials within the 105-F Building. Identification of the hazards associated with the activities of the 105-F Building ISS Project. Identification of internally and externally initiated accident scenarios with the potential to produce significant local or offsite consequences during the 105-F Building ISS Project. Bounding evaluation of the consequences of the potentially significant accident scenarios. Hazard classification based on the bounding consequence evaluation. Associated safety function and controls, including commitments. Radiological and other employee safety and health considerations

An anthropometric classification of body contour deformities after massive weight loss.

Science.gov (United States)

Iglesias, Martin; Butron, Patricia; Abarca, Leonardo; Perez-Monzo, Mario F; de Rienzo-Madero, Beatriz

2010-08-01

Deformities caused by massive weight loss were originally subsidized at the Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán." This caused great economical losses, which led to the development of a classification to select patients with functional problems secondary to massive weight loss. The parameter used is the size of the pannus in relation to fixed anatomic structures within the following anatomic regions: abdomen, arms, thighs, mammary glands, lateral thoracic area, back, lumbar region, gluteal region, sacrum, and mons pubis. Grade 3 deformities are candidates for body contouring surgery because they constitute a functional problem. Grade 2 deformities reevaluated whether the patient has comorbidities. Lesser grades are considered aesthetic procedures and are not candidates for surgical rehabilitation at the Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán." This classification allowed an improvement in communication between the different surgical-medical specialties; therefore, we suggest its application not only for surgical-administrative reasons but also for academic purposes.

Classification of obesity by means of the body mass index and verification by measurement of the body composition using the tritium dilution technique

International Nuclear Information System (INIS)

Leonhardt, W.; Fischer, S.; Weck, M.; Hanefeld, M.

1988-01-01

65 female and 142 male patients have been classified according to their body mass index (BMI) into the categories underweight (BMI 20 or less), normal weight (BMI over 20 - 25), overweight (BMI over 25 - 30), obesity (BMI over 30 - 40), and morbid obesity (BMI over 40). Body composition was measured in all patients using the tritium dilution method. Total body fat was calculated from the total body water values. Relative fat values increased from 17.1% (women) and 14.5% (men) resp. in underweight to 46.2% (women) and 43.3% (men) in morbid obesity. In all classes of BMI men exhibited higher values of body weight, body height and body water and lower values of absolute and relative fat as compared to women. However, the relative fat and water values, relative to 1 in the normal weight class, were equal for both sexes. The results demonstrate that the BMI is very well suited for the classification of obesity. (author)

The building blocks of the full body ownership illusion

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Antonella eMaselli

2013-03-01

Full Text Available Previous work has reported that it is not difficult to give people the illusion of ownership over an artificial body, providing a powerful tool for the investigation of the neural and cognitive mechanisms underlying body perception and self consciousness. We present an experimental study that uses immersive virtual reality focused on identifying the perceptual building blocks of this illusion. We systematically manipulated visuotactile and visual sensorimotor contingencies, visual perspective, and the appearance of the virtual body in order to assess their relative role and mutual interaction. Consistent results from subjective reports and physiological measures showed that a first person perspective over a fake humanoid body is essential for eliciting a body ownership illusion. We found that the level of realism of the virtual body, in particular the realism of skin tone, plays a critical role: when high enough, the illusion can be triggered by the sole effect of the spatial overlap between the real and virtual bodies, providing congruent visuoproprioceptive information, with no need for the additional contribution of congruent visuotactile and/or visual sensorimotor cues. Additionally, we found that the processing of incongruent perceptual cues can be modulated by the level of the illusion: when the illusion is strong, incongruent cues are not experienced as incorrect. Participants exposed to asynchronous visuotactile stimulation can experience the ownership illusion and perceive touch as originating from an object seen to contact the virtual body. Analogously, when the level of realism of the virtual body and/or the spatial overlap of the two bodies is not high enough, the contribution of congruent multisensory and/or sensorimotor cues is required for evoking the illusion. On the basis of these results and inspired by findings from neurophysiological recordings in the monkey, we propose a model that accounts for many of the results reported

The building blocks of the full body ownership illusion

Science.gov (United States)

Maselli, Antonella; Slater, Mel

2013-01-01

Previous work has reported that it is not difficult to give people the illusion of ownership over an artificial body, providing a powerful tool for the investigation of the neural and cognitive mechanisms underlying body perception and self consciousness. We present an experimental study that uses immersive virtual reality (IVR) focused on identifying the perceptual building blocks of this illusion. We systematically manipulated visuotactile and visual sensorimotor contingencies, visual perspective, and the appearance of the virtual body in order to assess their relative role and mutual interaction. Consistent results from subjective reports and physiological measures showed that a first person perspective over a fake humanoid body is essential for eliciting a body ownership illusion. We found that the illusion of ownership can be generated when the virtual body has a realistic skin tone and spatially substitutes the real body seen from a first person perspective. In this case there is no need for an additional contribution of congruent visuotactile or sensorimotor cues. Additionally, we found that the processing of incongruent perceptual cues can be modulated by the level of the illusion: when the illusion is strong, incongruent cues are not experienced as incorrect. Participants exposed to asynchronous visuotactile stimulation can experience the ownership illusion and perceive touch as originating from an object seen to contact the virtual body. Analogously, when the level of realism of the virtual body is not high enough and/or when there is no spatial overlap between the two bodies, then the contribution of congruent multisensory and/or sensorimotor cues is required for evoking the illusion. On the basis of these results and inspired by findings from neurophysiological recordings in the monkey, we propose a model that accounts for many of the results reported in the literature. PMID:23519597

Gender differences in the evaluation of physical attractiveness ideals for male and female body builds.

Science.gov (United States)

Salusso-Deonier, C J; Markee, N L; Pedersen, E L

1993-06-01

The purposes of this research were (1) to explore gender differences in the evaluation of physical attractiveness stimuli developed to represent commonly occurring real builds, (2) to identify observers' concepts of physical attractiveness ideals promoted by the media, and (3) to begin cross-validation of these stimuli as representations of observers' concepts of ideal physical attractiveness for male and female builds. Responses included (1) open-ended descriptions of ideal male and ideal female build, (2) ratings of relative attractiveness of 12 male and 15 female stimuli, (3) selections of stimulus types which best represented ideal builds, and (4) selections of stimulus types perceived to be promoted by the media. Analysis showed strong cross-validation among modes of response. Ideal male build included average/balanced type (small and medium), lean/broad-shouldered type (large), and muscular bulk type (medium). Ideal female body build included average/balanced type (small and medium) and lean/broad-shouldered type (small and medium). Gender differences were in emphasis only. Women emphasized lean/broad-shouldered and average/balanced male types. Men emphasized the muscular bulk male type. Body types perceived to be media-promoted highlighted stereotypic male muscularity and female leanness.

The classification of body dysmorphic disorder symptoms in male and female adolescents.

Science.gov (United States)

Schneider, Sophie C; Baillie, Andrew J; Mond, Jonathan; Turner, Cynthia M; Hudson, Jennifer L

2018-01-01

Body dysmorphic disorder (BDD) was categorised in DSM-5 within the newly created 'obsessive-compulsive and related disorders' chapter, however this classification remains subject to debate. Confirmatory factor analysis was used to test competing models of the co-occurrence of symptoms of BDD, obsessive-compulsive disorder, unipolar depression, anxiety, and eating disorders in a community sample of adolescents, and to explore potential sex differences in these models. Self-report questionnaires assessing disorder symptoms were completed by 3149 Australian adolescents. The fit of correlated factor models was calculated separately in males and females, and measurement invariance testing compared parameters of the best-fitting model between males and females. All theoretical models of the classification of BDD had poor fit to the data. Good fit was found for a novel model where BDD symptoms formed a distinct latent factor, correlated with affective disorder and eating disorder latent factors. Metric non-invariance was found between males and females, and the majority of factor loadings differed between males and females. Correlations between some latent factors also differed by sex. Only cross-sectional data were collected, and the study did not assess a broad range of DSM-5 defined eating disorder symptoms or other disorders in the DSM-5 obsessive-compulsive and related disorders chapter. This study is the first to statistically evaluate competing models of BDD classification. The findings highlight the unique features of BDD and its associations with affective and eating disorders. Future studies examining the classification of BDD should consider developmental and sex differences in their models. Copyright © 2017. Published by Elsevier B.V.

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

The effect of time on EMG classification of hand motions in able-bodied and transradial amputees

DEFF Research Database (Denmark)

Waris, Asim; Niazi, Imran Khan; Jamil, Mohsin

2018-01-01

While several studies have demonstrated the short-term performance of pattern recognition systems, long-term investigations are very limited. In this study, we investigated changes in classification performance over time. Ten able-bodied individuals and six amputees took part in this study. EMG s...... difference between training and testing day increases. Furthermore, for iEMG, performance in amputees was directly proportional to the size of the residual limb.......While several studies have demonstrated the short-term performance of pattern recognition systems, long-term investigations are very limited. In this study, we investigated changes in classification performance over time. Ten able-bodied individuals and six amputees took part in this study. EMG...... was computed for all possible combinations between the days. For all subjects, surface sEMG (7.2 ± 7.6%), iEMG (11.9 ± 9.1%) and cEMG (4.6 ± 4.8%) were significantly different (P 

Differences in Body Build in Children of Different Ethnic Groups and their Impact on the Prevalence of Stunting, Thinness, Overweight, and Obesity.

Science.gov (United States)

Poh, Bee Koon; Wong, Jyh Eiin; Norimah, A Karim; Deurenberg, Paul

2016-03-01

The prevalence of stunting, thinness, overweight, and obesity among children differs by ethnicity. It is not known whether differences in body build across the ethnic groups influence the interpretation of nutritional parameters. To explore the differences in body build across the 5 main ethnic groups in Malaysia and to determine whether differences in body build have an impact on the interpretation of nutrition indicators. A total of 3227 children aged 2.0 to 12.9 years who participated in the South East Asian Nutrition Surveys (SEANUTS) in Malaysia were included in this analysis. Body weight, height, sitting height, wrist and knee breadths, and biceps and subscapular skinfolds were measured, and relative leg length, slenderness index, and sum of skinfolds were calculated. Z scores for height-for-age (HAZ) and body mass index-for-age (BAZ) were calculated using the World Health Organization (WHO) 2007 growth standards. Differences in relative leg length and slenderness across the ethnic groups were correlated with HAZ and BAZ. Correction for differences in body build did, in some ethnic groups, have significant impact on the prevalence of stunting, thinness, overweight, and obesity, and the pattern of prevalence across ethnic groups changed. At the population level, corrections for body build had only minor and mostly nonsignificant effects on prevalence, but at an individual level, corrections for body build placed a substantial number of children in different height or weight categories. Whether these misclassifications warrant additional assessment of body build in clinical practice will need further investigation. © The Author(s) 2016.

The ideal of beauty in the building of recognition marks in ocularcentric societies: the building of the body in blind women in Metropolitan Area in Monterrey

Directory of Open Access Journals (Sweden)

Brenda Araceli Bustos García

2014-12-01

Full Text Available The aim of this paper is around the question: How do the blind women build the body image? Are they influenced by the hegemonic discourse of the ideal of beauty? At first we define the characteristics of an ocularcentric society. Than once we make a deconstruction of empirical research about the body building in blind women. Finally we present our proposed analysis, relying on narrative psychology, developing a perspective that interprets the building body in blind women as a narrative act through which marks recognition are used to evaluate and classify something as beautiful and attractive. In the analysis of the interviews we found that building of recognition marks has two variables: a one in which certain distrusts and even rejections in the opinions generated is shown by using senses such as smell , touch, etc. (b Other one in which a concept is constructed: tactile aesthetics. Distrust or acceptance of aesthetic tactile is generated mainly by aspects such as: (a age at which they lost the sight (b job they do (c blindness condition time.

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

76 FR 63913 - Commercial Building Workforce Job/Task Analyses

Science.gov (United States)

2011-10-14

... were developed for the following six job classifications: Commercial Building Energy Auditor.... Workshops were held for each of the following job classifications: Commercial Building Energy Auditor... field (e.g., commercial building energy auditor, commercial building energy modeler, commissioning/retro...

Overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three body mass index classification systems.

Science.gov (United States)

St-Jean, Audray; Meziou, Salma; Ayotte, Pierre; Lucas, Michel

2017-11-22

Little is known about the suitability of three commonly used body mass index (BMI) classification systems for Indigenous youth. We estimated overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three BMI classification systems, assessed the level of agreement between them, and evaluated their accuracy through body fat and cardiometabolic risk factors. Data on 288 youth (aged 8-17 years) were collected. Overweight and obesity prevalence were estimated with Centers for Disease Control and Prevention (CDC), International Obesity Task Force (IOTF) and World Health Organization (WHO) criteria. Agreement was measured with weighted kappa (κw). Associations with body fat and cardiometabolic risk factors were evaluated by analysis of variance. Obesity prevalence was 42.7% with IOTF, 47.2% with CDC, and 49.3% with WHO criteria. Agreement was almost perfect between IOTF and CDC (κw = 0.93), IOTF and WHO (κw = 0.91), and WHO and CDC (κw = 0.94). Means of body fat and cardiometabolic risk factors were significantly higher (P trend  obesity, regardless of the system used. Youth considered overweight by IOTF but obese by CDC or WHO exhibited less severe clinical obesity. IOTF seems to be more accurate in identifying obesity in Cree youth.

Influence of measurement uncertainty on classification of thermal environment in buildings according to European Standard EN 15251

DEFF Research Database (Denmark)

Kolarik, Jakub; Olesen, Bjarne W.

2015-01-01

European Standard EN 15 251 in its current version does not provide any guidance on how to handle uncertainty of long term measurements of indoor environmental parameters used for classification of buildings. The objective of the study was to analyse the uncertainty for field measurements...... measurements of operative temperature at two measuring points (south/south-west and north/northeast orientation). Results of the present study suggest that measurement uncertainty needs to be considered during assessment of thermal environment in existing buildings. When expanded standard uncertainty was taken...... into account in categorization of thermal environment according to EN 15251, the difference in prevalence of exceeded category limits were up to 17.3%, 8.3% and 2% of occupied hours for category I, II and III respectively....

Comparison of Different Classification Algorithms for the Detection of User's Interaction with Windows in Office Buildings

DEFF Research Database (Denmark)

Markovic, Romana; Wolf, Sebastian; Cao, Jun

2017-01-01

Occupant behavior in terms of interactions with windows and heating systems is seen as one of the main sources of discrepancy between predicted and measured heating, ventilation and air conditioning (HVAC) building energy consumption. Thus, this work analyzes the performance of several...... classification algorithms for detecting occupant's interactions with windows, while taking the imbalanced properties of the available data set into account. The tested methods include support vector machines (SVM), random forests, and their combination with dynamic Bayesian networks (DBN). The results will show...

Climate classifications and building energy use implications in China

International Nuclear Information System (INIS)

Wan, Kevin K.W.; Li, Danny H.W.; Lam, Joseph C.; Yang, Liu

2010-01-01

Cluster analysis of summer and winter discomfort in terms of heat and cold stresses based on 102-year (1901-2002) weather data in China was conducted. Five bioclimate zones were identified. These were compared with the corresponding thermal and solar zoning classifications. Bio-I and Bio-II tended to locate largely within severe cold and cold climates in the north with excellent solar availability (annual clearness index K t generally exceeding 0.5). Bio-III and Bio-IV covered mostly the hot summer and cold winter and mild climate zones. Despite the relatively low K t in winter, passive solar heating should be able to meet a significant proportion of the heating requirements. Bio-V covered the hot summer and warmer winter region, where heat stress and hence cooling requirement dominated. Decreasing trends in the zone-average annual cumulative cold stress during the 102-year period were observed for all five zones. There was, however, no distinct pattern for the heat stress and the changes tended to be more subtle. These indicate that climate change during the 20 th century affected winter discomfort (especially in colder climates in the north) more than the summer discomfort. This could have significant implications for energy use in buildings if such trends persist. (author)

The Classification of Romanian High-Schools

Science.gov (United States)

Ivan, Ion; Milodin, Daniel; Naie, Lucian

2006-01-01

The article tries to tackle the issue of high-schools classification from one city, district or from Romania. The classification criteria are presented. The National Database of Education is also presented and the application of criteria is illustrated. An algorithm for high-school multi-rang classification is proposed in order to build classes of…

The Sitting-Height Index of Build, (Body Mass/(Sitting Height3, as an Improvement on the Body Mass Index for Children, Adolescents and Young Adults

Directory of Open Access Journals (Sweden)

Richard Burton

2018-02-01

Full Text Available The body mass index (BMI is unsatisfactory in being affected by both relative leg length and height, and, for use with children and adolescents, therefore needs to be interpreted in relation to age. The sitting-height index of build (body mass/(sitting height3, is largely free of these disadvantages. Furthermore, because that index is independent of relative leg length, the latter can be treated as a separate indicator of nutritional history and health risks. Past studies on white children and adults have shown body mass to be approximately proportional to (sitting height3. Moreover, multiple regression of (body mass1/3 on sitting height and leg length, using year-by-year averages, has indicated that leg length is an insignificant predictor of body mass. The present study used data for individuals, namely 2–20 years old males and females, black as well as white. Regression analysis as above again showed leg length to be an insignificant predictor of body mass, but only above the age of about nine years. However, sitting height is still a stronger predictor of body mass than leg length at all ages. The advantages of the sitting-height index of build for use with young people are confirmed.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models

Directory of Open Access Journals (Sweden)

Paccaud Fred

2004-04-01

Full Text Available Abstract Background We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. Methods Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i linear regression; (ii logistic classification; (iii regression trees; (iv classification trees (iii and iv are collectively known as "CART". Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. Results Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60–80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. Conclusions There were no striking differences between either the algebraic (i, ii vs. non-algebraic (iii, iv, or the regression (i, iii vs. classification (ii, iv modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

Pattern Classification with Memristive Crossbar Circuits

Science.gov (United States)

2016-03-31

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

Selective classification and quantification model of C&D waste from material resources consumed in residential building construction.

Science.gov (United States)

Mercader-Moyano, Pilar; Ramírez-de-Arellano-Agudo, Antonio

2013-05-01

The unfortunate economic situation involving Spain and the European Union is, among other factors, the result of intensive construction activity over recent years. The excessive consumption of natural resources, together with the impact caused by the uncontrolled dumping of untreated C&D waste in illegal landfills have caused environmental pollution and a deterioration of the landscape. The objective of this research was to generate a selective classification and quantification model of C&D waste based on the material resources consumed in the construction of residential buildings, either new or renovated, namely the Conventional Constructive Model (CCM). A practical example carried out on ten residential buildings in Seville, Spain, enabled the identification and quantification of the C&D waste generated in their construction and the origin of the waste, in terms of the building material from which it originated and its impact for every m(2) constructed. This model enables other researchers to establish comparisons between the various improvements proposed for the minimization of the environmental impact produced by building a CCM, new corrective measures to be proposed in future policies that regulate the production and management of C&D waste generated in construction from the design stage to the completion of the construction process, and the establishment of sustainable management for C&D waste and for the selection of materials for the construction on projected or renovated buildings.

Classification of low energy houses in Danish Building Regulations

DEFF Research Database (Denmark)

Rose, Jørgen; Svendsen, Svend

2005-01-01

The new Danish Building Regulations (Building Regulations, 2005) introduces the total energy consumption, i.e. energy use for heating, ventilation, cooling and domestic hot water, for buildings as a measure for the energy efficiency of new buildings, i.e. moving away from the former U-value demands....... In addition to the minimum requirements for new buildings, the new Building Regulations also specify requirements for characterizing a building as either low energy building class 1 or low energy building class 2. This paper describes a type-house that is presently being built in Denmark. The type......-house easily meets the requirements for being categorized as a low energy building class 1, and the paper investigates how much U-values can be increased if the type-house were to fulfil the requirements for a low energy building class 2 or a building that just fulfils the minimum demands....

Virtual Satellite Construction and Application for Image Classification

International Nuclear Information System (INIS)

Su, W G; Su, F Z; Zhou, C H

2014-01-01

Nowadays, most remote sensing image classification uses single satellite remote sensing data, so the number of bands and band spectral width is consistent. In addition, observed phenomenon such as land cover have the same spectral signature, which causes the classification accuracy to decrease as different data have unique characteristic. Therefore, this paper analyzes different optical remote sensing satellites, comparing the spectral differences and proposes the ideas and methods to build a virtual satellite. This article illustrates the research on the TM, HJ-1 and MODIS data. We obtained the virtual band X 0 through these satellites' bands combined it with the 4 bands of a TM image to build a virtual satellite with five bands. Based on this, we used these data for image classification. The experimental results showed that the virtual satellite classification results of building land and water information were superior to the HJ-1 and TM data respectively

Dynamic Human Body Modeling Using a Single RGB Camera.

Science.gov (United States)

Zhu, Haiyu; Yu, Yao; Zhou, Yu; Du, Sidan

2016-03-18

In this paper, we present a novel automatic pipeline to build personalized parametric models of dynamic people using a single RGB camera. Compared to previous approaches that use monocular RGB images, our system can model a 3D human body automatically and incrementally, taking advantage of human motion. Based on coarse 2D and 3D poses estimated from image sequences, we first perform a kinematic classification of human body parts to refine the poses and obtain reconstructed body parts. Next, a personalized parametric human model is generated by driving a general template to fit the body parts and calculating the non-rigid deformation. Experimental results show that our shape estimation method achieves comparable accuracy with reconstructed models using depth cameras, yet requires neither user interaction nor any dedicated devices, leading to the feasibility of using this method on widely available smart phones.

Acoustic classification schemes in Europe – Applicability for new, existing and renovated housing

DEFF Research Database (Denmark)

Rasmussen, Birgit

2016-01-01

The first acoustic classification schemes for dwellings were published in the 1990’es as national standards with the main purpose to introduce the possibility of specifying easily stricter acoustic criteria for new-build than the minimum requirements found in building regulations. Since then, more...... countries have introduced acoustic classification schemes, the first countries updated more times and some countries introduced acoustic classification also for other building categories. However, the classification schemes continued to focus on new buildings and have in general limited applicability...... for existing buildings from before implementation of acoustic regulations, typically in the 1950’es or later. The paper will summarize main characteristics, differences and similarities of the current national quality classes for housing in ten countries in Europe. In addition, the status and challenges...

Feature Evaluation for Building Facade Images - AN Empirical Study

Science.gov (United States)

Yang, M. Y.; Förstner, W.; Chai, D.

2012-08-01

The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

ORGANIZATIONAL STRUCTURE FOR BUILDINGS RECONSTRUCTION OF HISTORICAL BUILDING OF ODESSA

Directory of Open Access Journals (Sweden)

POSTERNAK I. М.

2016-12-01

Full Text Available Formulation of the problem. As one of perspective forms of integration various complexes act in town-planning structure. In the course of formation of plans of social and economic development of large cities even more often there is a situation when for increase of efficiency of used resources concentration of efforts is necessary not simply, but also new progressive forms of the organization of building manufacture. Purpose. To offer the organizational structure using in practice the saved up scientific and technical potential for reconstruction of buildings of historical building of Odessa 1820 … 1920 years under standards power efficiency and to execute researches engineering architectonics residential buildings of historical building of a city of Odessa. Conclusion. It is offered to create in the city of Odessa "the Corporate scientific and technical complex town-planning power reconstruction "CSTC T-PPR", as innovative organizational structure which uses in practice the saved up scientific and technical potential for reconstruction of buildings of historical building of Odessa under standards power efficiency. It is considered engineering architectonics residential buildings of historical building of a city of Odessa, in particular, not looking on diverse buildings of inhabited appointment of Odessa, for them there are defining factors on which probably to make their grouping and at the same time to allocate the general lines inherent to a housing estate as a whole. It is resulted a general characteristic and classification of residential buildings of historical building of a city of Odessa ХІХ … beginnings ХХ centuries It is allocated and expanded classification of such buildings of inhabited appointment by duration of residing at them.

ORGANIZATIONAL STRUCTURE FOR RECONSTRUCTION OF BUILDINGS HISTORICAL BUILDING OF ODESSA

Directory of Open Access Journals (Sweden)

POSTERNAK I. М.

2017-05-01

Full Text Available Summary. Raising of problem. As one of perspective forms of integration various complexes act in town- planning structure. In the course of formation of plans of social and economic development of large cities even more often there is a situation when for increase of efficiency of used resources concentration of efforts is necessary not simply, but also new progressive forms of the organization of building manufacture. Purpose. To offer the organizational structure using in practice the saved up scientific and technical potential for reconstruction of buildings of historical building of Odessa 1820 … 1920 years under standards power efficiency and to execute researches engineering architectonics residential buildings of historical building of a city of Odessa. Conclusion. It is offered to create in the city of Odessa "the Corporate scientific and technical complex town-planning power reconstruction "CSTC T-PPR", as innovative organizational structure which uses in practice the saved up scientific and technical potential for reconstruction of buildings of historical building of Odessa under standards power efficiency. It is considered engineering architectonics residential buildings of historical building of a city of Odessa, in particular, not looking on diverse buildings of inhabited appointment of Odessa, for them there are defining factors on which probably to make their grouping and at the same time to allocate the general lines inherent to a housing estate as a whole. It is resulted a general characteristic and classification of residential buildings of historical building of a city of Odessa ХІХ beginnings ХХ centuries It is allocated and expanded classification of such buildings of inhabited appointment by duration of residing at them.

Active Learning for Text Classification

OpenAIRE

Hu, Rong

2011-01-01

Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

The Importance of Classification to Business Model Research

OpenAIRE

Susan Lambert

2015-01-01

Purpose: To bring to the fore the scientific significance of classification and its role in business model theory building. To propose a method by which existing classifications of business models can be analyzed and new ones developed. Design/Methodology/Approach: A review of the scholarly literature relevant to classifications of business models is presented along with a brief overview of classification theory applicable to business model research. Existing business model classification...

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

Directory of Open Access Journals (Sweden)

Lim JU

2017-08-01

Full Text Available Jeong Uk Lim,1 Jae Ha Lee,2 Ju Sang Kim,3 Yong Il Hwang,4 Tae-Hyung Kim,5 Seong Yong Lim,6 Kwang Ha Yoo,7 Ki-Suck Jung,4 Young Kyoon Kim,8 Chin Kook Rhee8 1Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, St Paul’s Hospital, College of Medicine, The Catholic University of Korea, 2Division of Pulmonology, Department of Internal Medicine, Inje University College of Medicine, Haeundae Paik Hospital, Busan, 3Division of Pulmonary Medicine, Department of Internal Medicine, Incheon St Mary’s Hospital, College of Medicine, The Catholic University of Korea, Incheon, 4Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, 5Division of Pulmonary and Critical Care Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, 6Division of Pulmonary and Critical Care Medicine, Department of Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 7Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Konkuk University School of Medicine, 8Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Seoul St Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea Introduction: A low body mass index (BMI is associated with increased mortality and low health-related quality of life in patients with COPD. The Asia-Pacific classification of BMI has a lower cutoff for overweight and obese categories compared to the World Health Organization (WHO classification. The present study assessed patients with COPD among different BMI categories according to two BMI classification systems: WHO and Asia-Pacific. Patients and methods: Patients with COPD aged 40 years or older from the Korean COPD Subtype Study cohort were selected for evaluation

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

Science.gov (United States)

Liang, Wei; Zhang, Yinlong; Tan, Jindong; Li, Yang

2014-01-01

This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient's ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS) filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs) are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC) in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN) platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen. PMID:24681668

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

Science.gov (United States)

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

2015-07-01

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

Building an asynchronous web-based tool for machine learning classification.

Science.gov (United States)

Weber, Griffin; Vinterbo, Staal; Ohno-Machado, Lucila

2002-01-01

Various unsupervised and supervised learning methods including support vector machines, classification trees, linear discriminant analysis and nearest neighbor classifiers have been used to classify high-throughput gene expression data. Simpler and more widely accepted statistical tools have not yet been used for this purpose, hence proper comparisons between classification methods have not been conducted. We developed free software that implements logistic regression with stepwise variable selection as a quick and simple method for initial exploration of important genetic markers in disease classification. To implement the algorithm and allow our collaborators in remote locations to evaluate and compare its results against those of other methods, we developed a user-friendly asynchronous web-based application with a minimal amount of programming using free, downloadable software tools. With this program, we show that classification using logistic regression can perform as well as other more sophisticated algorithms, and it has the advantages of being easy to interpret and reproduce. By making the tool freely and easily available, we hope to promote the comparison of classification methods. In addition, we believe our web application can be used as a model for other bioinformatics laboratories that need to develop web-based analysis tools in a short amount of time and on a limited budget.

Relative significance of heat transfer processes to quantify tradeoffs between complexity and accuracy of energy simulations with a building energy use patterns classification

Science.gov (United States)

Heidarinejad, Mohammad

This dissertation develops rapid and accurate building energy simulations based on a building classification that identifies and focuses modeling efforts on most significant heat transfer processes. The building classification identifies energy use patterns and their contributing parameters for a portfolio of buildings. The dissertation hypothesis is "Building classification can provide minimal required inputs for rapid and accurate energy simulations for a large number of buildings". The critical literature review indicated there is lack of studies to (1) Consider synoptic point of view rather than the case study approach, (2) Analyze influence of different granularities of energy use, (3) Identify key variables based on the heat transfer processes, and (4) Automate the procedure to quantify model complexity with accuracy. Therefore, three dissertation objectives are designed to test out the dissertation hypothesis: (1) Develop different classes of buildings based on their energy use patterns, (2) Develop different building energy simulation approaches for the identified classes of buildings to quantify tradeoffs between model accuracy and complexity, (3) Demonstrate building simulation approaches for case studies. Penn State's and Harvard's campus buildings as well as high performance LEED NC office buildings are test beds for this study to develop different classes of buildings. The campus buildings include detailed chilled water, electricity, and steam data, enabling to classify buildings into externally-load, internally-load, or mixed-load dominated. The energy use of the internally-load buildings is primarily a function of the internal loads and their schedules. Externally-load dominated buildings tend to have an energy use pattern that is a function of building construction materials and outdoor weather conditions. However, most of the commercial medium-sized office buildings have a mixed-load pattern, meaning the HVAC system and operation schedule dictate

Bodies, building and bricks: Women architects and builders in eight eco-communities in Argentina, Britain, Spain, Thailand and USA

OpenAIRE

Pickerill, J.

2015-01-01

Eco-building is a male domain where men are presumed to be better builders and designers, more men than women build and women find their design ideas and contributions to eco-building are belittled. This article suggests that a focus on bodies, embodiment and the ‘doing’ of building is a potentially productive way to move beyond current gender discrimination. This article makes three key interventions using empirical material from eight case studies of eco-communities in Britain, Thailand, Sp...

Myosin heavy chain composition of single fibres from m. biceps brachii of male body builders

DEFF Research Database (Denmark)

Klitgaard, H; Zhou, M.-Y.; Richter, Erik

1990-01-01

The myosin heavy chain (MHC) composition of single fibres from m. biceps brachii of young sedentary men (28 +/- 0.4 years, mean +/- SE, n = 4) and male body builders (25 +/- 2.0 years, n = 4) was analysed with a sensitive one-dimensional electrophoretic technique. Compared with sedentary men...... expression of MHC isoforms within histochemical type II fibres of human skeletal muscle with body building. Furthermore, in human skeletal muscle differences in expression of MHC isoforms may not always be reflected in the traditional histochemical classification of types I, IIa, IIb and IIc fibres....

Thermal Comfort and Ventilation Criteria for low Energy Residential Buildings in Building Codes

DEFF Research Database (Denmark)

Cao, Guangyu; Kurnitski, Jarek; Awbi, Hazim

2012-01-01

of the indoor air quality in such buildings. Currently, there are no global guidelines for specifying the indoor thermal environment in such low-energy buildings. The objective of this paper is to analyse the classification of indoor thermal comfort levels and recommended ventilation rates for different low...

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

Directory of Open Access Journals (Sweden)

Wei Liang

2014-03-01

Full Text Available This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient’s ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen.

FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

Directory of Open Access Journals (Sweden)

M. Y. Yang

2012-08-01

Full Text Available The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

Body mass index: different nutritional status according to WHO, OPAS and Lipschitz classifications in gastrointestinal cancer patients.

Science.gov (United States)

Barao, Katia; Forones, Nora Manoukian

2012-01-01

The body mass index (BMI) is the most common marker used on diagnoses of the nutritional status. The great advantage of this index is the easy way to measure, the low cost, the good correlation with the fat mass and the association to morbidity and mortality. To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. A prospective study on 352 patients with esophageal, gastric or colorectal cancer was done. The BMI was calculated and analyzed by the classification of WHO, Lipschitz and OPAS. The mean age was 62.1 ± 12.4 years and 59% of them had more than 59 years. The BMI had not difference between the genders in patients cancer had more than 65 years. A different cut off must be used for this patients, because undernourished patients may be wrongly considered well nourished.

Use of Binary Partition Tree and energy minimization for object-based classification of urban land cover

Science.gov (United States)

Li, Mengmeng; Bijker, Wietske; Stein, Alfred

2015-04-01

Two main challenges are faced when classifying urban land cover from very high resolution satellite images: obtaining an optimal image segmentation and distinguishing buildings from other man-made objects. For optimal segmentation, this work proposes a hierarchical representation of an image by means of a Binary Partition Tree (BPT) and an unsupervised evaluation of image segmentations by energy minimization. For building extraction, we apply fuzzy sets to create a fuzzy landscape of shadows which in turn involves a two-step procedure. The first step is a preliminarily image classification at a fine segmentation level to generate vegetation and shadow information. The second step models the directional relationship between building and shadow objects to extract building information at the optimal segmentation level. We conducted the experiments on two datasets of Pléiades images from Wuhan City, China. To demonstrate its performance, the proposed classification is compared at the optimal segmentation level with Maximum Likelihood Classification and Support Vector Machine classification. The results show that the proposed classification produced the highest overall accuracies and kappa coefficients, and the smallest over-classification and under-classification geometric errors. We conclude first that integrating BPT with energy minimization offers an effective means for image segmentation. Second, we conclude that the directional relationship between building and shadow objects represented by a fuzzy landscape is important for building extraction.

Building a Cohesive Body of Design Knowledge: Developments from a Design Science Research Perspective

DEFF Research Database (Denmark)

Cash, Philip; Piirainen, Kalle A.

2015-01-01

researchers have identified difficulties in building on past works, and combining insights from across the field. This work starts to dissolve some of these issues by drawing on Design Science Research to propose an integrated approach for the development of design research knowledge, coupled with pragmatic......Design is an extremely diverse field where there has been widespread debate on how to build a cohesive body of scientific knowledge. To date, no satisfactory proposition has been adopted across the field – hampering scientific development. Without this basis for bringing research together design...... advice for design researchers. This delivers a number of implications for researchers as well as for the field as a whole....

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

Managing Measurement Uncertainty in Building Acoustics

Directory of Open Access Journals (Sweden)

Chiara Scrosati

2015-12-01

Full Text Available In general, uncertainties should preferably be determined following the principles laid down in ISO/IEC Guide 98-3, the Guide to the expression of uncertainty in measurement (GUM:1995. According to current knowledge, it seems impossible to formulate these models for the different quantities in building acoustics. Therefore, the concepts of repeatability and reproducibility are necessary to determine the uncertainty of building acoustics measurements. This study shows the uncertainty of field measurements of a lightweight wall, a heavyweight floor, a façade with a single glazing window and a façade with double glazing window that were analyzed by a Round Robin Test (RRT, conducted in a full-scale experimental building at ITC-CNR (Construction Technologies Institute of the National Research Council of Italy. The single number quantities and their uncertainties were evaluated in both narrow and enlarged range and it was shown that including or excluding the low frequencies leads to very significant differences, except in the case of the sound insulation of façades with single glazing window. The results obtained in these RRTs were compared with other results from literature, which confirm the increase of the uncertainty of single number quantities due to the low frequencies extension. Having stated the measurement uncertainty for a single measurement, in building acoustics, it is also very important to deal with sampling for the purposes of classification of buildings or building units. Therefore, this study also shows an application of the sampling included in the Italian Standard on the acoustic classification of building units on a serial type building consisting of 47 building units. It was found that the greatest variability is observed in the façade and it depends on both the great variability of window’s typologies and on workmanship. Finally, it is suggested how to manage the uncertainty in building acoustics, both for one single

Preliminary Hazard Classification for the 105-B Reactor

International Nuclear Information System (INIS)

Kerr, N.R.

1997-08-01

This document summarizes the inventories of radioactive and hazardous materials present within the 105-B Reactor and uses the inventory information to determine the preliminary hazard classification for the surveillance and maintenance activities of the facility. The result of this effort was the preliminary hazard classification for the 105-B Building surveillance and maintenance activities. The preliminary hazard classification was determined to be Nuclear Category 3. Additional hazard and accident analysis will be documented in a separate report to define the hazard controls and final hazard classification

Objective classification of ecological status in marine water bodies using ecotoxicological information and multivariate analysis.

Science.gov (United States)

Beiras, Ricardo; Durán, Iria

2014-12-01

Some relevant shortcomings have been identified in the current approach for the classification of ecological status in marine water bodies, leading to delays in the fulfillment of the Water Framework Directive objectives. Natural variability makes difficult to settle fixed reference values and boundary values for the Ecological Quality Ratios (EQR) for the biological quality elements. Biological responses to environmental degradation are frequently of nonmonotonic nature, hampering the EQR approach. Community structure traits respond only once ecological damage has already been done and do not provide early warning signals. An alternative methodology for the classification of ecological status integrating chemical measurements, ecotoxicological bioassays and community structure traits (species richness and diversity), and using multivariate analyses (multidimensional scaling and cluster analysis), is proposed. This approach does not depend on the arbitrary definition of fixed reference values and EQR boundary values, and it is suitable to integrate nonlinear, sensitive signals of ecological degradation. As a disadvantage, this approach demands the inclusion of sampling sites representing the full range of ecological status in each monitoring campaign. National or international agencies in charge of coastal pollution monitoring have comprehensive data sets available to overcome this limitation.

Seismic Performance of Masonry Buildings in Algeria

OpenAIRE

F. Lazzali; S. Bedaoui

2012-01-01

Structural performance and seismic vulnerability of masonry buildings in Algeria are investigated in this paper. Structural classification of such buildings is carried out regarding their structural elements. Seismicity of Algeria is briefly discussed. Then vulnerability of masonry buildings and their failure mechanisms in the Boumerdes earthquake (May, 2003) are examined.

Towards a genetic classification of uranium deposits

International Nuclear Information System (INIS)

Cuney, M.

2009-01-01

As the IAEA's uranium deposit classification is based on the deposit nature and morphology, some deposits which have been formed by very different genetic processes and located in very different geological environments, are grouped according to this classification. In order to build up a reliable genetic classification based on the mechanism at the origin of the formation of the deposit, the author presents the five main categories according to which uranium deposits can be classified: magmatic, hydrothermal, evapotranspiration, syn-sedimentary, and infiltration of meteoric water

Reactor building

International Nuclear Information System (INIS)

Ebata, Sakae.

1990-01-01

At least one valve rack is disposed in a reactor building, on which pipeways to a main closure valve, valves and bypasses of turbines are placed and contained. The valve rack is fixed to the main body of the building or to a base mat. Since the reactor building is designed as class A earthquake-proofness and for maintaining the S 1 function, the valve rack can be fixed to the building main body or to the base mat. With such a constitution, the portions for maintaining the S 1 function are concentrated to the reactor building. As a result, the dispersion of structures of earthquake-proof portion corresponding to the reference earthquake vibration S 1 can be prevented. Accordingly, the conditions for the earthquake-proof design of the turbine building and the turbine/electric generator supporting rack are defined as only the class B earthquake-proof design conditions. In view of the above, the amount of building materials can be saved and the time for construction can be shortened. (I.S.)

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

Science.gov (United States)

Hotz, Christine S; Templeton, Steven J; Christopher, Mary M

2005-03-01

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

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)

[Body weight evolution and classification of body weight in relation to the results of bariatric surgery: roux-en-Y gastric bypass].

Science.gov (United States)

Novais, Patrícia Fátima Sousa; Rasera Junior, Irineu; Leite, Celso Vieira de Souza; Oliveira, Maria Rita Marques de

2010-03-01

The objective of this study was to assess the evolution and classification of body weight in relation to the results of bariatric surgery in women who underwent the procedure more than two years ago. A total of 141 women underwent banded Roux-en-Y gastric bypass (RYGB). The participants were divided according to the time elapsed since surgery and the percentage of excess weight lost (%EWL): 75. The women in the group with %EWL 75 (36.2%) ranged from normal to pre-obese and presented lower late weight gain than the women in the other groups. Weight evolution two or more years after surgery showed the expected reductions, with some individuals responding better to surgery than others. This shows that it is necessary to monitor, investigate and intervene to obtain the desired results.

Multisensor multiresolution data fusion for improvement in classification

Science.gov (United States)

Rubeena, V.; Tiwari, K. C.

2016-04-01

The rapid advancements in technology have facilitated easy availability of multisensor and multiresolution remote sensing data. Multisensor, multiresolution data contain complementary information and fusion of such data may result in application dependent significant information which may otherwise remain trapped within. The present work aims at improving classification by fusing features of coarse resolution hyperspectral (1 m) LWIR and fine resolution (20 cm) RGB data. The classification map comprises of eight classes. The class names are Road, Trees, Red Roof, Grey Roof, Concrete Roof, Vegetation, bare Soil and Unclassified. The processing methodology for hyperspectral LWIR data comprises of dimensionality reduction, resampling of data by interpolation technique for registering the two images at same spatial resolution, extraction of the spatial features to improve classification accuracy. In the case of fine resolution RGB data, the vegetation index is computed for classifying the vegetation class and the morphological building index is calculated for buildings. In order to extract the textural features, occurrence and co-occurence statistics is considered and the features will be extracted from all the three bands of RGB data. After extracting the features, Support Vector Machine (SVMs) has been used for training and classification. To increase the classification accuracy, post processing steps like removal of any spurious noise such as salt and pepper noise is done which is followed by filtering process by majority voting within the objects for better object classification.

DETECTION OF COLLAPSED BUILDINGS BY CLASSIFYING SEGMENTED AIRBORNE LASER SCANNER DATA

Directory of Open Access Journals (Sweden)

S. O. Elberink

2012-09-01

Full Text Available Rapid mapping of damaged regions and individual buildings is essential for efficient crisis management. Airborne laser scanner (ALS data is potentially able to deliver accurate information on the 3D structures in a damaged region. In this paper we describe two different strategies how to process ALS point clouds in order to detect collapsed buildings automatically. Our aim is to detect collapsed buildings using post event data only. The first step in the workflow is the segmentation of the point cloud detecting planar regions. Next, various attributes are calculated for each segment. The detection of damaged buildings is based on the values of these attributes. Two different classification strategies have been applied in order to test whether the chosen strategy is capable of detect- ing collapsed buildings. The results of the classification are analysed and assessed for accuracy against a reference map in order to validate the quality of the rules derived. Classification results have been achieved with accuracy measures from 60–85% complete- ness and correctness. It is shown that not only the classification strategy influences the accuracy measures; also the validation meth- odology, including the type and accuracy of the reference data, plays a major role.

Classification in Medical Imaging

DEFF Research Database (Denmark)

Chen, Chen

Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... on characterizing human faces and emphysema disease in lung CT images....

Acoustic classification of dwellings

DEFF Research Database (Denmark)

Berardi, Umberto; Rasmussen, Birgit

2014-01-01

insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...

New Site Coefficients and Site Classification System Used in Recent Building Seismic Code Provisions

Science.gov (United States)

Dobry, R.; Borcherdt, R.D.; Crouse, C.B.; Idriss, I.M.; Joyner, W.B.; Martin, G.R.; Power, M.S.; Rinne, E.E.; Seed, R.B.

2000-01-01

Recent code provisions for buildings and other structures (1994 and 1997 NEHRP Provisions, 1997 UBC) have adopted new site amplification factors and a new procedure for site classification. Two amplitude-dependent site amplification factors are specified: Fa for short periods and Fv for longer periods. Previous codes included only a long period factor S and did not provide for a short period amplification factor. The new site classification system is based on definitions of five site classes in terms of a representative average shear wave velocity to a depth of 30 m (V?? s). This definition permits sites to be classified unambiguously. When the shear wave velocity is not available, other soil properties such as standard penetration resistance or undrained shear strength can be used. The new site classes denoted by letters A - E, replace site classes in previous codes denoted by S1 - S4. Site classes A and B correspond to hard rock and rock, Site Class C corresponds to soft rock and very stiff / very dense soil, and Site Classes D and E correspond to stiff soil and soft soil. A sixth site class, F, is defined for soils requiring site-specific evaluations. Both Fa and Fv are functions of the site class, and also of the level of seismic hazard on rock, defined by parameters such as Aa and Av (1994 NEHRP Provisions), Ss and S1 (1997 NEHRP Provisions) or Z (1997 UBC). The values of Fa and Fv decrease as the seismic hazard on rock increases due to soil nonlinearity. The greatest impact of the new factors Fa and Fv as compared with the old S factors occurs in areas of low-to-medium seismic hazard. This paper summarizes the new site provisions, explains the basis for them, and discusses ongoing studies of site amplification in recent earthquakes that may influence future code developments.

Automatic indexing, compiling and classification

International Nuclear Information System (INIS)

Andreewsky, Alexandre; Fluhr, Christian.

1975-06-01

A review of the principles of automatic indexing, is followed by a comparison and summing-up of work by the authors and by a Soviet staff from the Moscou INFORM-ELECTRO Institute. The mathematical and linguistic problems of the automatic building of thesaurus and automatic classification are examined [fr

Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

Science.gov (United States)

Pang, Shiyan; Hu, Xiangyun; Cai, Zhongliang; Gong, Jinqi; Zhang, Mi

2018-03-24

In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects. A novel structural feature that was extracted from aerial images is constructed to classify the candidate changed building objects into buildings and non-buildings. The changed building objects are further classified as "newly built", "taller", "demolished", and "lower" by combining the classification and the digital surface models of two periods. Finally, three typical areas from a large dataset are used to validate the proposed method. Numerous experiments demonstrate the effectiveness of the proposed algorithm.

Use of building typologies for energy performance assessment of national building stocks. Existent experiences in European Countries and common approach. First TABULA synthesis report

Energy Technology Data Exchange (ETDEWEB)

Loga, Tobias; Diefenbach, Nikolaus (eds.)

2010-06-15

The present study examines the experiences with building typologies in the European countries. The objective is to learn how to structure the variety of energy-related features of existing build-ings. As a result of the enquiry it can be stated that there are a lot of different activities which are based on typological criteria. Some of them are concentrating on providing information material and conducting energy advice. On the other hand, building types are used for a better understand-ing of the energy performance of building portfolios on different levels: from the strategic planning of housing companies up to the evaluation of national policies and measures in the building sector. On the basis of these experiences a common approach for building typologies has been devel-oped. The core elements of this harmonised approach are a classification systematic, a structure for building and supply system data and a coherent energy balance method. Furthermore a uni-form classification of statistical data enables a concerted approach for designing national building stock models. Finally, a concise itinerary is described which allows experts to develop step by step a national or regional building typology which are compatible with the common TABULA approach. (orig.)

Compact and Hybrid Feature Description for Building Extraction

Science.gov (United States)

Li, Z.; Liu, Y.; Hu, Y.; Li, P.; Ding, Y.

2017-05-01

Building extraction in aerial orthophotos is crucial for various applications. Currently, deep learning has been shown to be successful in addressing building extraction with high accuracy and high robustness. However, quite a large number of samples is required in training a classifier when using deep learning model. In order to realize accurate and semi-interactive labelling, the performance of feature description is crucial, as it has significant effect on the accuracy of classification. In this paper, we bring forward a compact and hybrid feature description method, in order to guarantees desirable classification accuracy of the corners on the building roof contours. The proposed descriptor is a hybrid description of an image patch constructed from 4 sets of binary intensity tests. Experiments show that benefiting from binary description and making full use of color channels, this descriptor is not only computationally frugal, but also accurate than SURF for building extraction.

Hazard Classification for Fuel Supply Shutdown Facility

International Nuclear Information System (INIS)

BENECKE, M.W.

2000-01-01

Final hazard classification for the 300 Area N Reactor fuel storage facility resulted in the assignment of Nuclear Facility Hazard Category 3 for the uranium metal fuel and feed material storage buildings (303-A, 303-B, 303-G, 3712, and 3716). Radiological for the residual uranium and thorium oxide storage building and an empty former fuel storage building that may be used for limited radioactive material storage in the future (303-K/3707-G, and 303-E), and Industrial for the remainder of the Fuel Supply Shutdown buildings (303-F/311 Tank Farm, 303-M, 313-S, 333, 334 and Tank Farm, 334-A, and MO-052)

THE LOW BACKSCATTERING TARGETS CLASSIFICATION IN URBAN AREAS

Directory of Open Access Journals (Sweden)

L. Shi

2012-07-01

Full Text Available The Polarimetric and Interferometric Synthetic Aperture Radar (POLINSAR is widely used in urban area nowadays. Because of the physical and geometric sensitivity, the POLINSAR is suitable for the city classification, power-lines detection, building extraction, etc. As the new X-band POLINSAR radar, the china prototype airborne system, XSAR works with high spatial resolution in azimuth (0.1 m and slant range (0.4 m. In land applications, SAR image classification is a useful tool to distinguish the interesting area and obtain the target information. The bare soil, the cement road, the water and the building shadow are common scenes in the urban area. As it always exists low backscattering sign objects (LBO with the similar scattering mechanism (all odd bounce except for shadow in the XSAR images, classes are usually confused in Wishart-H-Alpha and Freeman-Durden methods. It is very hard to distinguish those targets only using the general information. To overcome the shortage, this paper explores an improved algorithm for LBO refined classification based on the Pre-Classification in urban areas. Firstly, the Pre-Classification is applied in the polarimetric datum and the mixture class is marked which contains LBO. Then, the polarimetric covariance matrix C3 is re-estimated on the Pre-Classification results to get more reliable results. Finally, the occurrence space which combining the entropy and the phase-diff standard deviation between HH and VV channel is used to refine the Pre-Classification results. The XSAR airborne experiments show the improved method is potential to distinguish the mixture classes in the low backscattering objects.

Model-Based Building Detection from Low-Cost Optical Sensors Onboard Unmanned Aerial Vehicles

Science.gov (United States)

Karantzalos, K.; Koutsourakis, P.; Kalisperakis, I.; Grammatikopoulos, L.

2015-08-01

The automated and cost-effective building detection in ultra high spatial resolution is of major importance for various engineering and smart city applications. To this end, in this paper, a model-based building detection technique has been developed able to extract and reconstruct buildings from UAV aerial imagery and low-cost imaging sensors. In particular, the developed approach through advanced structure from motion, bundle adjustment and dense image matching computes a DSM and a true orthomosaic from the numerous GoPro images which are characterised by important geometric distortions and fish-eye effect. An unsupervised multi-region, graphcut segmentation and a rule-based classification is responsible for delivering the initial multi-class classification map. The DTM is then calculated based on inpaininting and mathematical morphology process. A data fusion process between the detected building from the DSM/DTM and the classification map feeds a grammar-based building reconstruction and scene building are extracted and reconstructed. Preliminary experimental results appear quite promising with the quantitative evaluation indicating detection rates at object level of 88% regarding the correctness and above 75% regarding the detection completeness.

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.

Property Specification Patterns for intelligence building software

Science.gov (United States)

Chun, Seungsu

2018-03-01

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

Incorporating Open Source Data for Bayesian Classification of Urban Land Use From VHR Stereo Images

NARCIS (Netherlands)

Li, Mengmeng; De Beurs, Kirsten M.; Stein, Alfred; Bijker, Wietske

2017-01-01

This study investigates the incorporation of open source data into a Bayesian classification of urban land use from very high resolution (VHR) stereo satellite images. The adopted classification framework starts from urban land cover classification, proceeds to building-type characterization, and

[Physical fitness in relation to age and body build of young chess players].

Science.gov (United States)

Fornal-Urban, Agnieszka; Keska, Anna; Dobosz, Janusz; Nowacka-Dobosz, Sylwia

2009-01-01

Specificity of chess training promotes sedentary lifestyle and may reduce chess players participation in different physical activities. Limited physical activity leads to decrease of physical fitness and may augment the risk of overweight and obesity. It is suggested that these athletes will characterize more frequently lower physical fitness and weight/height proportions disorders. The aim of the study was evaluation of physical fitness and its relationship with age and body build of athletes. A sample of 73 individuals (35 girls--48% and 38 boys--52%) aged 8-19 years took part in this study. All competitors were members of national team and Polish representatives for the European and world chess championship. Chess players' physical fitness was measured by EUROFIT tests. With reference to the Polish population chess players characterized higher level of physical fitness. In six tests of EUROFIT chess players had better standardized results than controls. Sit ups (mean standardized result 0.842), shuttle run 10 x 5 m (0.577), standing broad jump (0.552) and flamingo balance (0.371) were very well performed by chess players. Only in one test, bent arm hang, sportsmen achieved worse results (-0.719). Permanent decrease of chess players' physical fitness with age was also observed. Although chess players' physical fitness was satisfied in comparison to age-matched control, it is recommended to include in their training more exercises developing strength. Because of changes in body build with age and decrease of physical fitness, chess players ought to participate in regular physical activity. Therefore chess organisers should provide the variety of active forms that can be chosen by competitors in their leisure time.

Automatic 3d Building Model Generations with Airborne LiDAR Data

Science.gov (United States)

Yastikli, N.; Cetin, Z.

2017-11-01

LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D

AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA

Directory of Open Access Journals (Sweden)

N. Yastikli

2017-11-01

Full Text Available LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified

Two-Stage Classification Approach for Human Detection in Camera Video in Bulk Ports

Directory of Open Access Journals (Sweden)

Mi Chao

2015-09-01

Full Text Available With the development of automation in ports, the video surveillance systems with automated human detection begun to be applied in open-air handling operation areas for safety and security. The accuracy of traditional human detection based on the video camera is not high enough to meet the requirements of operation surveillance. One of the key reasons is that Histograms of Oriented Gradients (HOG features of the human body will show great different between front & back standing (F&B and side standing (Side human body. Therefore, the final training for classifier will only gain a few useful specific features which have contribution to classification and are insufficient to support effective classification, while using the HOG features directly extracted by the samples from different human postures. This paper proposes a two-stage classification method to improve the accuracy of human detection. In the first stage, during preprocessing classification, images is mainly divided into possible F&B human body and not F&B human body, and then they were put into the second-stage classification among side human and non-human recognition. The experimental results in Tianjin port show that the two-stage classifier can improve the classification accuracy of human detection obviously.

New recommendations for building in tropical climates

Energy Technology Data Exchange (ETDEWEB)

Waal, H.B. de (ISOVER BV, Cappelle a/d IJssel (Netherlands))

1993-07-01

Traditional recommendations for building a thermally efficient or comfortable building in a tropical climate are briefly summarized. They suffer from three main drawbacks; they are not quantitative, partly incorrect and only for two climates; the hot dry and the warm humid. A new climate classification, made up of forty tropical climates is presented. Eight building elements, which affect the thermal system of a building, are distinguished. The method by which the new recommendations are derived, is discussed. The new recommendations are briefly presented. (Author)

Improved classification of small-scale urban watersheds using thematic mapper simulator data

Science.gov (United States)

Owe, M.; Ormsby, J. P.

1984-01-01

The utility of Landsat MSS classification methods in the case of small, highly urbanized hydrological basins containing complex land-use patterns is limited, and is plagued by misclassifications due to the spectral response similarity of many dissimilar surfaces. Landsat MSS data for the Conley Creek basin near Atlanta, Georgia, have been compared to thematic mapper simulator (TMS) data obtained on the same day by aircraft. The TMS data were able to alleviate many of the recurring patterns associated with MSS data, through bandwidth optimization, an increase of the number of spectral bands to seven, and an improvement of ground resolution to 30 m. The TMS is thereby able to detect small water bodies, powerline rights-of-way, and even individual buildings.

Specific classification of financial analysis of enterprise activity

Directory of Open Access Journals (Sweden)

Synkevych Nadiia I.

2014-01-01

Full Text Available Despite the fact that one can find a big variety of classifications of types of financial analysis of enterprise activity, which differ with their approach to classification and a number of classification features and their content, in modern scientific literature, their complex comparison and analysis of existing classification have not been done. This explains urgency of this study. The article studies classification of types of financial analysis of scientists and presents own approach to this problem. By the results of analysis the article improves and builds up a specific classification of financial analysis of enterprise activity and offers classification by the following features: objects, subjects, goals of study, automation level, time period of the analytical base, scope of study, organisation system, classification features of the subject, spatial belonging, sufficiency, information sources, periodicity, criterial base, method of data selection for analysis and time direction. All types of financial analysis significantly differ with their inherent properties and parameters depending on the goals of financial analysis. The developed specific classification provides subjects of financial analysis of enterprise activity with a possibility to identify a specific type of financial analysis, which would correctly meet the set goals.

Visual Alphabets: Video classification by end users

NARCIS (Netherlands)

Israël, Menno; van den Broek, Egon; van der Putten, Peter; den Uyl, Marten J.; Petrushin, Valery A.; Khan, Latifur

2007-01-01

The work presented here introduces a real-time automatic scene classifier within content-based video retrieval. In our envisioned approach end users like documentalists, not image processing experts, build classifiers interactively, by simply indicating positive examples of a scene. Classification

Dissimilarity Representations in Lung Parenchyma Classification

DEFF Research Database (Denmark)

Sørensen, Lauge Emil Borch Laurs; de Bruijne, Marleen

2009-01-01

parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram...... and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal...... are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung...

Classification and Filtering of Constrained Delaunay Triangulation for Automated Building Aggregation

Directory of Open Access Journals (Sweden)

GUO Peipei

2016-08-01

Full Text Available Building aggregation is an important part of research on large scale map generalization. A triangulation based approach is proposed from the perspective of shape features, six measure parameters of triangles in a constrained Delaunay triangulation are proposed. First of all, use the six measure parameters to determine which triangles are retained and which are erased. Then, the contours of retained triangles, as bridge areas between buildings, are automatically identified and right angle processed. And then, the buildings are aggregated with right angle feature retained by merging the bridge areas with connecting buildings. Finally, the approach is verified by being carried out on actual data. Experimental result shows that it is efficient and practical.

Fusion of Airborne Discrete-Return LiDAR and Hyperspectral Data for Land Cover Classification

Directory of Open Access Journals (Sweden)

Shezhou Luo

2015-12-01

Full Text Available Accurate land cover classification information is a critical variable for many applications. This study presents a method to classify land cover using the fusion data of airborne discrete return LiDAR (Light Detection and Ranging and CASI (Compact Airborne Spectrographic Imager hyperspectral data. Four LiDAR-derived images (DTM, DSM, nDSM, and intensity and CASI data (48 bands with 1 m spatial resolution were spatially resampled to 2, 4, 8, 10, 20 and 30 m resolutions using the nearest neighbor resampling method. These data were thereafter fused using the layer stacking and principal components analysis (PCA methods. Land cover was classified by commonly used supervised classifications in remote sensing images, i.e., the support vector machine (SVM and maximum likelihood (MLC classifiers. Each classifier was applied to four types of datasets (at seven different spatial resolutions: (1 the layer stacking fusion data; (2 the PCA fusion data; (3 the LiDAR data alone; and (4 the CASI data alone. In this study, the land cover category was classified into seven classes, i.e., buildings, road, water bodies, forests, grassland, cropland and barren land. A total of 56 classification results were produced, and the classification accuracies were assessed and compared. The results show that the classification accuracies produced from two fused datasets were higher than that of the single LiDAR and CASI data at all seven spatial resolutions. Moreover, we find that the layer stacking method produced higher overall classification accuracies than the PCA fusion method using both the SVM and MLC classifiers. The highest classification accuracy obtained (OA = 97.8%, kappa = 0.964 using the SVM classifier on the layer stacking fusion data at 1 m spatial resolution. Compared with the best classification results of the CASI and LiDAR data alone, the overall classification accuracies improved by 9.1% and 19.6%, respectively. Our findings also demonstrated that the

A Novel Classification Method for Syndrome Differentiation of Patients with AIDS

Directory of Open Access Journals (Sweden)

Yufeng Zhao

2015-01-01

Full Text Available We consider the analysis of an AIDS dataset where each patient is characterized by a list of symptoms and is labeled with one or more TCM syndromes. The task is to build a classifier that maps symptoms to TCM syndromes. We use the minimum reference set-based multiple instance learning (MRS-MIL method. The method identifies a list of representative symptoms for each syndrome and builds a Gaussian mixture model based on them. The models for all syndromes are then used for classification via Bayes rule. By relying on a subset of key symptoms for classification, MRS-MIL can produce reliable and high quality classification rules even on datasets with small sample size. On the AIDS dataset, it achieves average precision and recall 0.7736 and 0.7111, respectively. Those are superior to results achieved by alternative methods.

Women Build Long Bones With Less Cortical Mass Relative to Body Size and Bone Size Compared With Men.

Science.gov (United States)

Jepsen, Karl J; Bigelow, Erin M R; Schlecht, Stephen H

2015-08-01

The twofold greater lifetime risk of fracturing a bone for white women compared with white men and black women has been attributed in part to differences in how the skeletal system accumulates bone mass during growth. On average, women build more slender long bones with less cortical area compared with men. Although slender bones are known to have a naturally lower cortical area compared with wider bones, it remains unclear whether the relatively lower cortical area of women is consistent with their increased slenderness or is reduced beyond that expected for the sex-specific differences in bone size and body size. Whether this sexual dimorphism is consistent with ethnic background and is recapitulated in the widely used mouse model also remains unclear. We asked (1) do black women build bones with reduced cortical area compared with black men; (2) do white women build bones with reduced cortical area compared with white men; and (3) do female mice build bones with reduced cortical area compared with male mice? Bone strength and cross-sectional morphology of adult human and mouse bone were calculated from quantitative CT images of the femoral midshaft. The data were tested for normality and regression analyses were used to test for differences in cortical area between men and women after adjusting for body size and bone size by general linear model (GLM). Linear regression analysis showed that the femurs of black women had 11% lower cortical area compared with those of black men after adjusting for body size and bone size (women: mean=357.7 mm2; 95% confidence interval [CI], 347.9-367.5 mm2; men: mean=400.1 mm2; 95% CI, 391.5-408.7 mm2; effect size=1.2; pbone size (women: mean=350.1 mm2; 95% CI, 340.4-359.8 mm2; men: mean=394.3 mm2; 95% CI, 386.5-402.1 mm2; effect size=1.3; pbone size (female: mean=0.73 mm2; 95% CI, 0.71-0.74 mm2; male: mean=0.70 mm2; 95% CI, 0.68-0.71 mm2; effect size=0.74; p=0.04, GLM). Female femurs are not simply a more slender version of male

Radon Protection in the Technical Building Code

International Nuclear Information System (INIS)

Frutos, B.; Garcia, J. P.; Martin, J. L.; Olaya, M.; Serrano, J I.; Suarez, E.; Fernandez, J. A.; Rodrigo, F.

2003-01-01

Building construction in areas with high radon gas contamination in land requires the incorporation of certain measures in order to prevent the accumulation of this gas on the inside of buildings. These measures should be considered primarily in the design and construction phases and should take the area of the country into consideration where the construction will take place depending on the potential risk of radon entrance. Within the Technical Building Code, radon protection has been considered through general classification of the country and specific areas where building construction is to take place, in different risk categories and in the introduction of building techniques appropriate for each area. (Author) 17 refs

Co-occurrence Models in Music Genre Classification

DEFF Research Database (Denmark)

Ahrendt, Peter; Goutte, Cyril; Larsen, Jan

2005-01-01

Music genre classification has been investigated using many different methods, but most of them build on probabilistic models of feature vectors x\\_r which only represent the short time segment with index r of the song. Here, three different co-occurrence models are proposed which instead consider...... genre data set with a variety of modern music. The basis was a so-called AR feature representation of the music. Besides the benefit of having proper probabilistic models of the whole song, the lowest classification test errors were found using one of the proposed models....

Lossless Compression of Classification-Map Data

Science.gov (United States)

Hua, Xie; Klimesh, Matthew

2009-01-01

A lossless image-data-compression algorithm intended specifically for application to classification-map data is based on prediction, context modeling, and entropy coding. The algorithm was formulated, in consideration of the differences between classification maps and ordinary images of natural scenes, so as to be capable of compressing classification- map data more effectively than do general-purpose image-data-compression algorithms. Classification maps are typically generated from remote-sensing images acquired by instruments aboard aircraft (see figure) and spacecraft. A classification map is a synthetic image that summarizes information derived from one or more original remote-sensing image(s) of a scene. The value assigned to each pixel in such a map is the index of a class that represents some type of content deduced from the original image data for example, a type of vegetation, a mineral, or a body of water at the corresponding location in the scene. When classification maps are generated onboard the aircraft or spacecraft, it is desirable to compress the classification-map data in order to reduce the volume of data that must be transmitted to a ground station.

Sensitivity analysis of the energy demand of existing buildings based on the Danish Building and Dwelling Register

DEFF Research Database (Denmark)

Nielsen, Anker; Wittchen, Kim Bjarne; Bertelsen, Niels Haldor

2014-01-01

performance certificate. The Danish Building Research Institute has described a method that can be applied for estimating the energy demand of dwellings. This is based on the information in the Danish Building and Dwelling Register and requirements in the Danish Building Regulations from the year......The EU Directive on the Energy Performance of Buildings requires that energy certification of buildings should be implemented in Denmark so that houses that are sold or let should have an energy performance certificate. The result is that only a small part of existing houses has an energy...... of construction of the house. The result is an estimate of the energy demand of each building with a variation. This makes it possible to make an automatic classification of all buildings. The paper discusses the uncertainties and makes a sensitivity analysis to find the important parameters. The variations...

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.

CONTROL OF INDOOR ENVIRONMENTS VIA THE REGULATION OF BUILDING ENVELOPES

Directory of Open Access Journals (Sweden)

Mitja Košir

2011-01-01

Full Text Available The design of comfortable, healthy and stimulating indoor environments in buildings has a direct impact on the users and on energy consumption, as well as on the wider soci-economic environment of society.The indoor environment of buildings is defined with the formulation of the building envelope, which functions as an interface between the internal and external environments and its users. A properly designed, flexible and adequately controlled building envelope is a starting point in the formulation of a high-quality indoor environment. The systematic treatment of the indoor environment and building envelope from a user’s point of view represents an engineering approach that enables the holistic treatment of buildings, as well as integrated components and systems. The presented division of indoor environment in terms of visual, thermal, olfactory, acoustic and ergonomic sub-environments enables the classification and selection of crucial factors influencing design. This selection and classification can be implemented in the design, as well as in control applications of the building envelope. The implementation of the approach described is demonstrated with an example of an automated control system for the internal environment of an office in the building of the Faculty of Civil and Geodetic Engineering.

Classification of Polarimetric SAR Data Using Dictionary Learning

DEFF Research Database (Denmark)

Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg; Dahl, Anders Lindbjerg

2012-01-01

This contribution deals with classification of multilook fully polarimetric synthetic aperture radar (SAR) data by learning a dictionary of crop types present in the Foulum test site. The Foulum test site contains a large number of agricultural fields, as well as lakes, forests, natural vegetation......, grasslands and urban areas, which make it ideally suited for evaluation of classification algorithms. Dictionary learning centers around building a collection of image patches typical for the classification problem at hand. This requires initial manual labeling of the classes present in the data and is thus...... a method for supervised classification. Sparse coding of these image patches aims to maintain a proficient number of typical patches and associated labels. Data is consecutively classified by a nearest neighbor search of the dictionary elements and labeled with probabilities of each class. Each dictionary...

The effect of fasting and body reserves on cold tolerance in 2 pit-building insect predators.

Science.gov (United States)

Scharf, Inon; Daniel, Alma; MacMillan, Heath Andrew; Katz, Noa

2017-06-01

Pit-building antlions and wormlions are 2 distantly-related insect species, whose larvae construct pits in loose soil to trap small arthropod prey. This convergent evolution of natural histories has led to additional similarities in their natural history and ecology, and thus, these 2 species encounter similar abiotic stress (such as periodic starvation) in their natural habitat. Here, we measured the cold tolerance of the 2 species and examined whether recent feeding or food deprivation, as well as body composition (body mass and lipid content) and condition (quantified as mass-to-size residuals) affect their cold tolerance. In contrast to other insects, in which food deprivation either enhanced or impaired cold tolerance, prolonged fasting had no effect on the cold tolerance of either species, which had similar cold tolerance. The 2 species differed, however, in how cold tolerance related to body mass and lipid content: although body mass was positively correlated with the wormlion cold tolerance, lipid content was a more reliable predictor of cold tolerance in the antlions. Cold tolerance also underwent greater change with ontogeny in wormlions than in antlions. We discuss possible reasons for this lack of effect of food deprivation on both species' cold tolerance, such as their high starvation tolerance (being sit-and-wait predators).

Influence of the Risk-Contributing Factors on the Financing of the Investment Project for Building of Intelligent Buildings

OpenAIRE

Voytolovskiy Nikolay; Trebukhin Anatoliy; Shoshinov Vitaly

2017-01-01

This article provides the generic classification of risks of the investment projects for the construction of intelligent buildings which differ by the detachment of the subjective perception of risk by the investor. Risk and uncertainty were justified as system characteristics of the investment projects for the construction of intelligent buildings. Characteristics of the development was given in the context of project management. Methodical schemes of the development of the investment projec...

A deep learning pipeline for Indian dance style classification

Science.gov (United States)

Dewan, Swati; Agarwal, Shubham; Singh, Navjyoti

2018-04-01

In this paper, we address the problem of dance style classification to classify Indian dance or any dance in general. We propose a 3-step deep learning pipeline. First, we extract 14 essential joint locations of the dancer from each video frame, this helps us to derive any body region location within the frame, we use this in the second step which forms the main part of our pipeline. Here, we divide the dancer into regions of important motion in each video frame. We then extract patches centered at these regions. Main discriminative motion is captured in these patches. We stack the features from all such patches of a frame into a single vector and form our hierarchical dance pose descriptor. Finally, in the third step, we build a high level representation of the dance video using the hierarchical descriptors and train it using a Recurrent Neural Network (RNN) for classification. Our novelty also lies in the way we use multiple representations for a single video. This helps us to: (1) Overcome the RNN limitation of learning small sequences over big sequences such as dance; (2) Extract more data from the available dataset for effective deep learning by training multiple representations. Our contributions in this paper are three-folds: (1) We provide a deep learning pipeline for classification of any form of dance; (2) We prove that a segmented representation of a dance video works well with sequence learning techniques for recognition purposes; (3) We extend and refine the ICD dataset and provide a new dataset for evaluation of dance. Our model performs comparable or better in some cases than the state-of-the-art on action recognition benchmarks.

Sensitivity analysis of the energy demand of existing buildings based on the Danish Building and Dwelling Register (BBR)

DEFF Research Database (Denmark)

Nielsen, Anker; Wittchen, Kim Bjarne; Bertelsen, Niels Haldor

2014-01-01

performance certificate. The Danish Building Research Institute has described a method that can be applied for estimating the energy demand of dwellings. This is based on the information in the Danish Building and Dwelling Register and requirements in the Danish Building Regulations from the year......The EU Directive on the Energy Performance of Buildings requires that energy certification of buildings should be implemented in Denmark so that houses that are sold or let should have an energy performance certificate. The result is that only a small part of existing houses has an energy...... of construction of the house. The result is an estimate of the energy demand of each building with a variation. This makes it possible to make an automatic classification of all buildings. The paper discusses the uncertainties and makes a sensitivity analysis to find the important parameters. The variations...

A Method to Estimate Energy Demand in Existing Buildings Based on the Danish Building and Dwellings Register (BBR)

DEFF Research Database (Denmark)

Nielsen, Anker; Bertelsen, Niels Haldor; Wittchen, Kim Bjarne

2013-01-01

an energy label. The Danish Building Research Institute has described a method that can be used to estimate the energy demand in buildings specially dwellings. This is based on the information in the Danish Building and Dwelling Register (BBR) and information on building regulations at construction year......The Energy Performance Directive requires energy certifications for buildings. This is implemented in Denmark so that houses that are sold must have an energy performance label based on an evaluation from a visit to the building. The result is that only a small part of the existing houses has...... for the house. The result is an estimate for energy demand in each building with a variation. This makes it possible to make an automatic classification of all buildings. Then it is possible to find houses in need for thermal improvements. This method is tested for single family houses and flats. The paper...

Radon safety in terms of energy efficiency classification of buildings

Science.gov (United States)

Vasilyev, A.; Yarmoshenko, I.; Zhukovsky, M.

2017-06-01

According to the results of survey in Ekaterinburg, Russia, indoor radon concentrations above city average level have been found in each of the studied buildings with high energy efficiency class. Measures to increase energy efficiency were confirmed to decrease the air exchange rate and accumulation of high radon concentrations indoors. Despite of recommendations to use mechanical ventilation with heat recovery as the main scenario for reducing elevated radon concentrations in energy-efficient buildings, the use of such systems did not show an obvious advantage. In real situation, mechanical ventilation system is not used properly both in the automatic and manual mode, which does not give an obvious advantage over natural ventilation in the climate of the Middle Urals in Ekaterinburg. Significant number of buildings with a high class of energy efficiency and built using modern space-planning decisions contributes to an increase in the average radon concentration. Such situation contradicts to “as low as reasonable achievable” principle of the radiation protection.

CIN classification and prediction using machine learning methods

Science.gov (United States)

Chirkina, Anastasia; Medvedeva, Marina; Komotskiy, Evgeny

2017-06-01

The aim of this paper is a comparison of the existing classification algorithms with different parameters, and selection those ones, which allows solving the problem of primary diagnosis of cervical intraepithelial neoplasia (CIN), as it characterizes the condition of the body in the precancerous stage. The paper describes a feature selection process, as well as selection of the best models for a multiclass classification.

Typological diversity of tall buildings and complexes in relation to their functional structure

Science.gov (United States)

Generalov, Viktor P.; Generalova, Elena M.; Kalinkina, Nadezhda A.; Zhdanova, Irina V.

2018-03-01

The paper focuses on peculiarities of tall buildings and complexes, their typology and its formation in relation to their functional structure. The research is based on the analysis of tall buildings and complexes and identifies the following main functional elements of their formation: residential, administrative (office), hotel elements. The paper also considers the following services as «disseminated» in the space-planning structure: shops, medicine, entertainment, kids and sports facilities, etc., their location in the structure of the total bulk of the building and their impact on typological diversity. Research results include suggestions to add such concepts as «single-function tall buildings» and «mixed-use tall buildings and complexes» into the classification of tall buildings. In addition, if a single-function building or complex performs serving functions, it is proposed to add such concepts as «a residential tall building (complex) with provision of services», «an administrative (public) tall building (complex) with provision of services» into the classification of tall buildings. For mixed-use buildings and complexes the following terms are suggested: «a mixed-use tall building with provision of services», «a mixed-use tall complex with provision of services».

Energy Performance Certificate of building and confidence interval in assessment: An Italian case study

International Nuclear Information System (INIS)

Tronchin, Lamberto; Fabbri, Kristian

2012-01-01

The Directive 2002/91/CE introduced the Energy Performance Certificate (EPC), an energy policy tool. The aim of the EPC is to inform building buyers about the energy performance and energy costs of buildings. The EPCs represent a specific energy policy tool to orient the building sector and real-estate markets toward higher energy efficiency buildings. The effectiveness of the EPC depends on two factors: •The accuracy of energy performance evaluation made by independent experts. •The capability of the energy classification and of the scale of energy performance to control the energy index fluctuations. In this paper, the results of a case study located in Italy are shown. In this example, 162 independent technicians on energy performance of building evaluation have studied the same building. The results reveal which part of confidence intervals is dependent on software misunderstanding and that the energy classification ranges are able to tolerate the fluctuation of energy indices. The example was chosen in accordance with the legislation of the Emilia-Romagna Region on Energy Efficiency of Buildings. Following these results, some thermo-economic evaluation related to building and energy labelling are illustrated, as the EPC, which is an energy policy tool for the real-estate market and building sector to find a way to build or retrofit an energy efficiency building. - Highlights: ► Evaluation of the accuracy of energy performance of buildings in relation with the knowledge of independent experts. ► Round robin test based on 162 case studies on the confidence intervals expressed by independent experts. ► Statistical considerations between the confidence intervals expressed by independent experts and energy simulation software. ► Relation between “proper class” in energy classification of buildings and confidence intervals of independent experts.

Assessing reserve-building pursuits and person characteristics: psychometric validation of the Reserve-Building Measure

NARCIS (Netherlands)

Schwartz, Carolyn E.; Michael, Wesley; Zhang, Jie; Rapkin, Bruce D.; Sprangers, Mirjam A. G.

2018-01-01

A growing body of research suggests that regularly engaging in stimulating activities across multiple domains-physical, cultural, intellectual, communal, and spiritual-builds resilience. This project investigated the psychometric characteristics of the DeltaQuest Reserve-Building Measure for use in

Effects of prey macronutrient content on body composition and nutrient intake in a web-building spider.

Directory of Open Access Journals (Sweden)

Jesse Hawley

Full Text Available The nutritional composition of diets can vary widely in nature and have large effects on the growth, reproduction and survival of animals. Many animals, especially herbivores, will tightly regulate the nutritional composition of their body, which has been referred to as nutritional homeostasis. We tested how experimental manipulation of the lipid and protein content of live prey affected the nutrient reserves and subsequent diet regulation of web-building spiders, Argiope keyserlingi. Live locusts were injected with experimental solutions containing specific amounts of lipid and protein and then fed to spiders. The nutrient composition of the spiders' bodies was directly related to the nutrient composition of the prey on which they fed. We then conducted an experiment where spiders were fed either high lipid or high protein prey and subsequently provided with two large unmanipulated locusts. Prior diet did not affect the amount or ratio of lipid and protein ingested by spiders when feeding on unmanipulated prey. Argiope keyserlingi were flexible in the storage of lipid and protein in their bodies and did not bias their extraction of nutrients from prey to compensate for previously biased diets. Some carnivores, especially those that experience frequent food limitation, may be less likely to strictly regulate their body composition than herbivores because food limitation may encourage opportunistic ingestion and assimilation of nutrients.

Land Cover and Land Use Classification with TWOPAC: towards Automated Processing for Pixel- and Object-Based Image Classification

Directory of Open Access Journals (Sweden)

Stefan Dech

2012-09-01

Full Text Available We present a novel and innovative automated processing environment for the derivation of land cover (LC and land use (LU information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS, as introduced by the Open Geospatial Consortium (OGC, are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective.

CLASSIFICATION OF INFORMAL SETTLEMENTS THROUGH THE INTEGRATION OF 2D AND 3D FEATURES EXTRACTED FROM UAV DATA

Directory of Open Access Journals (Sweden)

C. M. Gevaert

2016-06-01

Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

MULTI-TEMPORAL CLASSIFICATION AND CHANGE DETECTION USING UAV IMAGES

Directory of Open Access Journals (Sweden)

S. Makuti

2018-05-01

Full Text Available In this paper different methodologies for the classification and change detection of UAV image blocks are explored. UAV is not only the cheapest platform for image acquisition but it is also the easiest platform to operate in repeated data collections over a changing area like a building construction site. Two change detection techniques have been evaluated in this study: the pre-classification and the post-classification algorithms. These methods are based on three main steps: feature extraction, classification and change detection. A set of state of the art features have been used in the tests: colour features (HSV, textural features (GLCM and 3D geometric features. For classification purposes Conditional Random Field (CRF has been used: the unary potential was determined using the Random Forest algorithm while the pairwise potential was defined by the fully connected CRF. In the performed tests, different feature configurations and settings have been considered to assess the performance of these methods in such challenging task. Experimental results showed that the post-classification approach outperforms the pre-classification change detection method. This was analysed using the overall accuracy, where by post classification have an accuracy of up to 62.6 % and the pre classification change detection have an accuracy of 46.5 %. These results represent a first useful indication for future works and developments.

Classification of jet fuels by fuzzy rule-building expert systems applied to three-way data by fast gas chromatography--fast scanning quadrupole ion trap mass spectrometry.

Science.gov (United States)

Sun, Xiaobo; Zimmermann, Carolyn M; Jackson, Glen P; Bunker, Christopher E; Harrington, Peter B

2011-01-30

A fast method that can be used to classify unknown jet fuel types or detect possible property changes in jet fuel physical properties is of paramount interest to national defense and the airline industries. While fast gas chromatography (GC) has been used with conventional mass spectrometry (MS) to study jet fuels, fast GC was combined with fast scanning MS and used to classify jet fuels into lot numbers or origin for the first time by using fuzzy rule-building expert system (FuRES) classifiers. In the process of building classifiers, the data were pretreated with and without wavelet transformation and evaluated with respect to performance. Principal component transformation was used to compress the two-way data images prior to classification. Jet fuel samples were successfully classified with 99.8 ± 0.5% accuracy for both with and without wavelet compression. Ten bootstrapped Latin partitions were used to validate the generalized prediction accuracy. Optimized partial least squares (o-PLS) regression results were used as positively biased references for comparing the FuRES prediction results. The prediction results for the jet fuel samples obtained with these two methods were compared statistically. The projected difference resolution (PDR) method was also used to evaluate the fast GC and fast MS data. Two batches of aliquots of ten new samples were prepared and run independently 4 days apart to evaluate the robustness of the method. The only change in classification parameters was the use of polynomial retention time alignment to correct for drift that occurred during the 4-day span of the two collections. FuRES achieved perfect classifications for four models of uncompressed three-way data. This fast GC/fast MS method furnishes characteristics of high speed, accuracy, and robustness. This mode of measurement may be useful as a monitoring tool to track changes in the chemical composition of fuels that may also lead to property changes. Copyright © 2010

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

Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Martin Längkvist

2016-04-01

Full Text Available The availability of high-resolution remote sensing (HRRS data has opened up the possibility for new interesting applications, such as per-pixel classification of individual objects in greater detail. This paper shows how a convolutional neural network (CNN can be applied to multispectral orthoimagery and a digital surface model (DSM of a small city for a full, fast and accurate per-pixel classification. The predicted low-level pixel classes are then used to improve the high-level segmentation. Various design choices of the CNN architecture are evaluated and analyzed. The investigated land area is fully manually labeled into five categories (vegetation, ground, roads, buildings and water, and the classification accuracy is compared to other per-pixel classification works on other land areas that have a similar choice of categories. The results of the full classification and segmentation on selected segments of the map show that CNNs are a viable tool for solving both the segmentation and object recognition task for remote sensing data.

Body size mediates social and environmental effects on nest building behaviour in a fish with paternal care.

Science.gov (United States)

Lehtonen, Topi K; Lindström, Kai; Wong, Bob B M

2015-07-01

Body size, social setting, and the physical environment can all influence reproductive behaviours, but their interactions are not well understood. Here, we investigated how male body size, male-male competition, and water turbidity influence nest-building behaviour in the sand goby (Pomatoschistus minutus), a marine fish with exclusive paternal care. We found that environmental and social factors affected the nest characteristics of small and large males differently. In particular, association between male size and the level of nest elaboration (i.e. the amount of sand piled on top of the nest) was positive only under clear water conditions. Similarly, male size and nest entrance size were positively associated only in the absence of competition. Such interactions may, in turn, help to explain the persistence of variation in reproductive behaviours, which-due to their importance in offspring survival-are otherwise expected to be under strong balancing selection.

Joint Feature Selection and Classification for Multilabel Learning.

Science.gov (United States)

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Active Learning of Classification Models with Likert-Scale Feedback.

Science.gov (United States)

Xue, Yanbing; Hauskrecht, Milos

2017-01-01

Annotation of classification data by humans can be a time-consuming and tedious process. Finding ways of reducing the annotation effort is critical for building the classification models in practice and for applying them to a variety of classification tasks. In this paper, we develop a new active learning framework that combines two strategies to reduce the annotation effort. First, it relies on label uncertainty information obtained from the human in terms of the Likert-scale feedback. Second, it uses active learning to annotate examples with the greatest expected change. We propose a Bayesian approach to calculate the expectation and an incremental SVM solver to reduce the time complexity of the solvers. We show the combination of our active learning strategy and the Likert-scale feedback can learn classification models more rapidly and with a smaller number of labeled instances than methods that rely on either Likert-scale labels or active learning alone.

School Building Organisation in Greece.

Science.gov (United States)

PEB Exchange, 2001

2001-01-01

Discusses the past and current organizational structure of Greece's School Building Organisation, a body established to work with government agencies in the design and construction of new buildings and the provisioning of educational equipment. Future planning to incorporate culture and creativity, sports, and laboratory learning in modern school…

Safety analysis of the nuclear chemistry Building 151

International Nuclear Information System (INIS)

Kvam, D.

1984-01-01

This report summarizes the results of a safety analysis that was done on Building 151. The report outlines the methodology, the analysis, and the findings that led to the low hazard classification. No further safety evaluation is indicated at this time. 5 tables

Link prediction boosted psychiatry disorder classification for functional connectivity network

Science.gov (United States)

Li, Weiwei; Mei, Xue; Wang, Hao; Zhou, Yu; Huang, Jiashuang

2017-02-01

Functional connectivity network (FCN) is an effective tool in psychiatry disorders classification, and represents cross-correlation of the regional blood oxygenation level dependent signal. However, FCN is often incomplete for suffering from missing and spurious edges. To accurate classify psychiatry disorders and health control with the incomplete FCN, we first `repair' the FCN with link prediction, and then exact the clustering coefficients as features to build a weak classifier for every FCN. Finally, we apply a boosting algorithm to combine these weak classifiers for improving classification accuracy. Our method tested by three datasets of psychiatry disorder, including Alzheimer's Disease, Schizophrenia and Attention Deficit Hyperactivity Disorder. The experimental results show our method not only significantly improves the classification accuracy, but also efficiently reconstructs the incomplete FCN.

Ethnic differences in the relationship between body mass index and percentage body fat among Asian children from different backgrounds.

Science.gov (United States)

Liu, Ailing; Byrne, Nuala M; Kagawa, Masaharu; Ma, Guansheng; Poh, Bee Koon; Ismail, Mohammad Noor; Kijboonchoo, Kallaya; Nasreddine, Lara; Trinidad, Trinidad Palad; Hills, Andrew P

2011-11-01

Overweight and obesity in Asian children are increasing at an alarming rate; therefore a better understanding of the relationship between BMI and percentage body fat (%BF) in this population is important. A total of 1039 children aged 8-10 years, encompassing a wide BMI range, were recruited from China, Lebanon, Malaysia, The Philippines and Thailand. Body composition was determined using the 2H dilution technique to quantify total body water and subsequently fat mass, fat-free mass and %BF. Ethnic differences in the BMI-%BF relationship were found; for example, %BF in Filipino boys was approximately 2 % lower than in their Thai and Malay counterparts. In contrast, Thai girls had approximately 2.0 % higher %BF values than in their Chinese, Lebanese, Filipino and Malay counterparts at a given BMI. However, the ethnic difference in the BMI-%BF relationship varied by BMI. Compared with Caucasian children of the same age, Asian children had 3-6 units lower BMI at a given %BF. Approximately one-third of the obese Asian children (%BF above 25 % for boys and above 30 % for girls) in the study were not identified using the WHO classification and more than half using the International Obesity Task Force classification. Use of the Chinese classification increased the sensitivity. Results confirmed the necessity to consider ethnic differences in body composition when developing BMI cut-points and other obesity criteria in Asian children.

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.

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

Science.gov (United States)

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

2015-05-01

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

Voice classification and vocal tract of singers: a study of x-ray images and morphology.

Science.gov (United States)

Roers, Friederike; Mürbe, Dirk; Sundberg, Johan

2009-01-01

This investigation compares vocal tract dimensions and the classification of singer voices by examining an x-ray material assembled between 1959 and 1991 of students admitted to the solo singing education at the University of Music, Dresden, Germany. A total of 132 images were available to analysis. Different classifications' values of the lengths of the total vocal tract, the pharynx, and mouth cavities as well as of the relative position of the larynx, the height of the palatal arch, and the estimated vocal fold length were analyzed statistically, and some significant differences were found. The length of the pharynx cavity seemed particularly influential on the total vocal tract length, which varied systematically with classification. Also studied were the relationships between voice classification and the body height and weight and the body mass index. The data support the hypothesis that there are consistent morphological vocal tract differences between singers of different voice classifications.

The United Nations Framework Classification for World Petroleum Resources

Science.gov (United States)

Ahlbrandt, T.S.; Blystad, P.; Young, E.D.; Slavov, S.; Heiberg, S.

2003-01-01

The United Nations has developed an international framework classification for solid fuels and minerals (UNFC). This is now being extended to petroleum by building on the joint classification of the Society of Petroleum Engineers (SPE), the World Petroleum Congresses (WPC) and the American Association of Petroleum Geologists (AAPG). The UNFC is a 3-dimansional classification. This: Is necessary in order to migrate accounts of resource quantities that are developed on one or two of the axes to the common basis; Provides for more precise reporting and analysis. This is particularly useful in analyses of contingent resources. The characteristics of the SPE/WPC/AAPG classification has been preserved and enhanced to facilitate improved international and national petroleum resource management, corporate business process management and financial reporting. A UN intergovernmental committee responsible for extending the UNFC to extractive energy resources (coal, petroleum and uranium) will meet in Geneva on October 30th and 31st to review experiences gained and comments received during 2003. A recommended classification will then be delivered for consideration to the United Nations through the Committee on Sustainable Energy of the Economic Commission for Europe (UN ECE).

Sound classification schemes in Europe - Quality classes intended for renovated housing

DEFF Research Database (Denmark)

Rasmussen, Birgit

2010-01-01

exposure in the home included in the proposed main objectives for a housing policy. In most countries in Europe, building regulations specify minimum requirements concerning acoustical conditions for new dwellings. In addition, several countries have introduced sound classification schemes with classes...... intended to reflect different levels of acoustical comfort. Consequently, acoustic requirements for a dwelling can be specified as the legal minimum requirements or as a specific class in a classification scheme. Most schemes have both higher classes than corresponding to the regulatory requirements...

Body schema building during childhood and adolescence: a neurosensory approach.

Science.gov (United States)

Assaiante, C; Barlaam, F; Cignetti, F; Vaugoyeau, M

2014-01-01

In order to perceive and act in its environment, the individual's body and its interactions with the sensory and social environment are represented in the brain. This internal representation of the moving body segments is labeled the body schema. Throughout life, body schema develops based on the sensory information used by the moving body and by its interactions with the environment including other people. Internal representations including body schema and representations of the outside world develop with learning and actions throughout ontogenesis and are constantly updated based on different sensory inputs. The aim of this review is to present some concepts and experimental data about body schema, internal representations and updating process during childhood and adolescence, as obtained using a neurosensory approach. From our developmental studies, it was possible to explore the slow maturation of the sensorimotor representations by examining the anticipatory control. By manipulating proprioceptive and visual information, which are at the heart of the construction of body schema, we wished to highlight notable differences between adolescents and young adults on both a postural and perceptual level, which confirms the late maturation of multisensory integration for central motor control. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Quantum Simulation with Circuit-QED Lattices: from Elementary Building Blocks to Many-Body Theory

Science.gov (United States)

Zhu, Guanyu

Recent experimental and theoretical progress in superconducting circuits and circuit QED (quantum electrodynamics) has helped to develop high-precision techniques to control, manipulate, and detect individual mesoscopic quantum systems. A promising direction is hence to scale up from individual building blocks to form larger-scale quantum many-body systems. Although realizing a scalable fault-tolerant quantum computer still faces major barriers of decoherence and quantum error correction, it is feasible to realize scalable quantum simulators with state-of-the-art technology. From the technological point of view, this could serve as an intermediate stage towards the final goal of a large-scale quantum computer, and could help accumulating experience with the control of quantum systems with a large number of degrees of freedom. From the physical point of view, this opens up a new regime where condensed matter systems can be simulated and studied, here in the context of strongly correlated photons and two-level systems. In this thesis, we mainly focus on two aspects of circuit-QED based quantum simulation. First, we discuss the elementary building blocks of the quantum simulator, in particular a fluxonium circuit coupled to a superconducting resonator. We show the interesting properties of the fluxonium circuit as a qubit, including the unusual structure of its charge matrix elements. We also employ perturbation theory to derive the effective Hamiltonian of the coupled system in the dispersive regime, where qubit and the photon frequencies are detuned. The observables predicted with our theory, including dispersive shifts and Kerr nonlinearity, are compared with data from experiments, such as homodyne transmission and two-tone spectroscopy. These studies also relate to the problem of detection in a circuit-QED quantum simulator. Second, we study many-body physics of circuit-QED lattices, serving as quantum simulators. In particular, we focus on two different

THE ISPRS BENCHMARK ON URBAN OBJECT CLASSIFICATION AND 3D BUILDING RECONSTRUCTION

Directory of Open Access Journals (Sweden)

F. Rottensteiner

2012-07-01

Full Text Available For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of airborne image and laserscanner data, has been made available to the scientific community. Researchers were encouraged to submit results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current airborne sensor data, but also common problems of state-of-the-art methods.

Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods

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Zhiling Guo

2016-03-01

Full Text Available In this study, a method based on supervised machine learning is proposed to identify village buildings from open high-resolution remote sensing images. We select Google Earth (GE RGB images to perform the classification in order to examine its suitability for village mapping, and investigate the feasibility of using machine learning methods to provide automatic classification in such fields. By analyzing the characteristics of GE images, we design different features on the basis of two kinds of supervised machine learning methods for classification: adaptive boosting (AdaBoost and convolutional neural networks (CNN. To recognize village buildings via their color and texture information, the RGB color features and a large number of Haar-like features in a local window are utilized in the AdaBoost method; with multilayer trained networks based on gradient descent algorithms and back propagation, CNN perform the identification by mining deeper information from buildings and their neighborhood. Experimental results from the testing area at Savannakhet province in Laos show that our proposed AdaBoost method achieves an overall accuracy of 96.22% and the CNN method is also competitive with an overall accuracy of 96.30%.

Deteksi Penyakit Dengue Hemorrhagic Fever dengan Pendekatan One Class Classification

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Zida Ziyan Azkiya

2017-10-01

Full Text Available Two class classification problem maps input into two target classes. In certain cases, training data is available only in the form of a single class, as in the case of Dengue Hemorrhagic Fever (DHF patients, where only data of positive patients is available. In this paper, we report our experiment in building a classification model for detecting DHF infection using One Class Classification (OCC approach. Data from this study is sourced from laboratory tests of patients with dengue fever. The OCC methods compared are One-Class Support Vector Machine and One-Class K-Means. The result shows SVM method obtained precision value = 1.0, recall = 0.993, f-1 score = 0.997, and accuracy of 99.7% while the K-Means method obtained precision value = 0.901, recall = 0.973, f- 1 score = 0.936, and accuracy of 93.3%. This indicates that the SVM method is slightly superior to K-Means for One-Class Classification of DHF patients.

A graduated food addiction classification approach significantly differentiates obesity among people with type 2 diabetes.

Science.gov (United States)

Raymond, Karren-Lee; Kannis-Dymand, Lee; Lovell, Geoff P

2016-10-01

This study examined a graduated severity level approach to food addiction classification against associations with World Health Organization obesity classifications (body mass index, kg/m 2 ) among 408 people with type 2 diabetes. A survey including the Yale Food Addiction Scale and several demographic questions demonstrated four distinct Yale Food Addiction Scale symptom severity groups (in line with Diagnostic and Statistical Manual of Mental Disorders (5th ed.) severity indicators): non-food addiction, mild food addiction, moderate food addiction and severe food addiction. Analysis of variance with post hoc tests demonstrated each severity classification group was significantly different in body mass index, with each grouping being associated with increased World Health Organization obesity classifications. These findings have implications for diagnosing food addiction and implementing treatment and prevention methodologies of obesity among people with type 2 diabetes.

Automated mapping of building facades by machine learning

DEFF Research Database (Denmark)

Höhle, Joachim

2014-01-01

Facades of buildings contain various types of objects which have to be recorded for information systems. The article describes a solution for this task focussing on automated classification by means of machine learning techniques. Stereo pairs of oblique images are used to derive 3D point clouds...

Capacity building in rural Guatemala by implementing a solid waste management program

International Nuclear Information System (INIS)

Zarate, M.A.; Slotnick, J.; Ramos, M.

2008-01-01

The development and implementation of a solid waste management program served to build local capacity in San Mateo Ixtatan between 2002 and 2003 as part of a public health action plan. The program was developed and implemented in two phases: (1) the identification and education of a working team from the community; and (2) the completion of a solid waste classification and quantification study. Social capital and the water cycle were two public health approaches utilized to build a sustainable program. The activities accomplished gained support from the community and municipal authorities. A description of the tasks completed and findings of the solid waste classification and quantification performed by a local working group are presented in this paper

A Hierarchical Object-oriented Urban Land Cover Classification Using WorldView-2 Imagery and Airborne LiDAR data

Science.gov (United States)

Wu, M. F.; Sun, Z. C.; Yang, B.; Yu, S. S.

2016-11-01

In order to reduce the “salt and pepper” in pixel-based urban land cover classification and expand the application of fusion of multi-source data in the field of urban remote sensing, WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data were used to improve the classification of urban land cover. An approach of object- oriented hierarchical classification was proposed in our study. The processing of proposed method consisted of two hierarchies. (1) In the first hierarchy, LiDAR Normalized Digital Surface Model (nDSM) image was segmented to objects. The NDVI, Costal Blue and nDSM thresholds were set for extracting building objects. (2) In the second hierarchy, after removing building objects, WorldView-2 fused imagery was obtained by Haze-ratio-based (HR) fusion, and was segmented. A SVM classifier was applied to generate road/parking lot, vegetation and bare soil objects. (3) Trees and grasslands were split based on an nDSM threshold (2.4 meter). The results showed that compared with pixel-based and non-hierarchical object-oriented approach, proposed method provided a better performance of urban land cover classification, the overall accuracy (OA) and overall kappa (OK) improved up to 92.75% and 0.90. Furthermore, proposed method reduced “salt and pepper” in pixel-based classification, improved the extraction accuracy of buildings based on LiDAR nDSM image segmentation, and reduced the confusion between trees and grasslands through setting nDSM threshold.

Influence of the Risk-Contributing Factors on the Financing of the Investment Project for Building of Intelligent Buildings

Directory of Open Access Journals (Sweden)

Voytolovskiy Nikolay

2017-01-01

Full Text Available This article provides the generic classification of risks of the investment projects for the construction of intelligent buildings which differ by the detachment of the subjective perception of risk by the investor. Risk and uncertainty were justified as system characteristics of the investment projects for the construction of intelligent buildings. Characteristics of the development was given in the context of project management. Methodical schemes of the development of the investment project risks were specified on the basis of interconnection of risk and project effectiveness. Risk management procedure at realization of the developer project was developed.

Review of Development Survey of Phase Change Material Models in Building Applications

Directory of Open Access Journals (Sweden)

Hussein J. Akeiber

2014-01-01

Full Text Available The application of phase change materials (PCMs in green buildings has been increasing rapidly. PCM applications in green buildings include several development models. This paper briefly surveys the recent research and development activities of PCM technology in building applications. Firstly, a basic description of phase change and their principles is provided; the classification and applications of PCMs are also included. Secondly, PCM models in buildings are reviewed and discussed according to the wall, roof, floor, and cooling systems. Finally, conclusions are presented based on the collected data.

Photovoltaic building sheathing element with anti-slide features

Science.gov (United States)

Keenihan, James R.; Langmaid, Joseph A.; Lopez, Leonardo C.

2015-09-08

The present invention is premised` upon an assembly that includes at least a photovoltaic building sheathing element capable of being affixed on a building structure, the photovoltaic building sheathing element. The element including a photovoltaic cell assembly, a body portion attached to one or more portions of the photovoltaic cell assembly; and at feast a first and a second connector assembly capable of directly or indirectly electrically connecting the photovoltaic cell assembly to one or more adjoining devices; wherein the body portion includes one or more geometric features adapted to engage a vertically adjoining device before installation.

On the International Agency for Research on Cancer classification of glyphosate as a probable human carcinogen.

Science.gov (United States)

Tarone, Robert E

2018-01-01

The recent classification by International Agency for Research on Cancer (IARC) of the herbicide glyphosate as a probable human carcinogen has generated considerable discussion. The classification is at variance with evaluations of the carcinogenic potential of glyphosate by several national and international regulatory bodies. The basis for the IARC classification is examined under the assumptions that the IARC criteria are reasonable and that the body of scientific studies determined by IARC staff to be relevant to the evaluation of glyphosate by the Monograph Working Group is sufficiently complete. It is shown that the classification of glyphosate as a probable human carcinogen was the result of a flawed and incomplete summary of the experimental evidence evaluated by the Working Group. Rational and effective cancer prevention activities depend on scientifically sound and unbiased assessments of the carcinogenic potential of suspected agents. Implications of the erroneous classification of glyphosate with respect to the IARC Monograph Working Group deliberative process are discussed.

ICF-based classification and measurement of functioning.

Science.gov (United States)

Stucki, G; Kostanjsek, N; Ustün, B; Cieza, A

2008-09-01

If we aim towards a comprehensive understanding of human functioning and the development of comprehensive programs to optimize functioning of individuals and populations we need to develop suitable measures. The approval of the International Classification, Disability and Health (ICF) in 2001 by the 54th World Health Assembly as the first universally shared model and classification of functioning, disability and health marks, therefore an important step in the development of measurement instruments and ultimately for our understanding of functioning, disability and health. The acceptance and use of the ICF as a reference framework and classification has been facilitated by its development in a worldwide, comprehensive consensus process and the increasing evidence regarding its validity. However, the broad acceptance and use of the ICF as a reference framework and classification will also depend on the resolution of conceptual and methodological challenges relevant for the classification and measurement of functioning. This paper therefore describes first how the ICF categories can serve as building blocks for the measurement of functioning and then the current state of the development of ICF based practical tools and international standards such as the ICF Core Sets. Finally it illustrates how to map the world of measures to the ICF and vice versa and the methodological principles relevant for the transformation of information obtained with a clinical test or a patient-oriented instrument to the ICF as well as the development of ICF-based clinical and self-reported measurement instruments.

The Performance of LBP and NSVC Combination Applied to Face Classification

Directory of Open Access Journals (Sweden)

Mohammed Ngadi

2016-01-01

Full Text Available The growing demand in the field of security led to the development of interesting approaches in face classification. These works are interested since their beginning in extracting the invariant features of the face to build a single model easily identifiable by classification algorithms. Our goal in this article is to develop more efficient practical methods for face detection. We present a new fast and accurate approach based on local binary patterns (LBP for the extraction of the features that is combined with the new classifier Neighboring Support Vector Classifier (NSVC for classification. The experimental results on different natural images show that the proposed method can get very good results at a very short detection time. The best precision obtained by LBP-NSVC exceeds 99%.

Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

Science.gov (United States)

Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

2017-06-01

During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

Village Building Identification Based on Ensemble Convolutional Neural Networks

Science.gov (United States)

Guo, Zhiling; Chen, Qi; Xu, Yongwei; Shibasaki, Ryosuke; Shao, Xiaowei

2017-01-01

In this study, we present the Ensemble Convolutional Neural Network (ECNN), an elaborate CNN frame formulated based on ensembling state-of-the-art CNN models, to identify village buildings from open high-resolution remote sensing (HRRS) images. First, to optimize and mine the capability of CNN for village mapping and to ensure compatibility with our classification targets, a few state-of-the-art models were carefully optimized and enhanced based on a series of rigorous analyses and evaluations. Second, rather than directly implementing building identification by using these models, we exploited most of their advantages by ensembling their feature extractor parts into a stronger model called ECNN based on the multiscale feature learning method. Finally, the generated ECNN was applied to a pixel-level classification frame to implement object identification. The proposed method can serve as a viable tool for village building identification with high accuracy and efficiency. The experimental results obtained from the test area in Savannakhet province, Laos, prove that the proposed ECNN model significantly outperforms existing methods, improving overall accuracy from 96.64% to 99.26%, and kappa from 0.57 to 0.86. PMID:29084154

CLASSIFICATION OF LIDAR DATA OVER BUILDING ROOFS USING K-MEANS AND PRINCIPAL COMPONENT ANALYSIS

Directory of Open Access Journals (Sweden)

Renato César dos Santos

Full Text Available Abstract: The classification is an important step in the extraction of geometric primitives from LiDAR data. Normally, it is applied for the identification of points sampled on geometric primitives of interest. In the literature there are several studies that have explored the use of eigenvalues to classify LiDAR points into different classes or structures, such as corner, edge, and plane. However, in some works the classes are defined considering an ideal geometry, which can be affected by the inadequate sampling and/or by the presence of noise when using real data. To overcome this limitation, in this paper is proposed the use of metrics based on eigenvalues and the k-means method to carry out the classification. So, the concept of principal component analysis is used to obtain the eigenvalues and the derived metrics, while the k-means is applied to cluster the roof points in two classes: edge and non-edge. To evaluate the proposed method four test areas with different levels of complexity were selected. From the qualitative and quantitative analyses, it could be concluded that the proposed classification procedure gave satisfactory results, resulting in completeness and correctness above 92% for the non-edge class, and between 61% to 98% for the edge class.

Feature selection gait-based gender classification under different circumstances

Science.gov (United States)

Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

2014-05-01

This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

Science.gov (United States)

Liu, Da; Li, Jianxun

2016-12-16

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

Approaches to Substance of Social Infrastructure and to Its Classification

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Kyrychenko Sergiy О. –

2016-03-01

Full Text Available The article is concerned with studying and analyzing approaches to both substance and classification of social infrastructure objects as a specific constellation of subsystems and components. To address the purpose set, the following tasks have been formulated: analysis of existing methods for determining the classification of social infrastructure; classification of the branches of social infrastructure using functional-dedicated approach; formulation of author's own definition of substance of social infrastructure. It has been determined that to date most often a social infrastructure classification is carried out depending on its functional tasks, although there are other approaches to classification. The author's definition of substance of social infrastructure has been formulated as follows: social infrastructure is a body of economy branches (public utilities, management, public safety and environment, socio-economic services, the purpose of which is to impact on reproductive potential and overall conditions of human activity in the spheres of work, everyday living, family, social-political, spiritual and intellectual development as well as life activity.

Classification Accuracy Increase Using Multisensor Data Fusion

Science.gov (United States)

Makarau, A.; Palubinskas, G.; Reinartz, P.

2011-09-01

other established methods illustrates the advantage in the classification accuracy for many classes such as buildings, low vegetation, sport objects, forest, roads, rail roads, etc.

Usability of Clay Mixed Red Mud as Building Material in Transdanubian (Hungary) Region

International Nuclear Information System (INIS)

Sas, Z.; Somlai, J.J.; Szeiler, G.; Kovacs, T.

2014-01-01

The most commonly used building materials in Hungary and in numerous country of the world are the bricks, which made from clays. Due to the congenial internal structure properties of the clays these raw materials can be mixed with other materials, provides great possibility to reuse industrial by-products as additive material. The production and inbuilt of new types of synthetic building materials based on NORM (naturally occurring radioactive materials) by-products is raising concerns among authorities, public and scientists. Several NORM residues produced in large quantity, such as: phospogypsum (phosphate industry), red mud (aluminium processing industry), fly ash, coal slag (coal burning and steelworks) and so on are presently under investigation. The aluminum manufacturing in Ajka (Hungary) started in 1943. As a result of the bauxite refining activities up to now approximately 30 Mt of red mud has been produced in Hungary, stored in reservoirs. The radionuclide content of the bauxite usually exceeds the world average in soils (WA), which entirely remains in the by-product during Bayer process. The exposure pathways in case of application of NORM residues have to be explored in order to reveal the potential risks of NORMs on residents. The gamma radiation originated from the primordial radionuclides (K-40; U-238; Th-232) and their daughter elements found in nature and in building materials as well increase the external dose of the human body. In the EU the Radiation Protection 112 (RP 112) guideline serves for classification of building material, wherein the gamma exposure is limited by I-index

Charakterystyka budowy ciała tancerzy stylu standardowego tańca sportowego na przykładzie pary mistrzów świata = Characteristics of body building standard style dancers on the example of pair of world champions

Directory of Open Access Journals (Sweden)

Wiesława Pilewska

2015-11-01

Abstract Aim of the study The aim of the study was to determine the specificity of somatic build ballroom dancers sporting standard style. Materials The research material was sporting ballroom dancing couple having the highest international dance class "S". World Champions of 2013, the standard style. The length of the internship dance couples was 19 years. Subjects were trained from 6 to 7 days a week, after 3-4 hours a day. They were both 28 years. Methods Physical development assessment was based on anthropometric measurements of body weight and height, the length of the neck, upper and lower limbs, torso, thigh and lower leg, foot length, width, shoulders, pelvis, feet, chest, deep chest, circuits, waist, hips, thighs and ankles. Typological classification was also used to assess the specificity of physique subjects. Conclusions A pair of dance sport sporty style with a high level of standard sports (with the 2013 World Champions. characterized by a specific construction of somatic manifested a certain size characteristics and indicators of body (shown in this work.Presented by their size parameters of somatic and morphological indicators should be considered as a result of the impact of dance training and the requirements of the standard style of discipline and separately for dancers and dance together for a couple as the specifics of their selection.   Key words: ballroom dancing, standard style, construction somatic, World Champions.

[Severity classification of chronic obstructive pulmonary disease based on deep learning].

Science.gov (United States)

Ying, Jun; Yang, Ceyuan; Li, Quanzheng; Xue, Wanguo; Li, Tanshi; Cao, Wenzhe

2017-12-01

In this paper, a deep learning method has been raised to build an automatic classification algorithm of severity of chronic obstructive pulmonary disease. Large sample clinical data as input feature were analyzed for their weights in classification. Through feature selection, model training, parameter optimization and model testing, a classification prediction model based on deep belief network was built to predict severity classification criteria raised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We get accuracy over 90% in prediction for two different standardized versions of severity criteria raised in 2007 and 2011 respectively. Moreover, we also got the contribution ranking of different input features through analyzing the model coefficient matrix and confirmed that there was a certain degree of agreement between the more contributive input features and the clinical diagnostic knowledge. The validity of the deep belief network model was proved by this result. This study provides an effective solution for the application of deep learning method in automatic diagnostic decision making.

CERN building numbers: no rhyme and little reason

CERN Multimedia

Katarina Anthony

2012-01-01

Over the years, people at CERN have been trying to develop a single theory to explain CERN’s building numbers. Behind these seemingly random numbers there must surely be an ultimate solution: CERN’s second Standard Model, if you will. The CERN Bulletin finds out more…   Still trying to understand CERN's building numbers? Give up... There’s no denying it: the CERN site cannot be navigated without professional help. You can walk down a single corridor and pass through Buildings 33, 4, 5 and 53… in that order. Surely there must be a method behind this madness? “Well, if there is one, we’ve yet to find it,” says Youri Robert, who is in charge of geographic information and patrimony data in the GS Department’s Site Engineering group, which is responsible for the classification of CERN’s buildings. “We do have some naming conventions in place, especially for buildings related to...

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

Directory of Open Access Journals (Sweden)

Tong Liu

2017-12-01

Full Text Available This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF links for path-dependent walker classification. The fluctuated received signal strength (RSS sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ and hidden Markov models (HMMs are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS and non-line-of-sight (NLOS scenarios are conducted to validate the proposed method.

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links.

Science.gov (United States)

Liu, Tong; Liang, Zhuo-Qian

2017-12-05

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method.

Lightweight Biometric Sensing for Walker Classification Using Narrowband RF Links

Science.gov (United States)

Liang, Zhuo-qian

2017-01-01

This article proposes a lightweight biometric sensing system using ubiquitous narrowband radio frequency (RF) links for path-dependent walker classification. The fluctuated received signal strength (RSS) sequence generated by human motion is used for feature representation. To capture the most discriminative characteristics of individuals, a three-layer RF sensing network is organized for building multiple sampling links at the most common heights of upper limbs, thighs, and lower legs. The optimal parameters of sensing configuration, such as the height of link location and number of fused links, are investigated to improve sensory data distinctions among subjects, and the experimental results suggest that the synergistic sensing by using multiple links can contribute a better performance. This is the new consideration of using RF links in building a biometric sensing system. In addition, two types of classification methods involving vector quantization (VQ) and hidden Markov models (HMMs) are developed and compared for closed-set walker recognition and verification. Experimental studies in indoor line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios are conducted to validate the proposed method. PMID:29206188

The status quo of green-building education in South Africa

African Journals Online (AJOL)

2015-10-30

Oct 30, 2015 ... on projects in the property-development industry. The purpose of this study ... adequate technical understanding of sustainable building methods. ... skills in green building as promptly as role players in the green-building sector might .... The body of knowledge about sustainability and green buildings is ...

Image Classification Workflow Using Machine Learning Methods

Science.gov (United States)

Christoffersen, M. S.; Roser, M.; Valadez-Vergara, R.; Fernández-Vega, J. A.; Pierce, S. A.; Arora, R.

2016-12-01

Recent increases in the availability and quality of remote sensing datasets have fueled an increasing number of scientifically significant discoveries based on land use classification and land use change analysis. However, much of the software made to work with remote sensing data products, specifically multispectral images, is commercial and often prohibitively expensive. The free to use solutions that are currently available come bundled up as small parts of much larger programs that are very susceptible to bugs and difficult to install and configure. What is needed is a compact, easy to use set of tools to perform land use analysis on multispectral images. To address this need, we have developed software using the Python programming language with the sole function of land use classification and land use change analysis. We chose Python to develop our software because it is relatively readable, has a large body of relevant third party libraries such as GDAL and Spectral Python, and is free to install and use on Windows, Linux, and Macintosh operating systems. In order to test our classification software, we performed a K-means unsupervised classification, Gaussian Maximum Likelihood supervised classification, and a Mahalanobis Distance based supervised classification. The images used for testing were three Landsat rasters of Austin, Texas with a spatial resolution of 60 meters for the years of 1984 and 1999, and 30 meters for the year 2015. The testing dataset was easily downloaded using the Earth Explorer application produced by the USGS. The software should be able to perform classification based on any set of multispectral rasters with little to no modification. Our software makes the ease of land use classification using commercial software available without an expensive license.

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....

Automated recognition system for ELM classification in JET

International Nuclear Information System (INIS)

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

2009-01-01

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

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

Science.gov (United States)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

Multispectral LiDAR Data for Land Cover Classification of Urban Areas

Directory of Open Access Journals (Sweden)

Salem Morsy

2017-04-01

Full Text Available Airborne Light Detection And Ranging (LiDAR systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

Multispectral LiDAR Data for Land Cover Classification of Urban Areas.

Science.gov (United States)

Morsy, Salem; Shaker, Ahmed; El-Rabbany, Ahmed

2017-04-26

Airborne Light Detection And Ranging (LiDAR) systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity) from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs) computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

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

Teaching practices epistemologically differentiated about human body learning

Directory of Open Access Journals (Sweden)

Rosália Maria Ribeiro de Aragão

2011-12-01

Full Text Available How could we teach about THE HUMAN BODY as a different way, in both epistemological and pedagogical approaches? How could we leave behind stagnant as well as stagnating aspects of traditional way of teaching, such as the fragmentation/segmentation of contents, the far away reality, the excessive use of details or else, whenever learning about our own body? These are some of the questions we have considered when trying to escape the bad influence which came from our "environment formation" - putting it on all the marks we have acquired inside or even outside school - trying to overview as meaning our body working...in constant interaction with the surrounding ambient. Among those pointed kind of formation marks we frequently acquire from studying at the University - which need to be transcended —here we come to detach those innumerable contacts with both anatomized and misfigurated supposed human bodies' which didn't even look like actual human bodies, because they could never seem to have sheltered life inside themselves. They were inert as well as static bodies, only used as a such of vain "didactic materials" that could/can permit many teachers on their educational formation to focus a certain teaching approach which only seeks both the students' memorization of an infinitude of "complicated words", and to structure the systems -by several procedures of nouns definition and/or classification - as part of the so called biological organism. In order to do a different way of teaching, we have based our approach on three alternative teaching methodologies which focus these matters under a constructive perspective. On those three focused studies, it is possible to observe that some very principles of a present day teaching approach were there considered to achieve some of them: the respect for the students' previous ideas; the understanding about knowledge as something that is not established for good but as ever changeable and, at last, the

An Algorithm of Building Extraction in Urban Area Based on Improved Top-hat Transformations and LBP Elevation Texture

Directory of Open Access Journals (Sweden)

HE Manyun

2017-09-01

Full Text Available Classification of building and vegetation is difficult solely by LiDAR data and vegetation in shadows can't be eliminated only by aerial images. The improved top-hat transformations and local binary patterns (LBP elevation texture analysis for building extraction are proposed based on the fusion of aerial images and LiDAR data. Firstly, LiDAR data is reorganized into grid cell, the algorithm removes ground points through top-hat transform. Then, the vegetation points are extracted by normalized difference vegetation index (NDVI. Thirdly, according to the elevation information of LiDAR points, LBP elevation texture is calculated and achieving precise elimination of vegetation in shadows or surrounding to the buildings. At last, morphological operations are used to fill the holes of building roofs, and region growing for complete building edges. The simulation is based on the complex urban area in Vaihingen benchmark provided by ISPRS, the results show that the algorithm affording higher classification accuracy.

Classification of jet fuel properties by near-infrared spectroscopy using fuzzy rule-building expert systems and support vector machines.

Science.gov (United States)

Xu, Zhanfeng; Bunker, Christopher E; Harrington, Peter de B

2010-11-01

Monitoring the changes of jet fuel physical properties is important because fuel used in high-performance aircraft must meet rigorous specifications. Near-infrared (NIR) spectroscopy is a fast method to characterize fuels. Because of the complexity of NIR spectral data, chemometric techniques are used to extract relevant information from spectral data to accurately classify physical properties of complex fuel samples. In this work, discrimination of fuel types and classification of flash point, freezing point, boiling point (10%, v/v), boiling point (50%, v/v), and boiling point (90%, v/v) of jet fuels (JP-5, JP-8, Jet A, and Jet A1) were investigated. Each physical property was divided into three classes, low, medium, and high ranges, using two evaluations with different class boundary definitions. The class boundaries function as the threshold to alarm when the fuel properties change. Optimal partial least squares discriminant analysis (oPLS-DA), fuzzy rule-building expert system (FuRES), and support vector machines (SVM) were used to build the calibration models between the NIR spectra and classes of physical property of jet fuels. OPLS-DA, FuRES, and SVM were compared with respect to prediction accuracy. The validation of the calibration model was conducted by applying bootstrap Latin partition (BLP), which gives a measure of precision. Prediction accuracy of 97 ± 2% of the flash point, 94 ± 2% of freezing point, 99 ± 1% of the boiling point (10%, v/v), 98 ± 2% of the boiling point (50%, v/v), and 96 ± 1% of the boiling point (90%, v/v) were obtained by FuRES in one boundaries definition. Both FuRES and SVM obtained statistically better prediction accuracy over those obtained by oPLS-DA. The results indicate that combined with chemometric classifiers NIR spectroscopy could be a fast method to monitor the changes of jet fuel physical properties.

Buildings and Health. Educational campaign for healthy buildings. Educational material

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-12-31

In recent years health and comfort problems associated with the indoor climate have come to constitute a problem in Sweden. To come to grips with this a nationwide educational campaign on Buildings and Health is being run. It is directed to those involved in planning, project design, construction and management of buildings. The objective is to convey a body of knowledge to the many occupational and professional groups in the construction sector on how to avoid indoor climate problems in homes, schools, offices and other workplaces. The campaign is being run by the Swedish National Board of Housing and Planning and the Swedish Council for Building Research, in co-operation with various organizations and companies in the construction industry, and with municipalities and authorities. The knowledge which is being disseminated through the campaign is summarized in this compendium. figs., tabs.

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

Science.gov (United States)

Shamim, Thorakkal

2014-01-01

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

Towards Automatic Classification of Exoplanet-Transit-Like Signals: A Case Study on Kepler Mission Data

Science.gov (United States)

Valizadegan, Hamed; Martin, Rodney; McCauliff, Sean D.; Jenkins, Jon Michael; Catanzarite, Joseph; Oza, Nikunj C.

2015-08-01

Building new catalogues of planetary candidates, astrophysical false alarms, and non-transiting phenomena is a challenging task that currently requires a reviewing team of astrophysicists and astronomers. These scientists need to examine more than 100 diagnostic metrics and associated graphics for each candidate exoplanet-transit-like signal to classify it into one of the three classes. Considering that the NASA Explorer Program's TESS mission and ESA's PLATO mission survey even a larger area of space, the classification of their transit-like signals is more time-consuming for human agents and a bottleneck to successfully construct the new catalogues in a timely manner. This encourages building automatic classification tools that can quickly and reliably classify the new signal data from these missions. The standard tool for building automatic classification systems is the supervised machine learning that requires a large set of highly accurate labeled examples in order to build an effective classifier. This requirement cannot be easily met for classifying transit-like signals because not only are existing labeled signals very limited, but also the current labels may not be reliable (because the labeling process is a subjective task). Our experiments with using different supervised classifiers to categorize transit-like signals verifies that the labeled signals are not rich enough to provide the classifier with enough power to generalize well beyond the observed cases (e.g. to unseen or test signals). That motivated us to utilize a new category of learning techniques, so-called semi-supervised learning, that combines the label information from the costly labeled signals, and distribution information from the cheaply available unlabeled signals in order to construct more effective classifiers. Our study on the Kepler Mission data shows that semi-supervised learning can significantly improve the result of multiple base classifiers (e.g. Support Vector Machines, Ada

Application of In-Segment Multiple Sampling in Object-Based Classification

Directory of Open Access Journals (Sweden)

Nataša Đurić

2014-12-01

Full Text Available When object-based analysis is applied to very high-resolution imagery, pixels within the segments reveal large spectral inhomogeneity; their distribution can be considered complex rather than normal. When normality is violated, the classification methods that rely on the assumption of normally distributed data are not as successful or accurate. It is hard to detect normality violations in small samples. The segmentation process produces segments that vary highly in size; samples can be very big or very small. This paper investigates whether the complexity within the segment can be addressed using multiple random sampling of segment pixels and multiple calculations of similarity measures. In order to analyze the effect sampling has on classification results, statistics and probability value equations of non-parametric two-sample Kolmogorov-Smirnov test and parametric Student’s t-test are selected as similarity measures in the classification process. The performance of both classifiers was assessed on a WorldView-2 image for four land cover classes (roads, buildings, grass and trees and compared to two commonly used object-based classifiers—k-Nearest Neighbor (k-NN and Support Vector Machine (SVM. Both proposed classifiers showed a slight improvement in the overall classification accuracies and produced more accurate classification maps when compared to the ground truth image.

Standardizing foot-type classification using arch index values.

Science.gov (United States)

Wong, Christopher Kevin; Weil, Rich; de Boer, Emily

2012-01-01

The lack of a reliable classification standard for foot type makes drawing conclusions from existing research and clinical decisions difficult, since different foot types may move and respond to treatment differently. The purpose of this study was to determine interrater agreement for foot-type classification based on photo-box-derived arch index values. For this correlational study with two raters, a sample of 11 healthy volunteers with normal to obese body mass indices was recruited from both a community weight-loss programme and a programme in physical therapy. Arch index was calculated using AutoCAD software from footprint photographs obtained via mirrored photo-box. Classification as high-arched, normal, or low-arched foot type was based on arch index values. Reliability of the arch index was determined with intra-class correlations; agreement on foot-type classification was determined using quadratic weighted kappa (κw). Average arch index was 0.215 for one tester and 0.219 for the second tester, with an overall range of 0.017 to 0.370. Both testers classified 6 feet as low-arched, 9 feet as normal, and 7 feet as high-arched. Interrater reliability for the arch index was ICC=0.90; interrater agreement for foot-type classification was κw=0.923. Classification of foot type based on arch index values derived from plantar footprint photographs obtained via mirrored photo-box showed excellent reliability in people with varying BMI. Foot-type classification may help clinicians and researchers subdivide sample populations to better differentiate mobility, gait, or treatment effects among foot types.

Standardizing Foot-Type Classification Using Arch Index Values

Science.gov (United States)

Weil, Rich; de Boer, Emily

2012-01-01

ABSTRACT Purpose: The lack of a reliable classification standard for foot type makes drawing conclusions from existing research and clinical decisions difficult, since different foot types may move and respond to treatment differently. The purpose of this study was to determine interrater agreement for foot-type classification based on photo-box-derived arch index values. Method: For this correlational study with two raters, a sample of 11 healthy volunteers with normal to obese body mass indices was recruited from both a community weight-loss programme and a programme in physical therapy. Arch index was calculated using AutoCAD software from footprint photographs obtained via mirrored photo-box. Classification as high-arched, normal, or low-arched foot type was based on arch index values. Reliability of the arch index was determined with intra-class correlations; agreement on foot-type classification was determined using quadratic weighted kappa (κw). Results: Average arch index was 0.215 for one tester and 0.219 for the second tester, with an overall range of 0.017 to 0.370. Both testers classified 6 feet as low-arched, 9 feet as normal, and 7 feet as high-arched. Interrater reliability for the arch index was ICC=0.90; interrater agreement for foot-type classification was κw=0.923. Conclusions: Classification of foot type based on arch index values derived from plantar footprint photographs obtained via mirrored photo-box showed excellent reliability in people with varying BMI. Foot-type classification may help clinicians and researchers subdivide sample populations to better differentiate mobility, gait, or treatment effects among foot types. PMID:23729964

Simultaneous Co-Clustering and Classification in Customers Insight

Science.gov (United States)

Anggistia, M.; Saefuddin, A.; Sartono, B.

2017-04-01

Building predictive model based on the heterogeneous dataset may yield many problems, such as less precise in parameter and prediction accuracy. Such problem can be solved by segmenting the data into relatively homogeneous groups and then build a predictive model for each cluster. The advantage of using this strategy usually gives result in simpler models, more interpretable, and more actionable without any loss in accuracy and reliability. This work concerns on marketing data set which recorded a customer behaviour across products. There are some variables describing customer and product as attributes. The basic idea of this approach is to combine co-clustering and classification simultaneously. The objective of this research is to analyse the customer across product characteristics, so the marketing strategy implemented precisely.

Lean waste classification model to support the sustainable operational practice

Science.gov (United States)

Sutrisno, A.; Vanany, I.; Gunawan, I.; Asjad, M.

2018-04-01

Driven by growing pressure for a more sustainable operational practice, improvement on the classification of non-value added (waste) is one of the prerequisites to realize sustainability of a firm. While the use of the 7 (seven) types of the Ohno model now becoming a versatile tool to reveal the lean waste occurrence. In many recent investigations, the use of the Seven Waste model of Ohno is insufficient to cope with the types of waste occurred in industrial practices at various application levels. Intended to a narrowing down this limitation, this paper presented an improved waste classification model based on survey to recent studies discussing on waste at various operational stages. Implications on the waste classification model to the body of knowledge and industrial practices are provided.

Using intelligent clustering techniques to classify the energy performance of school buildings

Energy Technology Data Exchange (ETDEWEB)

Santamouris, M.; Sfakianaki, K.; Papaglastra, M.; Pavlou, C.; Doukas, P.; Geros, V.; Assimakopoulos, M.N.; Zerefos, S. [University of Athens, Department of Physics, Division of Applied Physics, Laboratory of Meteorology, Athens (Greece); Mihalakakou, G.; Gaitani, N. [University of Ioannina, Department of Environmental and Natural Resources Management, Agrinio (Greece); Patargias, P. [University of Peloponnesus, Faculty of Human Sciences and Cultural Studies, Department of History, Kalamata (Greece); Primikiri, E. [University of Patras, Department of Architecture, Patras (Greece); Mitoula, R. [Charokopion University of Athens, Athens (Greece)

2007-07-01

The present paper deals with the energy performance, energy classification and rating and the global environmental quality of school buildings. A new energy classification technique based on intelligent clustering methodologies is proposed. Energy rating of school buildings provides specific information on their energy consumption and efficiency relative to the other buildings of similar nature and permits a better planning of interventions to improve its energy performance. The overall work reported in the present paper, is carried out in three phases. During the first phase energy consumption data have been collected through energy surveys performed in 320 schools in Greece. In the second phase an innovative energy rating scheme based on fuzzy clustering techniques has been developed, while in the third phase, 10 schools have been selected and detailed measurements of their energy efficiency and performance as well as of the global environmental quality have been performed using a specific experimental protocol. The proposed energy rating method has been applied while the main environmental and energy problems have been identified. The potential for energy and environmental improvements has been assessed. (author)

Vibration-damping structure for reactor building

International Nuclear Information System (INIS)

Kuno, Toshio; Iba, Chikara; Tanaka, Hideki; Kageyama, Mitsuru

1998-01-01

In a damping structure of a reactor building, an inner concrete body and a reactor container are connected by way of a vibration absorbing member. As the vibration absorbing member, springs or dampers are used. The inner concrete body and the reactor container each having weight and inherent frequency different from each other are opposed displaceably by way of the vibration absorbing member thereby enabling to reduce seismic input and reduce shearing force at least at leg portions. Accordingly, seismic loads are reduced to increase the grounding rate of the base thereby enabling to satisfy an allowable value. Therefore, it is not necessary to strengthen the inner concrete body and the reactor container excessively, the amount of reinforcing rods can be reduced, and the amount of a portion of the base buried to the ground can be reduced thereby enabling to constitute the reactor building easily. (N.H.)

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.

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.

Quantifying physical characteristics of wildland fuels using the fuel characteristic classification system.

Science.gov (United States)

Cynthia L. Riccardi; Susan J. Prichard; David V. Sandberg; Roger D. Ottmar

2007-01-01

Wildland fuel characteristics are used in many applications of operational fire predictions and to understand fire effects and behaviour. Even so, there is a shortage of information on basic fuel properties and the physical characteristics of wildland fuels. The Fuel Characteristic Classification System (FCCS) builds and catalogues fuelbed descriptions based on...

Hardware Accelerators Targeting a Novel Group Based Packet Classification Algorithm

Directory of Open Access Journals (Sweden)

O. Ahmed

2013-01-01

Full Text Available Packet classification is a ubiquitous and key building block for many critical network devices. However, it remains as one of the main bottlenecks faced when designing fast network devices. In this paper, we propose a novel Group Based Search packet classification Algorithm (GBSA that is scalable, fast, and efficient. GBSA consumes an average of 0.4 megabytes of memory for a 10 k rule set. The worst-case classification time per packet is 2 microseconds, and the preprocessing speed is 3 M rules/second based on an Xeon processor operating at 3.4 GHz. When compared with other state-of-the-art classification techniques, the results showed that GBSA outperforms the competition with respect to speed, memory usage, and processing time. Moreover, GBSA is amenable to implementation in hardware. Three different hardware implementations are also presented in this paper including an Application Specific Instruction Set Processor (ASIP implementation and two pure Register-Transfer Level (RTL implementations based on Impulse-C and Handel-C flows, respectively. Speedups achieved with these hardware accelerators ranged from 9x to 18x compared with a pure software implementation running on an Xeon processor.

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.

“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.

[Nosological classification and assessment of muscle dysmorphia].

Science.gov (United States)

Babusa, Bernadett; Túry, Ferenc

2011-01-01

Muscle dysmorphia is a recently described psychiatric disorder, characterized by a pathological preoccupation with muscle size. In spite of their huge muscles, muscle dysmorphia sufferers believe that they are insufficiently large and muscular therefore would like to be bigger and more muscular. Male bodybuilders are at high-risk for the disorder. The nosological classification of muscle dysmorphia has been changed over the years. However, consensus has not emerged so far. Most of the ongoing debate has conceptualized muscle dysmorphia as an eating disorder, obsessive-compulsive disorder and body dysmorphic disorder. There are a number of arguments for and againts. In the present study the authors do not take a position on the diagnostic classification of muscle dysmorphia. The purpose of the study is to review the present approaches relating to the diagnostic classification of muscle dysmporphia. Many different questionnaires were developed for the assessment of muscle dysmorphia. Currently, there is a lack of assessment methods measuring muscle dysmorphia symptoms in Hungary. As a secondary purpose the study also presents the Hungarian version of the Muscle Appearance Satisfaction Scale (Mayville et al., 2002).

Building Extraction in Very High Resolution Remote Sensing Imagery Using Deep Learning and Guided Filters

Directory of Open Access Journals (Sweden)

Yongyang Xu

2018-01-01

Full Text Available Very high resolution (VHR remote sensing imagery has been used for land cover classification, and it tends to a transition from land-use classification to pixel-level semantic segmentation. Inspired by the recent success of deep learning and the filter method in computer vision, this work provides a segmentation model, which designs an image segmentation neural network based on the deep residual networks and uses a guided filter to extract buildings in remote sensing imagery. Our method includes the following steps: first, the VHR remote sensing imagery is preprocessed and some hand-crafted features are calculated. Second, a designed deep network architecture is trained with the urban district remote sensing image to extract buildings at the pixel level. Third, a guided filter is employed to optimize the classification map produced by deep learning; at the same time, some salt-and-pepper noise is removed. Experimental results based on the Vaihingen and Potsdam datasets demonstrate that our method, which benefits from neural networks and guided filtering, achieves a higher overall accuracy when compared with other machine learning and deep learning methods. The method proposed shows outstanding performance in terms of the building extraction from diversified objects in the urban district.

Detection and Classification of Changes in Buildings from Airborne Laser Scanning Data

Directory of Open Access Journals (Sweden)

Sudan Xu

2015-12-01

Full Text Available The difficulty associated with the Lidar data change detection method is lack of data, which is mainly caused by occlusion or pulse absorption by the surface material, e.g., water. To address this challenge, we present a new strategy for detecting buildings that are “changed”, “unchanged”, or “unknown”, and quantifying the changes. The designation “unknown” is applied to locations where, due to lack of data in at least one of the epochs, it is not possible to reliably detect changes in the structure. The process starts with classified data sets in which buildings are extracted. Next, a point-to-plane surface difference map is generated by merging and comparing the two data sets. Context rules are applied to the difference map to distinguish between “changed”, “unchanged”, and “unknown”. Rules are defined to solve problems caused by the lack of data. Further, points labelled as “changed” are re-classified into changes to roofs, walls, dormers, cars, constructions above the roof line, and undefined objects. Next, all the classified changes are organized as changed building objects, and the geometric indices are calculated from their 3D minimum bounding boxes. Performance analysis showed that 80%–90% of real changes are found, of which approximately 50% are considered relevant.

PRTR/309 building nuclear facility preliminary

International Nuclear Information System (INIS)

Cornwell, B.C.

1994-01-01

The hazard classification of the Plutonium Recycle Test Reactor (PRTR)/309 building as a ''Radiological Facility'' and the office portions as ''Other Industrial Facility'' are documented by this report. This report provides: a synopsis of the history and facility it's uses; describes major area of the facility; and assesses the radiological conditions for the facility segments. The assessment is conducted using the hazard category threshold values, segmentation methodology, and graded approach guidance of DOE-STD-1027-92

Accelerometer-based on-body sensor localization for health and medical monitoring applications

Science.gov (United States)

Vahdatpour, Alireza; Amini, Navid; Xu, Wenyao; Sarrafzadeh, Majid

2011-01-01

In this paper, we present a technique to recognize the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the user’s body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89% accuracy in estimating the location of devices on the body. In order to study the feasibility of classification of left limbs from right limbs (e.g., left arm vs. right arm), we performed analysis, based of which no meaningful classification was observed. Personalized ultraviolet monitoring and wireless transmission power control comprise two immediate applications of our on-body device localization approach. Such applications, along with their corresponding feasibility studies, are discussed. PMID:22347840

Information support of monitoring of technical condition of buildings in construction risk area

Science.gov (United States)

Skachkova, M. E.; Lepihina, O. Y.; Ignatova, V. V.

2018-05-01

The paper presents the results of the research devoted to the development of a model of information support of monitoring buildings technical condition; these buildings are located in the construction risk area. As a result of the visual and instrumental survey, as well as the analysis of existing approaches and techniques, attributive and cartographic databases have been created. These databases allow monitoring defects and damages of buildings located in a 30-meter risk area from the object under construction. The classification of structures and defects of these buildings under survey is presented. The functional capabilities of the developed model and the field of it practical applications are determined.

Reverberation time in class rooms – Comparison of regulations and classification criteria in the Nordic countries

DEFF Research Database (Denmark)

Rasmussen, Birgit; Brunskog, Jonas; Hoffmeyer, Dan

2012-01-01

Regulatory requirements or guidelines for classroom reverberation time exist in all five Nordic countries and in most of Europe – as well as other acoustic criteria for schools, e.g. concerning airborne and impact sound insulation, facade sound insulation and installation noise. There are several...... reasons for having such requirements: Improving learning efficiency for pupils and work conditions for teachers and reducing noise levels, thus increasing comfort for everyone. Instead of including acoustic regulatory requirements for schools directly in the building regulations, Iceland, Norway...... and Sweden have introduced acoustic quality classes A, B, C and D in national standards with class C referred to as regulatory requirements. These national classification standards are dealing with acoustic classes for several types of buildings. A classification scheme also exists in Finland...

New decision support tool for acute lymphoblastic leukemia classification

Science.gov (United States)

Madhukar, Monica; Agaian, Sos; Chronopoulos, Anthony T.

2012-03-01

In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL. The developed system includes different methods to accurately measure furthermore cell properties in microscope blood film images. The blood images are exposed to series of pre-processing steps which include color correlation, and contrast enhancement. By performing K-means clustering on the resultant images, the nuclei of the cells under consideration are obtained. Shape features and texture features are then extracted for classification. The system is further tested on the classification of spectra measured from the cell nuclei in blood samples in order to distinguish normal cells from those affected by Acute Lymphoblastic Leukemia. The results show that the proposed system robustly segments and classifies acute lymphoblastic leukemia based on complete microscopic blood images.

Acute leukemia classification by ensemble particle swarm model selection.

Science.gov (United States)

Escalante, Hugo Jair; Montes-y-Gómez, Manuel; González, Jesús A; Gómez-Gil, Pilar; Altamirano, Leopoldo; Reyes, Carlos A; Reta, Carolina; Rosales, Alejandro

2012-07-01

Acute leukemia is a malignant disease that affects a large proportion of the world population. Different types and subtypes of acute leukemia require different treatments. In order to assign the correct treatment, a physician must identify the leukemia type or subtype. Advanced and precise methods are available for identifying leukemia types, but they are very expensive and not available in most hospitals in developing countries. Thus, alternative methods have been proposed. An option explored in this paper is based on the morphological properties of bone marrow images, where features are extracted from medical images and standard machine learning techniques are used to build leukemia type classifiers. This paper studies the use of ensemble particle swarm model selection (EPSMS), which is an automated tool for the selection of classification models, in the context of acute leukemia classification. EPSMS is the application of particle swarm optimization to the exploration of the search space of ensembles that can be formed by heterogeneous classification models in a machine learning toolbox. EPSMS does not require prior domain knowledge and it is able to select highly accurate classification models without user intervention. Furthermore, specific models can be used for different classification tasks. We report experimental results for acute leukemia classification with real data and show that EPSMS outperformed the best results obtained using manually designed classifiers with the same data. The highest performance using EPSMS was of 97.68% for two-type classification problems and of 94.21% for more than two types problems. To the best of our knowledge, these are the best results reported for this data set. Compared with previous studies, these improvements were consistent among different type/subtype classification tasks, different features extracted from images, and different feature extraction regions. The performance improvements were statistically significant

Site Classification using Multichannel Channel Analysis of Surface Wave (MASW) method on Soft and Hard Ground

Science.gov (United States)

Ashraf, M. A. M.; Kumar, N. S.; Yusoh, R.; Hazreek, Z. A. M.; Aziman, M.

2018-04-01

Site classification utilizing average shear wave velocity (Vs(30) up to 30 meters depth is a typical parameter. Numerous geophysical methods have been proposed for estimation of shear wave velocity by utilizing assortment of testing configuration, processing method, and inversion algorithm. Multichannel Analysis of Surface Wave (MASW) method is been rehearsed by numerous specialist and professional to geotechnical engineering for local site characterization and classification. This study aims to determine the site classification on soft and hard ground using MASW method. The subsurface classification was made utilizing National Earthquake Hazards Reduction Program (NERHP) and international Building Code (IBC) classification. Two sites are chosen to acquire the shear wave velocity which is in the state of Pulau Pinang for soft soil and Perlis for hard rock. Results recommend that MASW technique can be utilized to spatially calculate the distribution of shear wave velocity (Vs(30)) in soil and rock to characterize areas.

DATA CLASSIFICATION WITH NEURAL CLASSIFIER USING RADIAL BASIS FUNCTION WITH DATA REDUCTION USING HIERARCHICAL CLUSTERING

Directory of Open Access Journals (Sweden)

M. Safish Mary

2012-04-01

Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.

Managing Regulatory Body Competence

International Nuclear Information System (INIS)

2013-01-01

In 2001, the IAEA published TECDOC 1254, which examined the way in which the recognized functions of a regulatory body for nuclear facilities results in competence needs. Using the systematic approach to training (SAT), TECDOC 1254 provided a framework for regulatory bodies for managing training and developing and their maintaining their competence. It has been successfully used by many regulators. The IAEA has also introduced a methodology and an assessment tool - Guidelines for Systematic Assessment of Regulatory Competence Needs (SARCoN) - which provides practical guidance on analysing the training and development needs of a regulatory body and, through a gap analysis, guidance on establishing competence needs and how to meet them. In 2009, the IAEA established a steering committee (supported by a bureau) with the mission to advise the IAEA on how it could best assist Member States to develop suitable competence management systems for their regulatory bodies. The committee recommended the development of a safety report on managing staff competence as an integral part of a regulatory body's management system. This Safety Report was developed in response to this request. It supersedes TECDOC 1254, broadens its application to regulatory bodies for all facilities and activities, and builds upon the experience gained through the application of TECDOC 1254 and SARCoN and the feedback received from Member States. This Safety Report applies to the management of adequate competence as needs change, and as such is equally applicable to the needs of States 'embarking' on a nuclear power programme. It also deals with the special case of building up the competence of regulatory bodies as part of the overall process of establishing an 'embarking' State's regulatory system

Preliminary Hazard Classification of the 1714-N, Lead Storage

International Nuclear Information System (INIS)

Kerr, N. R.

1999-01-01

The 1714-N, -NA and -NB is a building segment that was deactivated under the N Area Deactivation Project. During the deactivation the building was designated as an area to store recycled or reused lead products. This document presents the Preliminary Hazard Classification (PHC) for the continued storage of lead products by Bechtel Hanford, Inc. (BHI). Two types of hazardous substances are the focus of this PHC: lead and residual radiological contamination. An evaluation contained in this PHC concludes that there is little risk from the remaining hazardous substances. It was further concluded that standard institutional controls that are implemented under the BHI contract provide adequate protection to people and the environment. No further safety analysis documentation is required for the continued lead storage

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.

Progressive Classification Using Support Vector Machines

Science.gov (United States)

Wagstaff, Kiri; Kocurek, Michael

2009-01-01

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user

Volumetric response classification in metastatic solid tumors on MSCT: Initial results in a whole-body setting

International Nuclear Information System (INIS)

Wulff, A.M.; Fabel, M.; Freitag-Wolf, S.; Tepper, M.; Knabe, H.M.; Schäfer, J.P.; Jansen, O.; Bolte, H.

2013-01-01

Purpose: To examine technical parameters of measurement accuracy and differences in tumor response classification using RECIST 1.1 and volumetric assessment in three common metastasis types (lung nodules, liver lesions, lymph node metastasis) simultaneously. Materials and methods: 56 consecutive patients (32 female) aged 41–82 years with a wide range of metastatic solid tumors were examined with MSCT for baseline and follow up. Images were evaluated by three experienced radiologists using manual measurements and semi-automatic lesion segmentation. Institutional ethics review was obtained and all patients gave written informed consent. Data analysis comprised interobserver variability operationalized as coefficient of variation and categorical response classification according to RECIST 1.1 for both manual and volumetric measures. Continuous data were assessed for statistical significance with Wilcoxon signed-rank test and categorical data with Fleiss kappa. Results: Interobserver variability was 6.3% (IQR 4.6%) for manual and 4.1% (IQR 4.4%) for volumetrically obtained sum of relevant diameters (p < 0.05, corrected). 4–8 patients’ response to therapy was classified differently across observers by using volumetry compared to standard manual measurements. Fleiss kappa revealed no significant difference in categorical agreement of response classification between manual (0.7558) and volumetric (0.7623) measurements. Conclusion: Under standard RECIST thresholds there was no advantage of volumetric compared to manual response evaluation. However volumetric assessment yielded significantly lower interobserver variability. This may allow narrower thresholds for volumetric response classification in the future

Volumetric response classification in metastatic solid tumors on MSCT: Initial results in a whole-body setting

Energy Technology Data Exchange (ETDEWEB)

Wulff, A.M., E-mail: a.wulff@rad.uni-kiel.de [Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel (Germany); Fabel, M. [Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel (Germany); Freitag-Wolf, S., E-mail: freitag@medinfo.uni-kiel.de [Institut für Medizinische Informatik und Statistik, Brunswiker Str. 10, 24105 Kiel (Germany); Tepper, M., E-mail: m.tepper@rad.uni-kiel.de [Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel (Germany); Knabe, H.M., E-mail: h.knabe@rad.uni-kiel.de [Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel (Germany); Schäfer, J.P., E-mail: jp.schaefer@rad.uni-kiel.de [Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel (Germany); Jansen, O., E-mail: o.jansen@neurorad.uni-kiel.de [Klinik für Diagnostische Radiologie, Arnold-Heller-Straße 3, Haus 23, 24105 Kiel (Germany); Bolte, H., E-mail: hendrik.bolte@ukmuenster.de [Klinik für Nuklearmedizin, Albert-Schweitzer-Campus 1, Gebäude A1, 48149 Münster (Germany)

2013-10-01

Purpose: To examine technical parameters of measurement accuracy and differences in tumor response classification using RECIST 1.1 and volumetric assessment in three common metastasis types (lung nodules, liver lesions, lymph node metastasis) simultaneously. Materials and methods: 56 consecutive patients (32 female) aged 41–82 years with a wide range of metastatic solid tumors were examined with MSCT for baseline and follow up. Images were evaluated by three experienced radiologists using manual measurements and semi-automatic lesion segmentation. Institutional ethics review was obtained and all patients gave written informed consent. Data analysis comprised interobserver variability operationalized as coefficient of variation and categorical response classification according to RECIST 1.1 for both manual and volumetric measures. Continuous data were assessed for statistical significance with Wilcoxon signed-rank test and categorical data with Fleiss kappa. Results: Interobserver variability was 6.3% (IQR 4.6%) for manual and 4.1% (IQR 4.4%) for volumetrically obtained sum of relevant diameters (p < 0.05, corrected). 4–8 patients’ response to therapy was classified differently across observers by using volumetry compared to standard manual measurements. Fleiss kappa revealed no significant difference in categorical agreement of response classification between manual (0.7558) and volumetric (0.7623) measurements. Conclusion: Under standard RECIST thresholds there was no advantage of volumetric compared to manual response evaluation. However volumetric assessment yielded significantly lower interobserver variability. This may allow narrower thresholds for volumetric response classification in the future.

A Classification Table for Achondrites

Science.gov (United States)

Chennaoui-Aoudjehane, H.; Larouci, N.; Jambon, A.; Mittlefehldt, D. W.

2014-01-01

Classifying chondrites is relatively easy and the criteria are well documented. It is based on mineral compositions, textural characteristics and more recently, magnetic susceptibility. It can be more difficult to classify achondrites, especially those that are very similar to terrestrial igneous rocks, because mineralogical, textural and compositional properties can be quite variable. Achondrites contain essentially olivine, pyroxenes, plagioclases, oxides, sulphides and accessory minerals. Their origin is attributed to differentiated parents bodies: large asteroids (Vesta); planets (Mars); a satellite (the Moon); and numerous asteroids of unknown size. In most cases, achondrites are not eye witnessed falls and some do not have fusion crust. Because of the mineralogical and magnetic susceptibility similarity with terrestrial igneous rocks for some achondrites, it can be difficult for classifiers to confirm their extra-terrestrial origin. We -as classifiers of meteorites- are confronted with this problem with every suspected achondrite we receive for identification. We are developing a "grid" of classification to provide an easier approach for initial classification. We use simple but reproducible criteria based on mineralogical, petrological and geochemical studies. We presented the classes: acapulcoites, lodranites, winonaites and Martian meteorites (shergottite, chassignites, nakhlites). In this work we are completing the classification table by including the groups: angrites, aubrites, brachinites, ureilites, HED (howardites, eucrites, and diogenites), lunar meteorites, pallasites and mesosiderites. Iron meteorites are not presented in this abstract.

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...

Application of partial least squares near-infrared spectral classification in diabetic identification

Science.gov (United States)

Yan, Wen-juan; Yang, Ming; He, Guo-quan; Qin, Lin; Li, Gang

2014-11-01

In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum - a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip's NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups - i.e. 53 samples as calibration set and 25 as prediction set - then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387.The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122.The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.

Polymyositis and dermatomyositis: Disease spectrum and classification

Directory of Open Access Journals (Sweden)

Siba P Raychaudhuri

2012-01-01

Full Text Available Muscle inflammation and weakness are the key features of idiopathic inflammatory myopathies (IIMs. In addition IIMs are frequently associated with cutaneous and pulmonary involvement. In clinical practice the three common inflammatory myopathies we come across are polymyositis (PM, dermatomyositis (DM and inclusion body myositis (IBM. The Bohan and Peter criteria combine clinical, laboratory, and pathologic features to define PM and DM. They did not recognize inclusion body myositis (IBM or other inflammatory myopathies, such as granulomatous and eosinophilic myositis. Thus the disease spectrum is wide and IIMs are a heterogeneous group of autoimmune disorders. To address these issues in this article we have discussed the currently developing newer classifications of IIMs.

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...

An enhanced topologically significant directed random walk in cancer classification using gene expression datasets

Directory of Open Access Journals (Sweden)

Choon Sen Seah

2017-12-01

Full Text Available Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.

A Classification of Human-to-Human Communication during the Use of Immersive Teleoperation Interfaces

DEFF Research Database (Denmark)

Kraus, Martin; Kibsgaard, Martin

2015-01-01

We propose a new classification of the human-to-human communication during the use of immersive teleoperation interfaces based on real-life examples. While a large body of research is concerned with communication in collaborative virtual environments (CVEs), less research focuses on cases where...... of the proposed classification to real environments can offer useful reference cases. Using this extended classification not only allows us to discuss and understand differences and similarities of various forms of communication in a more systematic way, but it also provides guidelines and reference cases...... for the design of immersive teleoperation interfaces that support human-to-human communication....

Comparative study of building footprint estimation methods from LiDAR point clouds

Science.gov (United States)

Rozas, E.; Rivera, F. F.; Cabaleiro, J. C.; Pena, T. F.; Vilariño, D. L.

2017-10-01

Building area calculation from LiDAR points is still a difficult task with no clear solution. Their different characteristics, such as shape or size, have made the process too complex to automate. However, several algorithms and techniques have been used in order to obtain an approximated hull. 3D-building reconstruction or urban planning are examples of important applications that benefit of accurate building footprint estimations. In this paper, we have carried out a study of accuracy in the estimation of the footprint of buildings from LiDAR points. The analysis focuses on the processing steps following the object recognition and classification, assuming that labeling of building points have been previously performed. Then, we perform an in-depth analysis of the influence of the point density over the accuracy of the building area estimation. In addition, a set of buildings with different size and shape were manually classified, in such a way that they can be used as benchmark.

Classification of Birds and Bats Using Flight Tracks

Energy Technology Data Exchange (ETDEWEB)

Cullinan, Valerie I.; Matzner, Shari; Duberstein, Corey A.

2015-05-01

Classification of birds and bats that use areas targeted for offshore wind farm development and the inference of their behavior is essential to evaluating the potential effects of development. The current approach to assessing the number and distribution of birds at sea involves transect surveys using trained individuals in boats or airplanes or using high-resolution imagery. These approaches are costly and have safety concerns. Based on a limited annotated library extracted from a single-camera thermal video, we provide a framework for building models that classify birds and bats and their associated behaviors. As an example, we developed a discriminant model for theoretical flight paths and applied it to data (N = 64 tracks) extracted from 5-min video clips. The agreement between model- and observer-classified path types was initially only 41%, but it increased to 73% when small-scale jitter was censored and path types were combined. Classification of 46 tracks of bats, swallows, gulls, and terns on average was 82% accurate, based on a jackknife cross-validation. Model classification of bats and terns (N = 4 and 2, respectively) was 94% and 91% correct, respectively; however, the variance associated with the tracks from these targets is poorly estimated. Model classification of gulls and swallows (N ≥ 18) was on average 73% and 85% correct, respectively. The models developed here should be considered preliminary because they are based on a small data set both in terms of the numbers of species and the identified flight tracks. Future classification models would be greatly improved by including a measure of distance between the camera and the target.

Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

Science.gov (United States)

A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

Radioactive facilities classification criteria

International Nuclear Information System (INIS)

Briso C, H.A.; Riesle W, J.

1992-01-01

Appropriate classification of radioactive facilities into groups of comparable risk constitutes one of the problems faced by most Regulatory Bodies. Regarding the radiological risk, the main facts to be considered are the radioactive inventory and the processes to which these radionuclides are subjected. Normally, operations are ruled by strict safety procedures. Thus, the total activity of the radionuclides existing in a given facility is the varying feature that defines its risk. In order to rely on a quantitative criterion and, considering that the Annual Limits of Intake are widely accepted references, an index based on these limits, to support decisions related to radioactive facilities, is proposed. (author)

Electroencephalography Signal Grouping and Feature Classification Using Harmony Search for BCI

Directory of Open Access Journals (Sweden)

Tae-Ju Lee

2013-01-01

Full Text Available This paper presents a heuristic method for electroencephalography (EEG grouping and feature classification using harmony search (HS for improving the accuracy of the brain-computer interface (BCI system. EEG, a noninvasive BCI method, uses many electrodes on the scalp, and a large number of electrodes make the resulting analysis difficult. In addition, traditional EEG analysis cannot handle multiple stimuli. On the other hand, the classification method using the EEG signal has a low accuracy. To solve these problems, we use a heuristic approach to reduce the complexities in multichannel problems and classification. In this study, we build a group of stimuli using the HS algorithm. Then, the features from common spatial patterns are classified by the HS classifier. To confirm the proposed method, we perform experiments using 64-channel EEG equipment. The subjects are subjected to three kinds of stimuli: audio, visual, and motion. Each stimulus is applied alone or in combination with the others. The acquired signals are processed by the proposed method. The classification results in an accuracy of approximately 63%. We conclude that the heuristic approach using the HS algorithm on the BCI is beneficial for EEG signal analysis.

Building renovations in BIM systems

Directory of Open Access Journals (Sweden)

Smutný Marian

2018-01-01

Full Text Available Renovation of buildings is a demanding challenge for computer systems. Nowadays, complex 3D models of historic buildings can be scanned and modelled, including sculptural filigrees and stucco decorations with possibility to generate different projections, cross-sections and elevations according to descriptive geometry rules. However, all of this falls within the field of “3D Modelling”. BIM systems work with elements that have to be classified according to their purpose, or according to the way they are realized. The system is then able to sort, filter or group them. Also, it is able to compute their bill of quantity and quality based on their attributes. Last but not least, it has to be able to schematically display civil engineering drawings on the basis of classification of the elements which differ considerably from the display of descriptive geometry. In regular constructions, repeatability and predictability of the links between the elements suit computer systems. Thus, the issue of building renovations in BIM systems is to find a balance between modelling irregular constructions and irregular space arrangements, while maintaining the ability to interact with other BIM elements.

Consensus classification of posterior cortical atrophy.

Science.gov (United States)

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

2017-08-01

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

Incremental Learning of Medical Data for Multi-Step Patient Health Classification

DEFF Research Database (Denmark)

Kranen, Philipp; Müller, Emmanuel; Assent, Ira

2010-01-01

of textile sensors, body sensors and preprocessing techniques as well as the integration and merging of sensor data in electronic health record systems. Emergency detection on multiple levels will show the benefits of multi-step classification and further enhance the scalability of emergency detection...

Automated detection of repeated structures in building facades

Directory of Open Access Journals (Sweden)

M. Previtali

2013-10-01

Full Text Available Automatic identification of high-level repeated structures in 3D point clouds of building façades is crucial for applications like digitalization and building modelling. Indeed, in many architectural styles building façades are governed by arrangements of objects into repeated patterns. In particular, façades are generally designed as the repetition of some few basic objects organized into interlaced and\\or concatenated grid structures. Starting from this key observation, this paper presents an algorithm for Repeated Structure Detection (RSD in 3D point clouds of building façades. The presented methodology consists of three main phases. First, in the point cloud segmentation stage (i the building façade is decomposed into planar patches which are classified by means of some weak prior knowledge of urban buildings formulated in a classification tree. Secondly (ii, in the element clustering phase detected patches are grouped together by means of a similarity function and pairwise transformations between patches are computed. Eventually (iii, in the structure regularity estimation step the parameters of repeated grid patterns are calculated by using a Least- Squares optimization. Workability of the presented approach is tested using some real data from urban scenes.

Menstrual Changes in Body Composition of Female Athletes.

Science.gov (United States)

Stachoń, Aleksandra Jadwiga

2016-06-01

The aim of the study was to determine whether the tendencies and scope of changes in body mass, body composition and body girths across the menstrual cycle were similar or different in women of different body build. Anthropometric examinations were carried out in a group of 40 naturally regularly menstruated females practicing team sports (aged 19-21, B-v 169.3+/-6.4 cm, body mass 59.6+/-7.0 kg), in the follicular, periovulatory and luteal phases of the menstrual cycle. The phases were determined on the basis of data from two consecutive menstrual cycles taking into account the cycle’s length. To establish the type of body build, Body Mass Index, hydration status and skinfold thickness were measured. For a statistical analysis, a multiple comparisons with multiple confidence intervals were applied. The increase in body mass between the follicular and the luteal phases was observed in all groups of women, the biggest gain was recorded in slim women, who in the luteal phase weighted 0.8 kg more. The amount of fat mass increased significantly across the menstrual cycle only in more hydrated (by about 0.66 kg) and slim women (by about 0.54 kg). Significant changes between consecutive phases of the menstrual cycle in waist and hip girths, and suprailiac skinfold thickness in some groups of women also indicate influence of fatness and hydration status and slenderness. In view of the presented results, the body build seems important for an analysis of the pattern of each component’s changes across the menstrual cycle, especially for female athletes. Certain changes can be seen only in some groups of women, therefore somatic features can be considered as a predictor of the intensity of changes.

An estimation framework for building information modeling (BIM)-based demolition waste by type.

Science.gov (United States)

Kim, Young-Chan; Hong, Won-Hwa; Park, Jae-Woo; Cha, Gi-Wook

2017-12-01

Most existing studies on demolition waste (DW) quantification do not have an official standard to estimate the amount and type of DW. Therefore, there are limitations in the existing literature for estimating DW with a consistent classification system. Building information modeling (BIM) is a technology that can generate and manage all the information required during the life cycle of a building, from design to demolition. Nevertheless, there has been a lack of research regarding its application to the demolition stage of a building. For an effective waste management plan, the estimation of the type and volume of DW should begin from the building design stage. However, the lack of tools hinders an early estimation. This study proposes a BIM-based framework that estimates DW in the early design stages, to achieve an effective and streamlined planning, processing, and management. Specifically, the input of construction materials in the Korean construction classification system and those in the BIM library were matched. Based on this matching integration, the estimates of DW by type were calculated by applying the weight/unit volume factors and the rates of DW volume change. To verify the framework, its operation was demonstrated by means of an actual BIM modeling and by comparing its results with those available in the literature. This study is expected to contribute not only to the estimation of DW at the building level, but also to the automated estimation of DW at the district level.

Classification of hydration status using electrocardiogram and machine learning

Science.gov (United States)

Kaveh, Anthony; Chung, Wayne

2013-10-01

The electrocardiogram (ECG) has been used extensively in clinical practice for decades to non-invasively characterize the health of heart tissue; however, these techniques are limited to time domain features. We propose a machine classification system using support vector machines (SVM) that uses temporal and spectral information to classify health state beyond cardiac arrhythmias. Our method uses single lead ECG to classify volume depletion (or dehydration) without the lengthy and costly blood analysis tests traditionally used for detecting dehydration status. Our method builds on established clinical ECG criteria for identifying electrolyte imbalances and lends to automated, computationally efficient implementation. The method was tested on the MIT-BIH PhysioNet database to validate this purely computational method for expedient disease-state classification. The results show high sensitivity, supporting use as a cost- and time-effective screening tool.

A simple calibration of a whole-body counter for the measurement of total body potassium in humans

International Nuclear Information System (INIS)

Abdel-Wahab, M.S.; El-Fiki, S.A.; El-Enany, N.; Youssef, S.K.; Aly, A.M.; Abbas, M.T.

1992-01-01

A simple calibration procedure for the Inshas whole body counter for evaluating total body potassium has been adopted. More than 120 Egyptian employees in the Nuclear Research Center (N.R.C.) were studied for their total body potassium (TBK). The potassium values were found to have an average of 2.85±0.57 g K kg -1 body weight for males and 2.62±0.52 g K kg -1 for females, which are higher than the recommended value given for reference man by ICRP. The TBK varied directly with body build index and is slightly sex dependent (Author)

Comparison of three methods for measuring height in rehabilitation inpatients and the impact on body mass index classification: An open prospective study.

Science.gov (United States)

McDougall, Karen E; Stewart, Alison J; Argiriou, Alison M; Huggins, Catherine E; New, Peter W

2018-02-01

To compare standing height, estimated current height and demi-span estimated height and examine their impact on body mass index (BMI) classification. Cross-sectional data was collected on 104 patients admitted to an adult rehabilitation ward and seen by the dietitian. Patient's standing, estimated current height and demi-span estimated height were collected and grouped by age: 19-64 and ≥65 years. The limits of agreement (95% confidence interval) for estimated current height compared with standing height were +9.9 cm and -7.9 cm, in contrast to +8.7 cm and -14.3 cm for demi-span estimated height. Demi-span underestimated height when compared with standing height in both age groups, 19-64 years: (mean ± SD) 3.0 ± 6.5 cm (P = 0.001, n = 68) and ≥ 65 year age group 4.0 ± 6.0 cm (P < 0.001, n = 36), resulting in a significantly greater mean BMI (analysis of variance P < 0.001, P = 0.02). In the 19-64 and ≥65 year age groups, 3% (2/68) and 10% (4/36) of patients, respectively, had a different BMI classification using demi-span estimated height compared with standing height. Estimated current height is a simple and practical alternative if standing height is unable to be obtained when performing a nutrition assessment. Demi-span estimated height should be used with caution when calculating BMI to assess nutritional status, particularly in the elderly. © 2017 Dietitians Association of Australia.

Final decommissioning report for the 183-C Filter Building/Pumproom facility

International Nuclear Information System (INIS)

Marske, S.G.

1997-04-01

This report documents the decommissioning and demolition (D ampersand D) of the 183-C Filter Building/Pumproom facility (located at the Hanford Site in Richland, Washington). The 183-C Facility D ampersand D involved the performance of characterization to support the development of a project plan and final hazard classification

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.

Hygrothermal Material Properties for Soils in Building Science

Energy Technology Data Exchange (ETDEWEB)

Kehrer, Manfred [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pallin, Simon B. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-01-01

Hygrothermal performance of soils coupled to buildings is complicated because of the dearth of information on soil properties. However they are important when numerical simulation of coupled heat and moisture transport for below-grade building components are performed as their temperature and moisture content has an influence on the durability of the below-grade building component. Soils can be classified by soil texture. According to the Unified Soil Classification System (USCA), 12 different soils can be defined on the basis of three soil components: clay, sand, and silt. This study shows how existing material properties for typical American soils can be transferred and used for the calculation of the coupled heat and moisture transport of building components in contact with soil. Furthermore a thermal validation with field measurements under known boundary conditions is part of this study, too. Field measurements for soil temperature and moisture content for two specified soils are carried out right now under known boundary conditions. As these field measurements are not finished yet, the full hygrothermal validation is still missing

Guy's Guide to Body Image

Science.gov (United States)

... height). For them, puberty may add to their insecurities. Building a Better Body Image So what can ... image, but getting too focused on appearance can cause a guy to overlook the other positive parts ...

Hyperspectral imaging of polymer banknotes for building and analysis of spectral library

Science.gov (United States)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-11-01

The use of counterfeit banknotes increases crime rates and cripples the economy. New countermeasures are required to stop counterfeiters who use advancing technologies with criminal intent. Many countries started adopting polymer banknotes to replace paper notes, as polymer notes are more durable and have better quality. The research on authenticating such banknotes is of much interest to the forensic investigators. Hyperspectral imaging can be employed to build a spectral library of polymer notes, which can then be used for classification to authenticate these notes. This is however not widely reported and has become a research interest in forensic identification. This paper focuses on the use of hyperspectral imaging on polymer notes to build spectral libraries, using a pushbroom hyperspectral imager which has been previously reported. As an initial study, a spectral library will be built from three arbitrarily chosen regions of interest of five circulated genuine polymer notes. Principal component analysis is used for dimension reduction and to convert the information in the spectral library to principal components. A 99% confidence ellipse is formed around the cluster of principal component scores of each class and then used as classification criteria. The potential of the adopted methodology is demonstrated by the classification of the imaged regions as training samples.

Biogeographic classification of the Caspian Sea

Science.gov (United States)

Fendereski, F.; Vogt, M.; Payne, M. R.; Lachkar, Z.; Gruber, N.; Salmanmahiny, A.; Hosseini, S. A.

2014-11-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the hierarchical agglomerative clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow nearshore waters from those offshore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (one-way ANOVA, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 25 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

Biogeographic classification of the Caspian Sea

DEFF Research Database (Denmark)

Fendereski, F.; Vogt, M.; Payne, Mark

2014-01-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information deriv...... confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics....... from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions...... in phytoplankton phenology, with differences in the date of bloom initiation, its duration and amplitude between ecoregions. A first qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also...

Evaluation of low-level radioactive waste characterization and classification programs of the West Valley Demonstration Project

International Nuclear Information System (INIS)

Taie, K.R.

1994-01-01

The West Valley Demonstration Project (WVDP) is preparing to upgrade their low-level radioactive waste (LLW) characterization and classification program. This thesis describes a survey study of three other DOE sites conducted in support of this effort. The LLW characterization/classification programs of Oak Ridge National Laboratory, Savannah River Site, and Idaho National Engineering Laboratory were critically evaluated. The evaluation was accomplished through tours of each site facility and personnel interviews. Comparative evaluation of the individual characterization/classification programs suggests the WVDP should purchase a real-time radiography unit and a passive/active neutron detection system, make additional mechanical modifications to the segmented gamma spectroscopy assay system, provide a separate building to house characterization equipment and perform assays away from waste storage, develop and document a new LLW characterization/classification methodology, and make use of the supercompactor owned by WVDP

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...

Characterizing Geological Facies using Seismic Waveform Classification in Sarawak Basin

Science.gov (United States)

Zahraa, Afiqah; Zailani, Ahmad; Prasad Ghosh, Deva

2017-10-01

Numerous effort have been made to build relationship between geology and geophysics using different techniques throughout the years. The integration of these two most important data in oil and gas industry can be used to reduce uncertainty in exploration and production especially for reservoir productivity enhancement and stratigraphic identification. This paper is focusing on seismic waveform classification to different classes using neural network and to link them according to the geological facies which are established using the knowledge on lithology and log motif of well data. Seismic inversion is used as the input for the neural network to act as the direct lithology indicator reducing dependency on well calibration. The interpretation of seismic facies classification map provides a better understanding towards the lithology distribution, depositional environment and help to identify significant reservoir rock

Child-Pugh classification dependent alterations in serum leptin levels among cirrhotic patients: a case controlled study

Directory of Open Access Journals (Sweden)

Zeyrek Fadile

2004-09-01

Full Text Available Abstract Background As anorexia and hypermetabolism are common in cirrhosis, leptin levels may be increased in this disease. In this study, we investigated the relation between the severity of disease and serum leptin levels in post-hepatitis cirrhosis and the role of body composition, gender and viral aetiology of cirrhosis in this association. Methods Thirty-five cases with post-hepatitis cirrhosis and 15 healthy controls were enrolled in this study. Body composition including body mass index, body fat percentage and body fat mass were determined. Serum leptin levels were assayed. Results Leptin levels were significantly higher among cirrhotic patients independent of sex compared to controls (p = 0.001. Female patients in both groups have had higher leptin levels than males (in cirrhotics p = 0.029, in controls p = 0.02. Cirrhotic patients in each of A, B and C subgroups according to the Child- Pugh classification revealed significantly different levels compared to controls (p = 0.046, p = 0.004, p = 0.0001, respectively. Male cirrhotics in Child-Pugh Class B and C subgroups had significantly higher leptin levels compared to male controls (p = 0.006, p = 0.008. On the other hand, female patients only in Child Pugh class C subgroup have had higher levels of serum leptin compared to controls (p = 0.022. Child-Pugh classification has been found to be the sole discriminator in determination of leptin levels in cirrhotics by linear regression (beta: 0.435 p = 0.015. Conclusion Serum leptin levels increase in advanced liver disease independently of gender, body composition in posthepatitic cirrhosis. The increase is more abundant among patients that belong to C subgroup according to the Child- Pugh classification.

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.

A study on the validity of strategic classification processes

International Nuclear Information System (INIS)

Tae, Jae Woong; Shin, Dong Hun

2013-01-01

The commodity classification is to identify strategic commodity. The export license is to verify that exports have met the conditions required by the international export control system. NSSC (Nuclear Safety and Security Commission) operates the NEPS (Nuclear Export Promotion Service) for export control of nuclear items. NEPS contributed to reduce process time related to submission of documents, issuing certificates and licenses, etc. Nonetheless, it became necessary to enhance capacity to implement export control precisely and efficiently as development of Korean nuclear industry led to sharp increase of export. To provide more efficient ways, development of the advanced export control system, IXCS (Intelligent eXport Control System) was suggested. To build IXCS successfully, export control experts have analyzed Korean export control system. Two classification processes of items and technology were derived as a result of the research. However, it may reflect real cases insufficiently because it is derived by experts' discussion. This study evaluated how well the process explains real cases. Although the derived processes explained real cases well, some recommendations for improvement were found through this study. These evaluation results will help to make classification flow charts more compatible to the current export system. Most classification reports on equipment and material deliberated specification and functions while related systems were not considered. If a 'specification review' stage is added to the current process and delete unnecessary stages, this will improve accuracy of the flow chart. In the classification of nuclear technology, detailed process to identify specific information and data need to be specified to decrease subjectivity. Whether they are imitations or not is an unnecessary factor in both processes. The successful development of IXCS needs accurate export control processes as well as IT technology. If these classification processes are

A Proposal to Develop Interactive Classification Technology

Science.gov (United States)

deBessonet, Cary

1998-01-01

Research for the first year was oriented towards: 1) the design of an interactive classification tool (ICT); and 2) the development of an appropriate theory of inference for use in ICT technology. The general objective was to develop a theory of classification that could accommodate a diverse array of objects, including events and their constituent objects. Throughout this report, the term "object" is to be interpreted in a broad sense to cover any kind of object, including living beings, non-living physical things, events, even ideas and concepts. The idea was to produce a theory that could serve as the uniting fabric of a base technology capable of being implemented in a variety of automated systems. The decision was made to employ two technologies under development by the principal investigator, namely, SMS (Symbolic Manipulation System) and SL (Symbolic Language) [see debessonet, 1991, for detailed descriptions of SMS and SL]. The plan was to enhance and modify these technologies for use in an ICT environment. As a means of giving focus and direction to the proposed research, the investigators decided to design an interactive, classificatory tool for use in building accessible knowledge bases for selected domains. Accordingly, the proposed research was divisible into tasks that included: 1) the design of technology for classifying domain objects and for building knowledge bases from the results automatically; 2) the development of a scheme of inference capable of drawing upon previously processed classificatory schemes and knowledge bases; and 3) the design of a query/ search module for accessing the knowledge bases built by the inclusive system. The interactive tool for classifying domain objects was to be designed initially for textual corpora with a view to having the technology eventually be used in robots to build sentential knowledge bases that would be supported by inference engines specially designed for the natural or man-made environments in which the

Supervised classification of distributed data streams for smart grids

Energy Technology Data Exchange (ETDEWEB)

Guarracino, Mario R. [High Performance Computing and Networking - National Research Council of Italy, Naples (Italy); Irpino, Antonio; Verde, Rosanna [Seconda Universita degli Studi di Napoli, Dipartimento di Studi Europei e Mediterranei, Caserta (Italy); Radziukyniene, Neringa [Lithuanian Energy Institute, Laboratory of Systems Control and Automation, Kaunas (Lithuania)

2012-03-15

The electricity system inherited from the 19th and 20th centuries has been a reliable but centralized system. With the spreading of local, distributed and intermittent renewable energy resources, top-down central control of the grid no longer meets modern requirements. For these reasons, the power grid has been equipped with smart meters integrating bi-directional communications, advanced power measurement and management capabilities. Smart meters make it possible to remotely turn power on or off to a customer, read usage information, detect a service outage and the unauthorized use of electricity. To fully exploit their capabilities, we foresee the usage of distributed supervised classification algorithms. By gathering data available from meters and other sensors, such algorithms can create local classification models for attack detection, online monitoring, privacy preservation, workload balancing, prediction of energy demand and incoming faults. In this paper we present a decentralized distributed classification algorithm based on proximal support vector machines. The method uses partial knowledge, in form of data streams, to build its local model on each meter. We demonstrate the performance of the proposed scheme on synthetic datasets. (orig.)

Hidden Markov Models for indirect classification of occupant behaviour

DEFF Research Database (Denmark)

Liisberg, Jon Anders Reichert; Møller, Jan Kloppenborg; Bloem, H.

2016-01-01

Even for similar residential buildings, a huge variability in the energy consumption can be observed. This variability is mainly due to the different behaviours of the occupants and this impacts the thermal (temperature setting, window opening, etc.) as well as the electrical (appliances, TV......, computer, etc.) consumption. It is very seldom to find direct observations of occupant presence and behaviour in residential buildings. However, given the increasing use of smart metering, the opportunity and potential for indirect observation and classification of occupants’ behaviour is possible...... sequence of states was determined (global decoding). From reconstruction of the states, dependencies like ambient air temperature were investigated. Combined with an occupant survey, this was used to classify/interpret the states as (1) absent or asleep, (2) home, medium consumption and (3) home, high...

Region-Based Building Rooftop Extraction and Change Detection

Science.gov (United States)

Tian, J.; Metzlaff, L.; d'Angelo, P.; Reinartz, P.

2017-09-01

Automatic extraction of building changes is important for many applications like disaster monitoring and city planning. Although a lot of research work is available based on 2D as well as 3D data, an improvement in accuracy and efficiency is still needed. The introducing of digital surface models (DSMs) to building change detection has strongly improved the resulting accuracy. In this paper, a post-classification approach is proposed for building change detection using satellite stereo imagery. Firstly, DSMs are generated from satellite stereo imagery and further refined by using a segmentation result obtained from the Sobel gradients of the panchromatic image. Besides the refined DSMs, the panchromatic image and the pansharpened multispectral image are used as input features for mean-shift segmentation. The DSM is used to calculate the nDSM, out of which the initial building candidate regions are extracted. The candidate mask is further refined by morphological filtering and by excluding shadow regions. Following this, all segments that overlap with a building candidate region are determined. A building oriented segments merging procedure is introduced to generate a final building rooftop mask. As the last step, object based change detection is performed by directly comparing the building rooftops extracted from the pre- and after-event imagery and by fusing the change indicators with the roof-top region map. A quantitative and qualitative assessment of the proposed approach is provided by using WorldView-2 satellite data from Istanbul, Turkey.

REGION-BASED BUILDING ROOFTOP EXTRACTION AND CHANGE DETECTION

Directory of Open Access Journals (Sweden)

J. Tian

2017-09-01

Full Text Available Automatic extraction of building changes is important for many applications like disaster monitoring and city planning. Although a lot of research work is available based on 2D as well as 3D data, an improvement in accuracy and efficiency is still needed. The introducing of digital surface models (DSMs to building change detection has strongly improved the resulting accuracy. In this paper, a post-classification approach is proposed for building change detection using satellite stereo imagery. Firstly, DSMs are generated from satellite stereo imagery and further refined by using a segmentation result obtained from the Sobel gradients of the panchromatic image. Besides the refined DSMs, the panchromatic image and the pansharpened multispectral image are used as input features for mean-shift segmentation. The DSM is used to calculate the nDSM, out of which the initial building candidate regions are extracted. The candidate mask is further refined by morphological filtering and by excluding shadow regions. Following this, all segments that overlap with a building candidate region are determined. A building oriented segments merging procedure is introduced to generate a final building rooftop mask. As the last step, object based change detection is performed by directly comparing the building rooftops extracted from the pre- and after-event imagery and by fusing the change indicators with the roof-top region map. A quantitative and qualitative assessment of the proposed approach is provided by using WorldView-2 satellite data from Istanbul, Turkey.

Energy absorption and exposure build-up factors in teeth

International Nuclear Information System (INIS)

Manjunatha, H.C.; Rudraswamy, B.

2010-01-01

Full text: Gamma and X-radiation are widely used in medical imaging and radiation therapy. The user of radioisotopes must have knowledge about how radiation interacts with matter, especially with the human body, because when photons enter the medium/body, they degrade their energy and build up in the medium, giving rise to secondary radiation which can be estimated by a factor which is called the 'build-up factor'. It is essential to study the exposure build up factor in radiation dosimetry. G.P. fitting method has been used to compute energy absorption and exposure build-up factor of teeth (enamel outer surface (EOS), enamel middle (EM), enamel dentin junction towards enamel (EDJE), enamel dentin junction towards dentin (EDJD), dentin middle (DM) and dentin inner surface (DIS)) for wide energy range (0.015 MeV-15 MeV) up to the penetration depth of 40 mean free path. The dependence of energy absorption and exposure build up factor on incident photon energy, Penetration depth and effective atomic number has also been assessed. The relative dose distribution at a distance r from the point source is also estimated. The computed exposure and absorption build-up factors are useful to estimate the gamma and Bremsstrahlung radiation dose distribution teeth which is useful in clinical dosimetry

Technology for Building Systems Integration and Optimization – Landscape Report

Energy Technology Data Exchange (ETDEWEB)

William Goetzler, Matt Guernsey, Youssef Bargach

2018-01-31

BTO's Commercial Building Integration (CBI) program helps advance a range of innovative building integration and optimization technologies and solutions, paving the way for high-performing buildings that could use 50-70% less energy than typical buildings. CBI’s work focuses on early stage technology innovation, with an emphasis on how components and systems work together and how whole buildings are integrated and optimized. This landscape study outlines the current body of knowledge, capabilities, and the broader array of solutions supporting integration and optimization in commercial buildings. CBI seeks to support solutions for both existing buildings and new construction, which often present very different challenges.

Automatic Generation of 3D Building Models with Multiple Roofs

Institute of Scientific and Technical Information of China (English)

Kenichi Sugihara; Yoshitugu Hayashi

2008-01-01

Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

Towards a comprehensive classification of igneous rocks and magmas

Science.gov (United States)

Middlemost, Eric A. K.

1991-08-01

The IUGS Subcommission on the Systematics of Igneous Rocks has recently published an excellent book on the classification of these rocks. This event has shifted the vexed question of classification towards the top of the agenda in igneous petrology. Over the years the Subcommission has used many different criteria to establish the positions of the boundaries between the various common igneous rocks. It now has to adopt a holistic approach and develop a comprehensive, coherent classification that is purged of all the minor anomalies that arise between the various classifications that it has approved. It is appreciated that the Subcommission's classification was never intended to have any genetic implications; however, it is suggested that an ideal classification should he presented in such a way that it is able to group rocks into an order that directs attention to petrogenetic relationships between individual rocks and larger groups of rocks. Unfortunately, many of the Subcommission's definitions are Earth chauvinistic; for example, igneous rocks are defined as being those rocks that solidified from a molten state either within or on the surface of the Earth. Nowhere in the book is it acknowledged that during the past 20 years, while the Subcommission has been framing its many recommendations, a whole new science of planetary petrology has subsumed classical petrology. In any new edition of the book, the Subcommission should acknowledge that rocks are essentially the solid materials of which planets, natural satellites and other broadly similar cosmic bodies are made. The Subcommission should also explicitly recognise that igneous rocks can be divided into either a main sequence of essentially common rocks or a number of supplementary clans of special rocks that evolved outside the main sequence. It is hoped that in the near future the Subcommission will rescind its recommendation that the TAS classification should be regarded as an adjunct to its more traditional

Final Safety Analysis Document for Building 693 Chemical Waste Storage Building at Lawrence Livermore National Laboratory

International Nuclear Information System (INIS)

Salazar, R.J.; Lane, S.

1992-02-01

This Safety Analysis Document (SAD) for the Lawrence Livermore National Laboratory (LLNL) Building 693, Chemical Waste Storage Building (desipated as Building 693 Container Storage Unit in the Laboratory's RCRA Part B permit application), provides the necessary information and analyses to conclude that Building 693 can be operated at low risk without unduly endangering the safety of the building operating personnel or adversely affecting the public or the environment. This Building 693 SAD consists of eight sections and supporting appendices. Section 1 presents a summary of the facility designs and operations and Section 2 summarizes the safety analysis method and results. Section 3 describes the site, the facility desip, operations and management structure. Sections 4 and 5 present the safety analysis and operational safety requirements (OSRs). Section 6 reviews Hazardous Waste Management's (HWM) Quality Assurance (QA) program. Section 7 lists the references and background material used in the preparation of this report Section 8 lists acronyms, abbreviations and symbols. Appendices contain supporting analyses, definitions, and descriptions that are referenced in the body of this report

[Remote sensing monitoring and screening for urban black and odorous water body: A review.

Science.gov (United States)

Shen, Qian; Zhu, Li; Cao, Hong Ye

2017-10-01

Continuous improvement of urban water environment and overall control of black and odorous water body are not merely national strategic needs with the action plan for prevention and treatment of water pollution, but also the hot issues attracting the attention of people. Most previous researches concentrated on the study of cause, evaluation and treatment measures of this phenomenon, and there are few researches on the monitoring using remote sensing, which is often a strain to meet the national needs of operational monitoring. This paper mainly summarized the urgent research problems, mainly including the identification and classification standard, research on the key technologies, and the frame of remote sensing screening systems for the urban black and odorous water body. The main key technologies were concluded too, including the high spatial resolution image preprocessing and extraction technique for black and odorous water body, the extraction of water information in city zones, the classification of the black and odorous water, and the identification and classification technique based on satellite-sky-ground remote sensing. This paper summarized the research progress and put forward research ideas of monitoring and screening urban black and odorous water body via high spatial resolution remote sensing technology, which would be beneficial to having an overall grasp of spatial distribution and improvement progress of black and odorous water body, and provide strong technical support for controlling urban black and odorous water body.

Optimized hardware framework of MLP with random hidden layers for classification applications

Science.gov (United States)

Zyarah, Abdullah M.; Ramesh, Abhishek; Merkel, Cory; Kudithipudi, Dhireesha

2016-05-01

Multilayer Perceptron Networks with random hidden layers are very efficient at automatic feature extraction and offer significant performance improvements in the training process. They essentially employ large collection of fixed, random features, and are expedient for form-factor constrained embedded platforms. In this work, a reconfigurable and scalable architecture is proposed for the MLPs with random hidden layers with a customized building block based on CORDIC algorithm. The proposed architecture also exploits fixed point operations for area efficiency. The design is validated for classification on two different datasets. An accuracy of ~ 90% for MNIST dataset and 75% for gender classification on LFW dataset was observed. The hardware has 299 speed-up over the corresponding software realization.

INDUCON building concept; INDUCON-rakennuskonsepti

Energy Technology Data Exchange (ETDEWEB)

Sarja, A.; Laine, J.; Pulakka, S.; Saari, M. [VTT Building and Transport, Espoo (Finland)

2003-08-01

The new and stronger requirements: lifetime economy, functionality in use and in changes of use, technical lifetime performance, energy efficiency, healthy, safety, ecology and local culture, are serving a challenge for the building technology. Additionally the pressure towards decreasing the construction costs with the increase of productivity of the work and capital is increased. The objective of this research work has been to respond the challenges described above with creating alternative building concepts, which could allow production of individually designed apartment and office buildings, including methodology and methods to optimise the building concepts and individual buildings in relation to the lifetime quality. Building concept is a repeatable and documented way of design and construction, which can result in individual buildings with an optimised and high lifetime quality. Lifetime quality is the capability of a building to fulfil the requirements of the users, owners and society during entire design period of the building. The INDUCON building concept is focused on the following issues: Classified and optimised lifetime quality (incl. the viewpoints of functionality, performance, economy, ecology and culture), and the realisation of industrial production on an advanced level (incl. new models of building design and construction, simplification of building systems and products, decrease of the number of parts of buildings, improvement of finishing of the prefabricated components and modules, and improving the interaction and compatibility of structures and building service systems). As a result are presented: systematised and classified definitions of performance properties of buildings; corresponding specifications of building systems, modules and components; design principles, process descriptions; examples (incl. Routings of technical building services, specification and classification of the health and comfort properties of indoor air, calculations

Updated United Nations Framework Classification for reserves and resources of extractive industries

Science.gov (United States)

Ahlbrandt, T.S.; Blaise, J.R.; Blystad, P.; Kelter, D.; Gabrielyants, G.; Heiberg, S.; Martinez, A.; Ross, J.G.; Slavov, S.; Subelj, A.; Young, E.D.

2004-01-01

The United Nations have studied how the oil and gas resource classification developed jointly by the SPE, the World Petroleum Congress (WPC) and the American Association of Petroleum Geologists (AAPG) could be harmonized with the United Nations Framework Classification (UNFC) for Solid Fuel and Mineral Resources (1). The United Nations has continued to build on this and other works, with support from many relevant international organizations, with the objective of updating the UNFC to apply to the extractive industries. The result is the United Nations Framework Classification for Energy and Mineral Resources (2) that this paper will present. Reserves and resources are categorized with respect to three sets of criteria: ??? Economic and commercial viability ??? Field project status and feasibility ??? The level of geologic knowledge The field project status criteria are readily recognized as the ones highlighted in the SPE/WPC/AAPG classification system of 2000. The geologic criteria absorb the rich traditions that form the primary basis for the Russian classification system, and the ones used to delimit, in part, proved reserves. Economic and commercial criteria facilitate the use of the classification in general, and reflect the commercial considerations used to delimit proved reserves in particular. The classification system will help to develop a common understanding of reserves and resources for all the extractive industries and will assist: ??? International and national resources management to secure supplies; ??? Industries' management of business processes to achieve efficiency in exploration and production; and ??? An appropriate basis for documenting the value of reserves and resources in financial statements.

Physics of the Human Body

CERN Document Server

Herman, Irving P

2007-01-01

Physics of the Human Body comprehensively addresses the physical and engineering aspects of human physiology by using and building on first-year college physics and mathematics. Topics include the mechanics of the static body and the body in motion, the materials properties of the body, muscles in the body, the energetics of body metabolism, fluid flow in the cardiovascular and respiratory systems, the acoustics of sound waves in speaking and hearing, vision and the optics of the eye, the electrical properties of the body, and the basic engineering principles of feedback and control in regulating all aspects of function. The goal of this text is to understand physical issues concerning the human body, in part by developing and then using simple and subsequently more refined models of the macrophysics of the human body. Many chapters include a brief review of the necessary physical principles. There are problems at the end of each chapter; solutions to selected problems are also provided. This text is geared t...

Mobile communications – on standards, classifications and generations

DEFF Research Database (Denmark)

Tadayoni, Reza; Henten, Anders; Sørensen, Jannick Kirk

The research question addressed in this paper is concerned with the manners in which the general technological progress in mobile communications is presented and the reasons for the differences in these manners of presentation. The relevance of this research question is that the different....... In common parlance, progress in mobile technologies is mostly referred to as generations. In the International Telecommunication Union (ITU), the classification terminology is that of International Mobile Telecommunication (IMT) standards. In the specialized standards body with a central position...... in the standardization of core mobile technologies, namely 3GPP (3rd Generation Partnership Project), the terminology of ‘releases’ is used. In order to address the research question, the paper uses an analytical framework based on the differences and relationships between the concepts of standards, classifications...

Dual energy X-Ray absorptiometry body composition reference values from NHANES.

Directory of Open Access Journals (Sweden)

Thomas L Kelly

Full Text Available In 2008 the National Center for Health Statistics released a dual energy x-ray absorptiometry (DXA whole body dataset from the NHANES population-based sample acquired with modern fan beam scanners in 15 counties across the United States from 1999 through 2004. The NHANES dataset was partitioned by gender and ethnicity and DXA whole body measures of %fat, fat mass/height(2, lean mass/height(2, appendicular lean mass/height(2, %fat trunk/%fat legs ratio, trunk/limb fat mass ratio of fat, bone mineral content (BMC and bone mineral density (BMD were analyzed to provide reference values for subjects 8 to 85 years old. DXA reference values for adults were normalized to age; reference values for children included total and sub-total whole body results and were normalized to age, height, or lean mass. We developed an obesity classification scheme by using estabbody mass index (BMI classification thresholds and prevalences in young adults to generate matching classification thresholds for Fat Mass Index (FMI; fat mass/height(2. These reference values should be helpful in the evaluation of a variety of adult and childhood abnormalities involving fat, lean, and bone, for establishing entry criteria into clinical trials, and for other medical, research, and epidemiological uses.

FACTOR ANALYSIS OF MULTISTOREY RESIDENTIAL BUILDINGS ZONE

Directory of Open Access Journals (Sweden)

Петр Матвеевич Мазуркин

2016-02-01

Full Text Available According to the UN classification of 11 classes of soil cover, the first three are grass, trees and shrubs and forests. In the city they correspond to the three elements of vegetation: lawns, tree plantings (trees and shrubs. We have adopted zoning for city-building to identify statistical regularities. Map dimensions in GIS "Map 2011" Yoshkar-Ola was allocated to "residential zone" and "Area of construction of multi-storey residential buildings (cadastral 58 quart crystals". The parameters of the elements of the vegetation cover have been considered: the number of elements of different levels, area and perimeter, the absolute and relative form, and activity of vegetation. As the result, we have obtained equations of binomial rank distributions, conducted the ratings and selected the best of cadastral quarter on environmental conditions.

Planetary Taxonomy: Label Round Bodies "Worlds"

Science.gov (United States)

Margot, Jean-Luc; Levison, H. F.

2009-05-01

The classification of planetary bodies is as important to Astronomy as taxonomy is to other sciences. The etymological, historical, and IAU definitions of planet rely on a dynamical criterion, but some authors prefer a geophysical criterion based on "roundness". Although the former criterion is superior when it comes to classifying newly discovered objects, the conflict need not exist if we agree to identify the subset of "round" planetary objects as "worlds". This addition to the taxonomy would conveniently recognize that "round" objects such as Earth, Europa, Titan, Triton, and Pluto share some common planetary-type processes regardless of their distance from the host star. Some of these worlds are planets, others are not. Defining how round is round and handling the inevitable transition objects are non-trivial tasks. Because images at sufficient resolution are not available for the overwhelming majority of newly discovered objects, the degree of roundness is not a directly observable property and is inherently problematic as a basis for classification. We can tolerate some uncertainty in establishing the "world" status of a newly discovered object, and still establish its planet or satellite status with existing dynamical criteria. Because orbital parameters are directly observable, and because mass can often be measured either from orbital perturbations or from the presence of companions, the dynamics provide a robust and practical planet classification scheme. It may also be possible to determine which bodies are dynamically dominant from observations of the population magnitude/size distribution.

Raster Vs. Point Cloud LiDAR Data Classification

Science.gov (United States)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

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...

How automated image analysis techniques help scientists in species identification and classification?

Science.gov (United States)

Yousef Kalafi, Elham; Town, Christopher; Kaur Dhillon, Sarinder

2017-09-04

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification increased over the last two decades. Automation of data classification is primarily focussed on images, incorporating and analysing image data has recently become easier due to developments in computational technology. Research efforts in identification of species include specimens' image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, categorizing and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies.

Learning, Transparency and Relationship Building: Ethiopian ...

International Development Research Centre (IDRC) Digital Library (Canada)

Learning, Transparency and Relationship Building: Ethiopian Women Parliamentarians and Young Female University Students. IDRC's Democratic Governance, Women's Rights and Gender Equality initiative is supporting a body of comparative research on whether and how democratic processes and institutions are ...

A fuzzy decision tree method for fault classification in the steam generator of a pressurized water reactor

International Nuclear Information System (INIS)

Zio, Enrico; Baraldi, Piero; Popescu, Irina Crenguta

2009-01-01

This paper extends a method previously introduced by the authors for building a transparent fault classification algorithm by combining the fuzzy clustering, fuzzy logic and decision trees techniques. The baseline method transforms an opaque, fuzzy clustering-based classification model into a fuzzy logic inference model based on linguistic rules which can be represented by a decision tree formalism. The classification model thereby obtained is transparent in that it allows direct interpretation and inspection of the model. An extension in the procedure for the development of the fuzzy logic inference model is introduced to allow the treatment of more complicated cases, e.g. splitted and overlapping clusters. The corresponding computational tool developed relies on a number of parameters which can be tuned by the user to optimally compromise the level of transparency of the classification process and its efficiency. A numerical application is presented with regards to the fault classification in the Steam Generator of a Pressurized Water Reactor.

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....

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...

Building energy governance in Shanghai

Science.gov (United States)

Kung, YiHsiu Michelle

other rapidly growing second-tier or third-tier cities in China, and to further contribute to the general body of knowledge on Asia's urban building sustainability.

A Study to Compare the Cost of Operation and Maintenance in Green Building Index (GBI and Non-Green Building Index (Non-GBI Rated Building in Malaysia

Directory of Open Access Journals (Sweden)

Ping Lee Zheng

2016-01-01

Full Text Available Urges for sustainable development had pushed the government and professional bodies to respond and react by implementing regulations where possible to direct development in that manner. However, the outcome in most financial conferences and dialogues on sustainable buildings flagged on high construction and maintenance cost. Thus, this study is conducted to collect and analyze actual building operation and maintenance cost between GBI and Non-GBI rated buildings in Malaysia which are more than 2 years fully operated buildings. There are two categories of selected buildings which are residential and non-residential type of building. Each category of the building consists of similar building’s characteristic such as geographic location, mode of operation, building heights, total numbers of floors and units. The scope of building’s maintenance for this study is mainly on wear and tear of the wall painting, electrical light fittings, ceiling panels, roofing system and mechanical services like water pump system are recorded for their replacement frequency of service and the cost involved within a consistent period of 12 months operation at cost percentage saving of 78.9% and 40.4% for residential and non-residential buildings respectively compare against Non-GBI rated buildings. Electricity consumption for GBI rated buildings are lower than Non-GBI rated buildings which recorded at the cost variance of 23.8% and 6.3% and water consumption at 35.9% and 44.0% for the above mentioned two main categories of selected case study buildings. Results from this study conclude major savings on residential buildings category in term of maintenance cost and electricity consumption for GBI rated buildings. Whereby, non-residential category of buildings, GBI rated building had been proven to obtain significant savings in terms of maintenance cost and water consumption.

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

CSIR Research Space (South Africa)

Mabuza-Hocquet, Gugulethu

2017-03-01

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

Helle Brabrand body_space_interface

DEFF Research Database (Denmark)

Brabrand, Helle

2016-01-01

The WEBSITE presents a responsive body-space-media praxis and questions architectonic space-making as a field of artistic research. What are the implications of architectonic modelling, conceived on terms of becoming and in exchange with, but different from actually rising buildings? How to handle...... the complexity of models as performing and presenting agencies and expressions, rather than as re-presenting a building to be? Body_space_interface questions architectural making, asking what kind of world-material may be seized and transformed to produce sensual dimensions in modeling - and vice-versa, which...... you to take part in the above outlined reflections on modeling. It presents different projects as series of both moving and still images that call on improvising rhythm, duration, and order of succession; and it imply resonance and diagram as diverse modes of reflection....

Physics of the human body

CERN Document Server

Herman, Irving P

2016-01-01

This book comprehensively addresses the physics and engineering aspects of human physiology by using and building on first-year college physics and mathematics. Topics include the mechanics of the static body and the body in motion, the mechanical properties of the body, muscles in the body, the energetics of body metabolism, fluid flow in the cardiovascular and respiratory systems, the acoustics of sound waves in speaking and hearing, vision and the optics of the eye, the electrical properties of the body, and the basic engineering principles of feedback and control in regulating all aspects of function. The goal of this text is to clearly explain the physics issues concerning the human body, in part by developing and then using simple and subsequently more refined models of the macrophysics of the human body. Many chapters include a brief review of the underlying physics. There are problems at the end of each chapter; solutions to selected problems are also provided. This second edition enhances the treat...

Association of depression with body mass index classification, metabolic disease, and lifestyle: A web-based survey involving 11,876 Japanese people.

Science.gov (United States)

Hidese, Shinsuke; Asano, Shinya; Saito, Kenji; Sasayama, Daimei; Kunugi, Hiroshi

2018-02-10

Body mass index (BMI) and lifestyle-related physical illnesses have been implicated in the pathology of depression. We aimed to investigate the association of depression wih BMI classification (i.e., underweight, normal, overweight, and obese), metabolic disease, and lifestyle using a web-based survey in a large cohort. Participants were 1000 individuals who have had depression (mean age: 41.4 ± 12.3 years, 501 men) and 10,876 population-based controls (45.1 ± 13.6 years, 5691 men). The six-item Kessler scale (K6) test was used as a psychological distress scale. Compared to in the controls, obesity and hyperlipidemia were more common and frequency of a snack or night meal consumption was higher, whereas frequencies of breakfast consumption and vigorous and moderate physical activities were lower in the patients. K6 test scores were higher for underweight or obese people compared to normal or overweight people. A logistic regression analysis showed that the K6 test cut-off score was positively associated with being underweight, hyperlipidemia, and the frequency of a snack or night meal consumption, whereas it was negatively associated with the frequency of breakfast consumption in the patients. Logistic regression analyses showed that self-reported depression was positively associated with metabolic diseases and the frequency of a snack or night meal consumption, whereas it was negatively associated with the frequency of breakfast consumption. The observed associations of depression with BMI classification, metabolic disease, and lifestyle suggest that lifestyle and related physical conditions are involved in at least a portion of depressive disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

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...

A dynamical classification of the cosmic web

Science.gov (United States)

Forero-Romero, J. E.; Hoffman, Y.; Gottlöber, S.; Klypin, A.; Yepes, G.

2009-07-01

In this paper, we propose a new dynamical classification of the cosmic web. Each point in space is classified in one of four possible web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor (i.e. the Hessian of the gravitational potential) on a grid. The classification is based on counting the number of eigenvalues above a certain threshold, λth, at each grid point, where the case of zero, one, two or three such eigenvalues corresponds to void, sheet, filament or a knot grid point. The collection of neighbouring grid points, friends of friends, of the same web type constitutes voids, sheets, filaments and knots as extended web objects. A simple dynamical consideration of the emergence of the web suggests that the threshold should not be null, as in previous implementations of the algorithm. A detailed dynamical analysis would have found different threshold values for the collapse of sheets, filaments and knots. Short of such an analysis a phenomenological approach has been opted for, looking for a single threshold to be determined by analysing numerical simulations. Our cosmic web classification has been applied and tested against a suite of large (dark matter only) cosmological N-body simulations. In particular, the dependence of the volume and mass filling fractions on λth and on the resolution has been calculated for the four web types. We also study the percolation properties of voids and filaments. Our main findings are as follows. (i) Already at λth = 0.1 the resulting web classification reproduces the visual impression of the cosmic web. (ii) Between 0.2 net of interconnected filaments. This suggests a reasonable choice for λth as the parameter that defines the cosmic web. (iii) The dynamical nature of the suggested classification provides a robust framework for incorporating environmental information into galaxy formation models, and in particular to semi-analytical models.

UK adaptation strategy and technical measures: the impacts of climate change on buildings

International Nuclear Information System (INIS)

Sanders, C.H.; Phillipson, M.C.

2003-01-01

This paper discusses the importance of climate change for the UK building stock and reviews the predictions of the United Kingdom Climate Impacts Programme 2002 (UKCIP02) scenarios for the future climate that are of relevance to buildings and construction. The possible impacts of these changes on flooding, wind damage, driving rain impact, subsidence and the internal environment of buildings are reviewed and the steps that might be taken to mitigate these impacts discussed. The current response of regulators, standardisation bodies, building owners and the insurance industry to these impacts is examined, and it is shown that each body acts in different ways to different impacts. Some bodies, such as government departments responsible for building regulations and the insurance industry, are taking the possibility of climate change very seriously. However, the uncertainty of future climate predictions, especially as regards wind speed, means that it is not easy to incorporate these issues in formal legislation. The whole culture of standardisation, which is based on well-established data, such as mean climate data over the last 30 years, makes it difficult for British and European Standards, which underpin regulations, to react to the changing climate. (author)

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.

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.)

Application of the International Classification of Functioning, Disability and Health system to symptoms of the Duchenne and Becker muscular dystrophies.

Science.gov (United States)

Conway, Kristin M; Ciafaloni, Emma; Matthews, Dennis; Westfield, Chris; James, Kathy; Paramsothy, Pangaja; Romitti, Paul A

2018-07-01

Duchenne and Becker muscular dystrophies, collectively referred to as dystrophinopathies, are X-linked recessive diseases that affect dystrophin production resulting in compromised muscle function across multiple systems. The International Classification of Functioning, Disability and Health provides a systematic classification scheme from which body functions affected by a dystrophinopathy can be identified and used to examine functional health. The infrastructure of the Muscular Dystrophy Surveillance, Tracking, and Research Network was used to identify commonly affected body functions and link selected functions to clinical surveillance data collected through medical record abstraction. Seventy-one (24 second-, 41 third- and 7 fourth-level) body function categories were selected via clinician review and consensus. Of these, 15 of 24 retained second-level categories were linked to data elements from the Muscular Dystrophy Surveillance, Tracking, and Research Network surveillance database. Our findings support continued development of a core set of body functions from the International Classification of Functioning, Disability and Health system that are representative of disease progression in dystrophinopathies and the incorporation of these functions in standardized evaluations of functional health and implementation of individualized rehabilitation care plans. Implications for Rehabilitation Duchenne and Becker muscular dystrophies, collectively referred to as dystrophinopathies, are X-linked recessive disorders that affect the production of dystrophin resulting in compromised muscle function across multiple systems. The severity and progressive nature of dystrophinopathies can have considerable impact on a patient's participation in activities across multiple life domains. Our findings support continued development of an International Classification of Functioning, Disability and Health core set for childhood-onset dystrophinopathies. A standardized

Phenomenology and classification of dystonia: a consensus update.

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Albanese, Alberto; Bhatia, Kailash; Bressman, Susan B; Delong, Mahlon R; Fahn, Stanley; Fung, Victor S C; Hallett, Mark; Jankovic, Joseph; Jinnah, Hyder A; Klein, Christine; Lang, Anthony E; Mink, Jonathan W; Teller, Jan K

2013-06-15

This report describes the consensus outcome of an international panel consisting of investigators with years of experience in this field that reviewed the definition and classification of dystonia. Agreement was obtained based on a consensus development methodology during 3 in-person meetings and manuscript review by mail. Dystonia is defined as a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both. Dystonic movements are typically patterned and twisting, and may be tremulous. Dystonia is often initiated or worsened by voluntary action and associated with overflow muscle activation. Dystonia is classified along 2 axes: clinical characteristics, including age at onset, body distribution, temporal pattern and associated features (additional movement disorders or neurological features); and etiology, which includes nervous system pathology and inheritance. The clinical characteristics fall into several specific dystonia syndromes that help to guide diagnosis and treatment. We provide here a new general definition of dystonia and propose a new classification. We encourage clinicians and researchers to use these innovative definition and classification and test them in the clinical setting on a variety of patients with dystonia. © 2013 Movement Disorder Society. © 2013 Movement Disorder Society.

Assessment of respiratory muscle strength in children according to the classification of body mass index

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George Jung da Rosa

2014-06-01

Full Text Available OBJECTIVE: To assess and compare the respiratory muscle strength among eutrophic, overweight and obese school children, as well as to identify anthropometric and respiratory variables related to the results.METHODS: Cross-sectional survey with healthy schoolchildren aged 7-9 years old, divided into three groups: Normal weight, Overweight and Obese. The International Study of Asthma and Allergies in Childhood (ISAAC questionnaire was applied. The body mass index (BMI was evaluated, as well as the forced expiratory volume in one second (FEV1 with a portable digital device. The maximal inspiratory and expiratory pressures (MIP and MEP were measured by a digital manometer. Comparisons between the groups were made by Kruskal-Wallis test. Spearman's correlation coefficient was used to analyze the correlations among the variables.RESULTS: MIP of eutrophic school children was higher than MIP found in overweight (p=0.043 and obese (p=0.013 children. MIP was correlated with BMI percentile and weight classification (r=-0.214 and r=-0.256 and MEP was correlated with height (r=0.328. Both pressures showed strong correlation with each other in all analyses (r≥0.773, and less correlation with FEV1 (MIP - r=0.362 and MEP - r=0.494. FEV1 correlated with MEP in all groups (r: 0.429 - 0.569 and with MIP in Obese Group (r=0.565. Age was correlated with FEV1 (r=0.578, MIP (r=0.281 and MEP (r=0.328.CONCLUSIONS: Overweight and obese children showed lower MIP values, compared to eutrophic ones. The findings point to the influence of anthropometric variables on respiratory muscle strength in children.

Data for occupancy internal heat gain calculation in main building categories

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Kaiser Ahmed

2017-12-01

Full Text Available Heat losses from occupant body by means of convection, radiation, vapor, and sweat are essential data for indoor climate and energy simulations. Heat losses depend on the metabolic activity and body surface area. Higher variations of body surface area of occupants are observed in day care centers, kinder gardens and schools compared to other building categories (Tables 2 and 3 and these variations need to be accounted, otherwise in these building categories heat gains, CO2 and humidity generation are overestimated. Indoor temperature, humidity level, air velocity, and clothing insulation have significant influences on dry and total heat losses from occupant body leading to typical values for summer and winter. The data presented in this article are related to the research article entitled Occupancy schedules for energy simulation in new prEN16798-1 and ISO/FDIS 17772-1 standards (Ahmed et al., 2017 [1]. Keywords: Body surface area, Metabolic rate, Dry heat loss, Total heat loss, Internal heat gain

A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

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Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

2014-10-01

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

Scaling and allometry in the building geometries of Greater London

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Batty, M.; Carvalho, R.; Hudson-Smith, A.; Milton, R.; Smith, D.; Steadman, P.

2008-06-01

Many aggregate distributions of urban activities such as city sizes reveal scaling but hardly any work exists on the properties of spatial distributions within individual cities, notwithstanding considerable knowledge about their fractal structure. We redress this here by examining scaling relationships in a world city using data on the geometric properties of individual buildings. We first summarise how power laws can be used to approximate the size distributions of buildings, in analogy to city-size distributions which have been widely studied as rank-size and lognormal distributions following Zipf [ Human Behavior and the Principle of Least Effort (Addison-Wesley, Cambridge, 1949)] and Gibrat [ Les Inégalités Économiques (Librarie du Recueil Sirey, Paris, 1931)]. We then extend this analysis to allometric relationships between buildings in terms of their different geometric size properties. We present some preliminary analysis of building heights from the Emporis database which suggests very strong scaling in world cities. The data base for Greater London is then introduced from which we extract 3.6 million buildings whose scaling properties we explore. We examine key allometric relationships between these different properties illustrating how building shape changes according to size, and we extend this analysis to the classification of buildings according to land use types. We conclude with an analysis of two-point correlation functions of building geometries which supports our non-spatial analysis of scaling.

Bio-geographic classification of the Caspian Sea

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Fendereski, F.; Vogt, M.; Payne, M. R.; Lachkar, Z.; Gruber, N.; Salmanmahiny, A.; Hosseini, S. A.

2014-03-01

Like other inland seas, the Caspian Sea (CS) has been influenced by climate change and anthropogenic disturbance during recent decades, yet the scientific understanding of this water body remains poor. In this study, an eco-geographical classification of the CS based on physical information derived from space and in-situ data is developed and tested against a set of biological observations. We used a two-step classification procedure, consisting of (i) a data reduction with self-organizing maps (SOMs) and (ii) a synthesis of the most relevant features into a reduced number of marine ecoregions using the Hierarchical Agglomerative Clustering (HAC) method. From an initial set of 12 potential physical variables, 6 independent variables were selected for the classification algorithm, i.e., sea surface temperature (SST), bathymetry, sea ice, seasonal variation of sea surface salinity (DSSS), total suspended matter (TSM) and its seasonal variation (DTSM). The classification results reveal a robust separation between the northern and the middle/southern basins as well as a separation of the shallow near-shore waters from those off-shore. The observed patterns in ecoregions can be attributed to differences in climate and geochemical factors such as distance from river, water depth and currents. A comparison of the annual and monthly mean Chl a concentrations between the different ecoregions shows significant differences (Kruskal-Wallis rank test, P qualitative evaluation of differences in community composition based on recorded presence-absence patterns of 27 different species of plankton, fish and benthic invertebrate also confirms the relevance of the ecoregions as proxies for habitats with common biological characteristics.

Automatic topic identification of health-related messages in online health community using text classification.

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Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

Suggestions for the New Social Entrepreneurship Initiative: Focus on Building a Body of Research-Proven Programs, Shown to Produce Major Gains in Education, Poverty Reduction, Crime Prevention, and Other Areas

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Coalition for Evidence-Based Policy, 2009

2009-01-01

This paper outlines a possible approach to implementing the Social Entrepreneurship initiative, focused on building a body of research-proven program models/strategies, and scaling them up, so as to produce major progress in education, poverty reduction, crime prevention, and other areas. The paper summarizes the rationale for this approach, then…

A DIMENSION REDUCTION-BASED METHOD FOR CLASSIFICATION OF HYPERSPECTRAL AND LIDAR DATA

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B. Abbasi

2015-12-01

Full Text Available The existence of various natural objects such as grass, trees, and rivers along with artificial manmade features such as buildings and roads, make it difficult to classify ground objects. Consequently using single data or simple classification approach cannot improve classification results in object identification. Also, using of a variety of data from different sensors; increase the accuracy of spatial and spectral information. In this paper, we proposed a classification algorithm on joint use of hyperspectral and Lidar (Light Detection and Ranging data based on dimension reduction. First, some feature extraction techniques are applied to achieve more information from Lidar and hyperspectral data. Also Principal component analysis (PCA and Minimum Noise Fraction (MNF have been utilized to reduce the dimension of spectral features. The number of 30 features containing the most information of the hyperspectral images is considered for both PCA and MNF. In addition, Normalized Difference Vegetation Index (NDVI has been measured to highlight the vegetation. Furthermore, the extracted features from Lidar data calculated based on relation between every pixel of data and surrounding pixels in local neighbourhood windows. The extracted features are based on the Grey Level Co-occurrence Matrix (GLCM matrix. In second step, classification is operated in all features which obtained by MNF, PCA, NDVI and GLCM and trained by class samples. After this step, two classification maps are obtained by SVM classifier with MNF+NDVI+GLCM features and PCA+NDVI+GLCM features, respectively. Finally, the classified images are fused together to create final classification map by decision fusion based majority voting strategy.

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

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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.

Building Fire Safety Audit at Faculty X, University of Indonesia, Year 2006

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Fatma Lestari

2010-10-01

Full Text Available Fire may cause loss of life, material and valuable assets. The objective of this study is to conduct audit for fire safety and emergency response in the building at Faculty X, University of Indonesia, Depok. The audit results on the building fire safety facilities including emergency response and preparedness are then compared to the Building Code Australia (BCA and Indonesian regulation on the building fire safety (Kep.MenPU.No 10 and 11/KPTS/2000. The building selected are Building A, B, C, D, F and G. Building classification for A, B, D, F and G are classified as Class 5, while Building C is classified as Class 9b. Variable which are evaluated including emergency exit, building structure, fire alarm and detector, communication and fire warning system, evacuation procedure, portable fire extinguishers, hydrant, sprinkler, and emergency response preparedness. Results suggested that emergency exit is locked, and this is not comply to the regulation. Building structure has been complied to the regulation since it was made of concrete. Fire detector and alarm only provided in Building G, while other building is not available. There is no evacuation procedure available. Portable fire extinguisher has been available in all the building. Hydrant an sprinkler only available in building G. There is no emergency response preparedness in this faculty. In conclusion, the fire safety facilities in this faculty need to be improved.

Classification

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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…

Cardiovascular manifestations of anabolic steroids in association with demographic variables in body building athletes.

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Gheshlaghi, Farzad; Piri-Ardakani, Mohammad-Reza; Masoumi, Gholam Reza; Behjati, Mohaddaseh; Paydar, Parva

2015-02-01

The most common drug abuse among athletes is anabolic steroids which lead to the development of cardiovascular diseases and sudden death. Thus, the aim of this study was to evaluate cardiovascular outcomes of anabolic consumption in body building athletes. Totally, 267 male athletes at the range of 20-45 years old with the regular consumption of anabolic steroids for >2 months with at least once weekly. High-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), and hematocrit (Hct) levels were measured after 10 h of fasting. Data analysis was performed using K2, t-test, ANOVA and correlation coefficient through SPSS 17. There was a nonsignificant difference between groups regarding HDL, TG, and total cholesterol. There was a significant decrease in the total and categorized LDL and Hct levels in consumers of anabolic steroid versus nonusers (P = 0.01 and P = 0.041, respectively). Results showed a significant increase in systolic and diastolic blood pressure (SBP and DBP) in anabolic steroid users which associates with duration of abuse (P = 0.02 and P = 0.03, respectively). No significant electrocardiography changes were found within the follow-up period. Increase in SBP or DBP is a common complication of these drugs which can lead serious vascular disorders. The lower LDL cholesterol level might be due to the higher amounts of lipid consumption in these athletes.

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

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Dai, Mengxi; Liu, Shucong; Zhang, Pengju

2018-01-01

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

Automatic classification of endogenous seismic sources within a landslide body using random forest algorithm

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Provost, Floriane; Hibert, Clément; Malet, Jean-Philippe; Stumpf, André; Doubre, Cécile

2016-04-01

Different studies have shown the presence of microseismic activity in soft-rock landslides. The seismic signals exhibit significantly different features in the time and frequency domains which allow their classification and interpretation. Most of the classes could be associated with different mechanisms of deformation occurring within and at the surface (e.g. rockfall, slide-quake, fissure opening, fluid circulation). However, some signals remain not fully understood and some classes contain few examples that prevent any interpretation. To move toward a more complete interpretation of the links between the dynamics of soft-rock landslides and the physical processes controlling their behaviour, a complete catalog of the endogeneous seismicity is needed. We propose a multi-class detection method based on the random forests algorithm to automatically classify the source of seismic signals. Random forests is a supervised machine learning technique that is based on the computation of a large number of decision trees. The multiple decision trees are constructed from training sets including each of the target classes. In the case of seismic signals, these attributes may encompass spectral features but also waveform characteristics, multi-stations observations and other relevant information. The Random Forest classifier is used because it provides state-of-the-art performance when compared with other machine learning techniques (e.g. SVM, Neural Networks) and requires no fine tuning. Furthermore it is relatively fast, robust, easy to parallelize, and inherently suitable for multi-class problems. In this work, we present the first results of the classification method applied to the seismicity recorded at the Super-Sauze landslide between 2013 and 2015. We selected a dozen of seismic signal features that characterize precisely its spectral content (e.g. central frequency, spectrum width, energy in several frequency bands, spectrogram shape, spectrum local and global maxima

Ethnic-Specific Criteria for Classification of Body Mass Index: A Perspective for Asian Indians and American Diabetes Association Position Statement.

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Misra, Anoop

2015-09-01

Definitions for overweight and obesity are universally applied using body mass index (BMI), based on morbidity and mortality data derived from white populations. However, several studies have shown higher body fat, excess metabolic perturbations, and cardiovascular risk factors at lower value of BMI in Asian versus white populations. Definitive guidelines have been published to classify a BMI of ≥23 kg/m(2) and ≥25 kg/m(2) as overweight and obese, respectively, by the Indian Consensus Group (for Asian Indians residing in India) and a BMI of ≥23 kg/m(2) for screening for diabetes by the National Institute of Health and Care Excellence of the United Kingdom (for migrant south Asians) and, in an encouraging initiative recently (2015), by the American Diabetes Association (for all Asian ethnic groups in the United States). Overall, multiple studies, and now several guidelines, emphasize early intervention with diet and physical activity in Asian ethnic groups for prevention and management of obesity-related noncommunicable diseases. By application of these guidelines, an additional 10-15% of the population in India would be labeled as overweight/obese, and more South Asians/Asians will be diagnosed with diabetes in the United Kingdom and the United States. Additional health resources need to be allocated to deal with increasing numbers of Asians with obesity-related noncommunicable diseases, and research is needed to evolve cost-effective interventions. Finally, consensus based on data is needed so that the World Health Organization and other international agencies could take definitive steps for revision of classification of BMI for Asian populations globally.

Texture classification by texton: statistical versus binary.

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Zhenhua Guo

Full Text Available Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8, image patch (Statistical_Joint and locally invariant fractal (Statistical_Fractal are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor.

CLASSIFICATION AND COMPLEX STATE VALUE OF SHOPPING CENTERS: PROJECT-ORIENTED APPROACH

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Юрій Павлович РАК

2016-02-01

Full Text Available Was done the analysis of projects objects of trade and entertainment centers from the perspective of improving the life safety and is proposed the definition of "Trade and entertainment center", "Trade and entertainment center" and "Complex value of trade and entertainment center." A classification of shopping centers on the classification criteria and the criteria are characterized by increased security status and attractiveness of their operation. The classification of trade and entertainment centers on the criteria of classification features were made. It characterizes the security situation and will increase the attractiveness of their operation. In the nearest future the most secure and modern TEC will be those buildings who will have unique qualities such as safety systems, excellent customer service, and thus by a high level of trust (the client to the mall. The important role will play those TEC, who have clearly formed value oriented project management, including communication values using innovative methods and models. Trade and entertainment centers as an organization are included in the complex process of interaction management. They being both as an enterprise that serves the public and satisfying a great range of his interests and architectural site, which is leased and increases the business attractiveness of the district of TEC location. This duality of the essence of TEC center makes difficult to assess the effectiveness of its security.

Classification of tumor based on magnetic resonance (MR) brain images using wavelet energy feature and neuro-fuzzy model

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Damayanti, A.; Werdiningsih, I.

2018-03-01

The brain is the organ that coordinates all the activities that occur in our bodies. Small abnormalities in the brain will affect body activity. Tumor of the brain is a mass formed a result of cell growth not normal and unbridled in the brain. MRI is a non-invasive medical test that is useful for doctors in diagnosing and treating medical conditions. The process of classification of brain tumor can provide the right decision and correct treatment and right on the process of treatment of brain tumor. In this study, the classification process performed to determine the type of brain tumor disease, namely Alzheimer’s, Glioma, Carcinoma and normal, using energy coefficient and ANFIS. Process stages in the classification of images of MR brain are the extraction of a feature, reduction of a feature, and process of classification. The result of feature extraction is a vector approximation of each wavelet decomposition level. The feature reduction is a process of reducing the feature by using the energy coefficients of the vector approximation. The feature reduction result for energy coefficient of 100 per feature is 1 x 52 pixels. This vector will be the input on the classification using ANFIS with Fuzzy C-Means and FLVQ clustering process and LM back-propagation. Percentage of success rate of MR brain images recognition using ANFIS-FLVQ, ANFIS, and LM back-propagation was obtained at 100%.

Museum as spacecraft: a building in virtual space

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Aguilera, Julieta C.

2014-02-01

This paper presents several immersion and interaction related visualizations that engage visitors in the context of an astronomy museum in order to help them build a mental model of the building as a whole, corresponding to the body of a spacecraft, and its parts considered individually, corresponding to the knowledge articulated from different scales in the Universe. Aspects of embodiment are utilized to find parallels with current trans-disciplinary theoretical developments in media arts.

Accessibility in Public Buildings: : Efficiency of Checklist Protocols

OpenAIRE

Andersson, Jonas E; Skehan, Terry

2016-01-01

In Sweden, governmental agencies and bodies are required to implement a higher level of accessibility in their buildings than that stipulated by the National Building and Planning Act (PBL). The Swedish Agency for Participation (MFD, Myndigheten för delaktighet) develops holistic guidelines in order to conceptualize this higher level of accessibility. In conjunction to these guidelines, various checklist protocols have been produced. The present study focuses on the efficiency of such checkli...

Building a Conceptual Framework: Philosophy, Definitions, and Procedure

OpenAIRE

Yosef Jabareen

2009-01-01

In this paper the author proposes a new qualitative method for building conceptual frameworks for phenomena that are linked to multidisciplinary bodies of knowledge. First, he redefines the key terms of concept, conceptual framework, and conceptual framework analysis. Concept has some components that define it. A conceptual framework is defined as a network or a “plane” of linked concepts. Conceptual framework analysis offers a procedure of theorization for building conceptual frameworks base...

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

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Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Differences in Body Build and Physical Fitness of PE Students from the Faculty of Physical Education and Sport in Biała Podlaska in the Years 1989, 2004, and 2014

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Saczuk Jerzy

2016-12-01

Full Text Available Introduction. In the current situation of the demographic decline and simultaneous tough competition on the educational market, the issues of not only teaching levels but also the competences and aptitudes of students themselves are raised more and more often. Therefore, this study sought to analyse differences in the body build and physical fitness of physical education (PE students from the Faculty of Physical Education and Sport in Biała Podlaska in the years 1989, 2004, and 2014. Material and methods. The material included the results of the anthropometric measurements and physical fitness tests of second-year students examined in 1989 (n = 111, 2004 (n = 181, and 2014 (n = 127. Martin and Saller’s technique was employed to measure anthropometric features necessary to establish body build types using the Heath-Carter method. Physical fitness was evaluated with the International Physical Fitness Test. Sample size (n, arithmetic mean (x̅, standard deviation (SD, and the T point scale were applied to assess the collected variables. Differences in the sizes of the analysed features between the groups were estimated with the use of ANOVA and the Newman-Keuls test. Results. The analysis revealed a constant increase in basic somatic features and endomorphy and a decrease in mesomorphy and physical fitness in male subjects. The ectomorphy of students examined in 2014 was at a level similar to that recorded in 1989. The pace of the described changes was different depending on the study period. Conclusions. Secular trends in body build and physical fitness observed in the study may stem from deterioration in the biological potential of youths or may result from lowering physical education entrance exam criteria at the university.

Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

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Shaodan Li

2017-11-01

Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

Dating ancient Chinese celadon porcelain by neutron activation analysis and bayesian classification

International Nuclear Information System (INIS)

Xie Guoxi; Feng Songlin; Feng Xiangqian; Zhu Jihao; Yan Lingtong; Li Li

2009-01-01

Dating ancient Chinese porcelain is one of the most important and difficult problems in porcelain archaeological field. Eighteen elements in bodies of ancient celadon porcelains fired in Southern Song to Yuan period (AD 1127-1368) and Ming dynasty (AD 1368-1644), including La, Sm, U, Ce, etc., were determined by neutron activation analysis (NAA). After the outliers of experimental data were excluded and multivariate normal distribution was tested, and Bayesian classification was used for dating of 165 ancient celadon porcelain samples. The results show that 98.2% of total ancient celadon porcelain samples are classified correctly. It means that NAA and Bayesian classification are very useful for dating ancient porcelain. (authors)

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

Science.gov (United States)

Weigl, Martin; Wild, Heike

2017-09-15

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

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....

Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial Building Sector to Support Policy and Innovation Planning

Energy Technology Data Exchange (ETDEWEB)

Coffey, Brian; Borgeson, Sam; Selkowitz, Stephen; Apte, Josh; Mathew, Paul; Haves, Philip

2009-07-01

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

Can Automatic Classification Help to Increase Accuracy in Data Collection?

Directory of Open Access Journals (Sweden)

Frederique Lang

2016-09-01

Full Text Available Purpose: The authors aim at testing the performance of a set of machine learning algorithms that could improve the process of data cleaning when building datasets. Design/methodology/approach: The paper is centered on cleaning datasets gathered from publishers and online resources by the use of specific keywords. In this case, we analyzed data from the Web of Science. The accuracy of various forms of automatic classification was tested here in comparison with manual coding in order to determine their usefulness for data collection and cleaning. We assessed the performance of seven supervised classification algorithms (Support Vector Machine (SVM, Scaled Linear Discriminant Analysis, Lasso and elastic-net regularized generalized linear models, Maximum Entropy, Regression Tree, Boosting, and Random Forest and analyzed two properties: accuracy and recall. We assessed not only each algorithm individually, but also their combinations through a voting scheme. We also tested the performance of these algorithms with different sizes of training data. When assessing the performance of different combinations, we used an indicator of coverage to account for the agreement and disagreement on classification between algorithms. Findings: We found that the performance of the algorithms used vary with the size of the sample for training. However, for the classification exercise in this paper the best performing algorithms were SVM and Boosting. The combination of these two algorithms achieved a high agreement on coverage and was highly accurate. This combination performs well with a small training dataset (10%, which may reduce the manual work needed for classification tasks. Research limitations: The dataset gathered has significantly more records related to the topic of interest compared to unrelated topics. This may affect the performance of some algorithms, especially in their identification of unrelated papers. Practical implications: Although the

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....

Body dysmorphic disorder: history and curiosities.

Science.gov (United States)

França, Katlein; Roccia, Maria Grazia; Castillo, David; ALHarbi, Mana; Tchernev, Georgi; Chokoeva, Anastasia; Lotti, Torello; Fioranelli, Massimo

2017-10-01

Body dysmorphic disorder is a chronic psychiatric disorder characterized by excessive preoccupation with an absent or minimal physical deformity. It causes severe distress and impairs normal functioning. In the last centuries, this disorder has been mentioned in the medical literature by important mental health practitioners by different names, such as "dysmorphophobia" or "dermatologic hypochondriasis". However, not until the last century was it included among the obsessive-compulsive disorders, although its classification has changed over time.Patients with body dysmorphic disorder constantly seek cosmetic treatments in order to improve their physical appearance, which more often deteriorates their mental condition. The high prevalence of psychiatric disorders in cosmetic medical practice has led in this field of study to the new science "cosmetic psychodermatology". This paper presents a summary of important facts about body dysmorphic disorder and its description throughout the history of medicine.

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.

Service Level Classification : How IKEA secures availability of the most important articles

OpenAIRE

Edlund Molin, Joanna; Åsell, Elinore

2011-01-01

Purpose - The purpose of this master thesis is to investigate the possibilities to extend or change the base of IKEA’s SL classification and give recommendations concerning potential improvements.  Method - This thesis has an inductive research strategy since data has been collected to build theory rather than the other way around (Bryman and Bell, 2007). The data has been collected by qualitative research, mainly through interviews with employees at the different IKEA organisations. Empirics...

TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

Directory of Open Access Journals (Sweden)

K. Bakuła

2016-06-01

Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and

Vertebral Body Compression Fractures and Bone Density: Automated Detection and Classification on CT Images.

Science.gov (United States)

Burns, Joseph E; Yao, Jianhua; Summers, Ronald M

2017-09-01

Purpose To create and validate a computer system with which to detect, localize, and classify compression fractures and measure bone density of thoracic and lumbar vertebral bodies on computed tomographic (CT) images. Materials and Methods Institutional review board approval was obtained, and informed consent was waived in this HIPAA-compliant retrospective study. A CT study set of 150 patients (mean age, 73 years; age range, 55-96 years; 92 women, 58 men) with (n = 75) and without (n = 75) compression fractures was assembled. All case patients were age and sex matched with control subjects. A total of 210 thoracic and lumbar vertebrae showed compression fractures and were electronically marked and classified by a radiologist. Prototype fully automated spinal segmentation and fracture detection software were then used to analyze the study set. System performance was evaluated with free-response receiver operating characteristic analysis. Results Sensitivity for detection or localization of compression fractures was 95.7% (201 of 210; 95% confidence interval [CI]: 87.0%, 98.9%), with a false-positive rate of 0.29 per patient. Additionally, sensitivity was 98.7% and specificity was 77.3% at case-based receiver operating characteristic curve analysis. Accuracy for classification by Genant type (anterior, middle, or posterior height loss) was 0.95 (107 of 113; 95% CI: 0.89, 0.98), with weighted κ of 0.90 (95% CI: 0.81, 0.99). Accuracy for categorization by Genant height loss grade was 0.68 (77 of 113; 95% CI: 0.59, 0.76), with a weighted κ of 0.59 (95% CI: 0.47, 0.71). The average bone attenuation for T12-L4 vertebrae was 146 HU ± 29 (standard deviation) in case patients and 173 HU ± 42 in control patients; this difference was statistically significant (P high sensitivity and with a low false-positive rate, as well as to calculate vertebral bone density, on CT images. © RSNA, 2017 Online supplemental material is available for this article.

Classification and recognition of the heritage values of the monuments of Tlemcen

Directory of Open Access Journals (Sweden)

Walid Hamma

2017-06-01

Full Text Available The first classification of historic monuments of Tlemcen dates from 1900 and the last from 2010. The 82 monuments date back to the Berber, Muslim and Roman eras. After the independence of Algeria, the French colonial heritage is not concerned by the rankings. They were removed from the list of monuments that was established by the French before 1962. The historic city of Tlemcen dates from the year 201 AD and features many old buildings. The latest ranking list does not reflect the architectural richness of this city. We then asked about the possibility of classifying the other historic buildings. From this questioning, we first identified all cultural goods which could be classified. Then we have evaluated these buildings following a grid of 20 heritage values. They are mentioned in the national and international legislation. It turns out that only 1.57 % of monuments of this city are classified.

Classification and methodical features of fitness and wellness facilities

Directory of Open Access Journals (Sweden)

Yu. I. Beliak

2014-11-01

Full Text Available Purpose : health and fitness use a large arsenal of different sports and physical activity. Development of fitness industry promotes its expansion and requires classification and methodological features that lead to the use of appropriate fitness programs. Material : more than 60 literature and video of 42 prestigious international fitness - conventions lessons were analyzed. Results : the evolution of species fitness and wellness, as well as the character used in those funds. Conclusions : as a means of improving classification attribute fitness appropriate to use their orientation, according to which they are divided into aerobic, strength exercises that promote flexibility and psychomotor coordination. The main methodological features fitness facilities are highlighted: the variety and interchangeability, clear regulation, the ability to transform, to exercise a selective effect on the body, the ability to solve a wide range of tasks, innovation.

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

Intended Use of a Building in Terms of Updating the Cadastral Database and Harmonizing the Data with other Public Records

Directory of Open Access Journals (Sweden)

Buśko Małgorzata

2017-06-01

Full Text Available According to the original wording of the Regulation on the register of land and buildings of 2001, in the real estate cadastre there was one attribute associated with the use of a building structure - its intended use, which was applicable until the amendment to the Regulation was introduced in 2013. Then, additional attributes were added, i.e. the type of the building according to the Classification of Fixed Assets (KST, the class of the building according to the Polish Classification of Types of Constructions (PKOB and, at the same time, the main functional use and other functions of the building remained in the Regulation as well. The record data on buildings are captured for the real estate cadastre from other data sets, for example those maintained by architectural and construction authorities. At the same time, the data contained in the cadastre, after they have been entered or changed in the database, are transferred to other registers, such as tax records, or land and mortgage court registers. This study is the result of the analysis of the laws applicable to the specific units and registers. A list of discrepancies in the attributes occurring in the different registers was prepared. The practical part of the study paid particular attention to the legal bases and procedures for entering the function of a building in the real estate cadastre, which is extremely significant, as it is the attribute determining the property tax basis.

Intended Use of a Building in Terms of Updating the Cadastral Database and Harmonizing the Data with other Public Records

Science.gov (United States)

Buśko, Małgorzata

2017-06-01

According to the original wording of the Regulation on the register of land and buildings of 2001, in the real estate cadastre there was one attribute associated with the use of a building structure - its intended use, which was applicable until the amendment to the Regulation was introduced in 2013. Then, additional attributes were added, i.e. the type of the building according to the Classification of Fixed Assets (KST), the class of the building according to the Polish Classification of Types of Constructions (PKOB) and, at the same time, the main functional use and other functions of the building remained in the Regulation as well. The record data on buildings are captured for the real estate cadastre from other data sets, for example those maintained by architectural and construction authorities. At the same time, the data contained in the cadastre, after they have been entered or changed in the database, are transferred to other registers, such as tax records, or land and mortgage court registers. This study is the result of the analysis of the laws applicable to the specific units and registers. A list of discrepancies in the attributes occurring in the different registers was prepared. The practical part of the study paid particular attention to the legal bases and procedures for entering the function of a building in the real estate cadastre, which is extremely significant, as it is the attribute determining the property tax basis.

Contextually guided very-high-resolution imagery classification with semantic segments

Science.gov (United States)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

BUILDING FAÇADE SEPARATION IN VERTICAL AERIAL IMAGES

Directory of Open Access Journals (Sweden)

P. Meixner

2012-07-01

Full Text Available Three-dimensional models of urban environments have great appeal and offer promises of interesting applications. While initially it was of interest to just have such 3D data, it increasingly becomes evident that one really would like to have interpreted urban objects. To be able to interpret buildings we have to split a visible whole building block into its different single buildings. Usually this is done using cadastral information to divide the single land parcels. The problem in this case is that sometimes the building boundaries derived from the cadastre are insufficiently accurate due to several reasons like old databases with lower accuracies or inaccuracies due to transformation between two coordinate systems. For this reason it can happen that a cadastral boundary coming from an old map is displaced by up to several meters and therefore divides two buildings incorrectly. To overcome such problems we incorporate the information from vertical aerial images. We introduce a façade separation method that is able to find individual building façades using multi view stereo. The purpose is to identify the individual façades and separate them from one another before on proceeds with the analysis of a façade's details. The source was a set of overlapping, thus "redundant" vertical aerial images taken by an UltraCam digital aerial camera. Therefore in a first step we determine the building block outlines using the building classification and use the height values from the Digital Surface Model (DSM to determine approximate "façade quadrilaterals". We also incorporate height discontinuities using the height profiles along the building outlines to enhance our façade separation. In a next step we detect repeated pattern in these "façade images" and use them to separate the façades respectively building blocks from one another. We show that this method can be successfully used to separate building façades using vertical aerial images with a

Earthquake Building Damage Mapping Based on Feature Analyzing Method from Synthetic Aperture Radar Data

Science.gov (United States)

An, L.; Zhang, J.; Gong, L.

2018-04-01

Playing an important role in gathering information of social infrastructure damage, Synthetic Aperture Radar (SAR) remote sensing is a useful tool for monitoring earthquake disasters. With the wide application of this technique, a standard method, comparing post-seismic to pre-seismic data, become common. However, multi-temporal SAR processes, are not always achievable. To develop a post-seismic data only method for building damage detection, is of great importance. In this paper, the authors are now initiating experimental investigation to establish an object-based feature analysing classification method for building damage recognition.

Excessive bodybuilding as pathology? A first neurophysiological classification.

Science.gov (United States)

Maier, Moritz Julian; Haeussinger, Florian Benedikt; Hautzinger, Martin; Fallgatter, Andreas Jochen; Ehlis, Ann-Christine

2017-11-15

Excessive bodybuilding as a pathological syndrome has been classified based on two different theories: bodybuilding as dependency or as muscle dysmorphic disorder (MDD). This study is a first attempt to find psychophysiological data supporting one of these classifications. Twenty-four participants (bodybuilders vs healthy controls) were presented with pictures of bodies, exercise equipment or general reward stimuli in a control or experimental condition, and were measured with functional near-infrared spectroscopy (fNIRS). Higher activation in the dorsolateral prefrontal cortex (DLPFC) and the orbitofrontal cortex (OFC) while watching bodies and training equipment in the experimental condition (muscular bodies and bodybuilding-typical equipment) would be an indicator for the addiction theory. Higher activation in motion-related areas would be an indicator for the MDD theory. We found no task-related differences between the groups in the DLPFC and OFC, but a significantly higher activation in bodybuilders in the primary somatosensory cortex (PSC) and left-hemispheric supplementary motor area (SMA) while watching body pictures (across conditions) as compared to the control group. These neurophysiological results could be interpreted as a first evidence for the MDD theory of excessive bodybuilding.

Thermal Comfort in a Naturally-Ventilated Educational Building

Directory of Open Access Journals (Sweden)

David Mwale Ogoli

2012-11-01

Full Text Available A comprehensive study of thermal comfort in a naturally ventilated education building (88,000 ft2 in a Chicago suburb will be conducted with 120 student subjects in 2007. This paper discusses some recent trends in worldwide thermal comfort studies and presents a proposal of research for this building through a series of questionnaire tables. Two research methods used inthermal comfort studies are field studies and laboratory experiments in climate-chambers. The various elements that constitute a “comfortable” thermal environment include physical factors (ambient air temperature, mean radiant temperature, air movement and humidity, personal factors(activity and clothing, classifications (gender, age, education, etc. and psychological expectations (knowledge, experience, psychological effect of visual warmth by, say, a fireplace. Comparisons are made using data gathered from Nairobi, Kenya.Keywords: Comfort, temperature, humidity and ventilation

Damping in building structures during earthquakes: test data and modeling

International Nuclear Information System (INIS)

Coats, D.W. Jr.

1982-01-01

A review and evaluation of the state-of-the-art of damping in building structures during earthquakes is presented. The primary emphasis is in the following areas: 1) the evaluation of commonly used mathematical techniques for incorporating damping effects in both simple and complex systems; 2) a compilation and interpretation of damping test data; and 3) an evaluation of structure testing methods, building instrumentation practices, and an investigation of rigid-body rotation effects on damping values from test data. A literature review provided the basis for evaluating mathematical techiques used to incorporate earthquake induced damping effects in simple and complex systems. A discussion on the effectiveness of damping, as a function of excitation type, is also included. Test data, from a wide range of sources, has been compiled and interpreted for buidings, nuclear power plant structures, piping, equipment, and isolated structural elements. Test methods used to determine damping and frequency parameters are discussed. In particular, the advantages and disadvantages associated with the normal mode and transfer function approaches are evaluated. Additionally, the effect of rigid-body rotations on damping values deduced from strong-motion building response records is investigated. A discussion of identification techniques typically used to determine building parameters (frequency and damping) from strong motion records is included. Finally, an analytical demonstration problem is presented to quantify the potential error in predicting fixed-base structural frequency and damping values from strong motion records, when rigid-body rotations are not properly accounted for

ROOF TYPE SELECTION BASED ON PATCH-BASED CLASSIFICATION USING DEEP LEARNING FOR HIGH RESOLUTION SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

T. Partovi

2017-05-01

Full Text Available 3D building reconstruction from remote sensing image data from satellites is still an active research topic and very valuable for 3D city modelling. The roof model is the most important component to reconstruct the Level of Details 2 (LoD2 for a building in 3D modelling. While the general solution for roof modelling relies on the detailed cues (such as lines, corners and planes extracted from a Digital Surface Model (DSM, the correct detection of the roof type and its modelling can fail due to low quality of the DSM generated by dense stereo matching. To reduce dependencies of roof modelling on DSMs, the pansharpened satellite images as a rich resource of information are used in addition. In this paper, two strategies are employed for roof type classification. In the first one, building roof types are classified in a state-of-the-art supervised pre-trained convolutional neural network (CNN framework. In the second strategy, deep features from deep layers of different pre-trained CNN model are extracted and then an RBF kernel using SVM is employed to classify the building roof type. Based on roof complexity of the scene, a roof library including seven types of roofs is defined. A new semi-automatic method is proposed to generate training and test patches of each roof type in the library. Using the pre-trained CNN model does not only decrease the computation time for training significantly but also increases the classification accuracy.

Evaluation of the body bearing of high performance female volleyball players

Directory of Open Access Journals (Sweden)

Stech M.

2010-09-01

Full Text Available In the present paper the results of the study of body bearing in 12 high performance female volleyball players of polish team (TPS Rumia are presented. To estimate body bearing the New-York's test of the body bearing classification was used. The results of the study have shown that asymmetrical positions of volleyball players in the time of services and attacks are contributed to formed some asymmetrical disturbances of body bearing. At the majority of sportsmen it is exhibited in omitting the left brachium and the left blade, in a right-hand scoliosis, in the tendency to a platypodia. It requires use of special preventive and adjusting exercises.

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

Science.gov (United States)

Khaira Batubara, Dina; Arif Bijaksana, Moch; Adiwijaya

2018-03-01

Research on the semantic argument classification requires semantically labeled data in large numbers, called corpus. Because building a corpus is costly and time-consuming, recently many studies have used existing corpus as the training data to conduct semantic argument classification research on new domain. But previous studies have proven that there is a significant decrease in performance when classifying semantic arguments on different domain between the training and the testing data. The main problem is when there is a new argument that found in the testing data but it is not found in the training data. This research carries on semantic argument classification on a new domain that is Quran English Translation by utilizing Propbank corpus as the training data. To recognize the new argument in the training data, this research proposes four new features for extending the argument features in the training data. By using SVM Linear, the experiment has proven that augmenting the proposed features to the baseline system with some combinations option improve the performance of semantic argument classification on Quran data using Propbank Corpus as training data.

Conceptual-driven classification for coding advise in health insurance reimbursement.

Science.gov (United States)

Li, Sheng-Tun; Chen, Chih-Chuan; Huang, Fernando

2011-01-01

With the non-stop increases in medical treatment fees, the economic survival of a hospital in Taiwan relies on the reimbursements received from the Bureau of National Health Insurance, which in turn depend on the accuracy and completeness of the content of the discharge summaries as well as the correctness of their International Classification of Diseases (ICD) codes. The purpose of this research is to enforce the entire disease classification framework by supporting disease classification specialists in the coding process. This study developed an ICD code advisory system (ICD-AS) that performed knowledge discovery from discharge summaries and suggested ICD codes. Natural language processing and information retrieval techniques based on Zipf's Law were applied to process the content of discharge summaries, and fuzzy formal concept analysis was used to analyze and represent the relationships between the medical terms identified by MeSH. In addition, a certainty factor used as reference during the coding process was calculated to account for uncertainty and strengthen the credibility of the outcome. Two sets of 360 and 2579 textual discharge summaries of patients suffering from cerebrovascular disease was processed to build up ICD-AS and to evaluate the prediction performance. A number of experiments were conducted to investigate the impact of system parameters on accuracy and compare the proposed model to traditional classification techniques including linear-kernel support vector machines. The comparison results showed that the proposed system achieves the better overall performance in terms of several measures. In addition, some useful implication rules were obtained, which improve comprehension of the field of cerebrovascular disease and give insights to the relationships between relevant medical terms. Our system contributes valuable guidance to disease classification specialists in the process of coding discharge summaries, which consequently brings benefits in

Spectral-spatial classification of hyperspectral image using three-dimensional convolution network

Science.gov (United States)

Liu, Bing; Yu, Xuchu; Zhang, Pengqiang; Tan, Xiong; Wang, Ruirui; Zhi, Lu

2018-01-01

Recently, hyperspectral image (HSI) classification has become a focus of research. However, the complex structure of an HSI makes feature extraction difficult to achieve. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. The design of an improved 3-D convolutional neural network (3D-CNN) model for HSI classification is described. This model extracts features from both the spectral and spatial dimensions through the application of 3-D convolutions, thereby capturing the important discrimination information encoded in multiple adjacent bands. The designed model views the HSI cube data altogether without relying on any pre- or postprocessing. In addition, the model is trained in an end-to-end fashion without any handcrafted features. The designed model was applied to three widely used HSI datasets. The experimental results demonstrate that the 3D-CNN-based method outperforms conventional methods even with limited labeled training samples.

Cardiovascular manifestations of anabolic steroids in association with demographic variables in body building athletes

Directory of Open Access Journals (Sweden)

Farzad Gheshlaghi

2015-01-01

Full Text Available Background: The most common drug abuse among athletes is anabolic steroids which lead to the development of cardiovascular diseases and sudden death. Thus, the aim of this study was to evaluate cardiovascular outcomes of anabolic consumption in body building athletes. Materials and Methods: Totally, 267 male athletes at the range of 20-45 years old with the regular consumption of anabolic steroids for >2 months with at least once weekly. High-density lipoprotein (HDL, low-density lipoprotein (LDL, triglyceride (TG, and hematocrit (Hct levels were measured after 10 h of fasting. Data analysis was performed using K2, t-test, ANOVA and correlation coefficient through SPSS 17. Results: There was a nonsignificant difference between groups regarding HDL, TG, and total cholesterol. There was a significant decrease in the total and categorized LDL and Hct levels in consumers of anabolic steroid versus nonusers (P = 0.01 and P = 0.041, respectively. Results showed a significant increase in systolic and diastolic blood pressure (SBP and DBP in anabolic steroid users which associates with duration of abuse (P = 0.02 and P = 0.03, respectively. No significant electrocardiography changes were found within the follow-up period. Conclusion: Increase in SBP or DBP is a common complication of these drugs which can lead serious vascular disorders. The lower LDL cholesterol level might be due to the higher amounts of lipid consumption in these athletes.

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.

The classification, recording, databasing and use of information about building damage caused by subsidence and landslides

OpenAIRE

Cooper, Anthony

2008-01-01

Building damage as a result of subsidence and lateral movement can be caused by numerous mechanisms including mining, dissolution of soluble rocks, shrink–swell of clays and landslides. In many instances, the distribution and severity of the damage caused can be diagnostic of the underlying geological condition and can be used as an aid to geological and geomorphological mapping. Many rigid buildings are sensitive to movement, meaning that careful surveys can delineate fine details that can b...

An investigation on the assessed thermal sensation and human body exergy consumption rate

DEFF Research Database (Denmark)

Simone, Angela; Kolarik, Jakub; Iwamatsu, Toshiya

2010-01-01

perception of the indoor environment is rare. As the building should provide healthy and comfortable environment for its occupants, it is reasonable to consider both the exergy flows in the building and within the human body. A relatively new approach of the relation between the exergy concept and the built......-environment research has been explored in the present work. The relationship of subjectively assessed thermal sensation data, from earlier thermal comfort studies, to the calculated human-body exergy consumption has been analysed. The results show that the minimum human body exergy consumption rate was related......The exergy concept helps to optimize indoor climate conditioning systems to meet the requirements of sustainable building design. While the exergy approach to design and operation of indoor climate conditioning systems is relatively well established, its exploitation in connection to human...

Empirical evaluation of data normalization methods for molecular classification.

Science.gov (United States)

Huang, Huei-Chung; Qin, Li-Xuan

2018-01-01

Data artifacts due to variations in experimental handling are ubiquitous in microarray studies, and they can lead to biased and irreproducible findings. A popular approach to correct for such artifacts is through post hoc data adjustment such as data normalization. Statistical methods for data normalization have been developed and evaluated primarily for the discovery of individual molecular biomarkers. Their performance has rarely been studied for the development of multi-marker molecular classifiers-an increasingly important application of microarrays in the era of personalized medicine. In this study, we set out to evaluate the performance of three commonly used methods for data normalization in the context of molecular classification, using extensive simulations based on re-sampling from a unique pair of microRNA microarray datasets for the same set of samples. The data and code for our simulations are freely available as R packages at GitHub. In the presence of confounding handling effects, all three normalization methods tended to improve the accuracy of the classifier when evaluated in an independent test data. The level of improvement and the relative performance among the normalization methods depended on the relative level of molecular signal, the distributional pattern of handling effects (e.g., location shift vs scale change), and the statistical method used for building the classifier. In addition, cross-validation was associated with biased estimation of classification accuracy in the over-optimistic direction for all three normalization methods. Normalization may improve the accuracy of molecular classification for data with confounding handling effects; however, it cannot circumvent the over-optimistic findings associated with cross-validation for assessing classification accuracy.

The Building Act 1984. The Building Regulations 1991; BR 211; Radon; guidance on protective measures for new dwellings, 1999 edition

International Nuclear Information System (INIS)

1999-01-01

This guidance is the 1999 edition of BR 211, Radon: guidance on protective measures for new dwellings, which was published on 11 November 1999. The guidance in the 1999 edition of BR 211 should be considered to apply to any building or building work for which a building notice, initial notice, amendment notice or public body's notice is given to a local authority, or full plans are deposited with a local authority on or after 14 February 2000. Where an amendment notice is given on or after 14 February 2000 relating to an initial notice given before that date, only new work added to the initial notice will be formally subject to the 1999 edition of BR 211

Effect of body fat and gender on body temperature distribution.

Science.gov (United States)

Neves, Eduardo Borba; Salamunes, Ana Carla Chierighini; de Oliveira, Rafael Melo; Stadnik, Adriana Maria Wan

2017-12-01

It is well known that body composition can influence peripheral heat loss and skin temperature. That the distribution of body fat is affected by gender is well known; however, there is little information on how body composition and gender influences the measure of skin temperature. This study evaluated skin temperature distribution according to body fat percentage (BF%) and gender. A sample of 94 apparently healthy volunteers (47 women and 47 men) was assessed with Dual-Energy X-Ray Absorptiometry (DXA) and infrared thermography (mean, maximum and minimum temperatures - T Mean , T Max and T Min ). The sample was divided into groups, according to health risk classification, based on BF%, as proposed by the American College of Sports Medicine: Average (n = 58), Elevated (n = 16) or High (n = 20). Women had lower T Mean in most regions of interest (ROI). In both genders, group High had lower temperature values than Average and Elevated in the trunk, upper and lower limbs. In men, palms and posterior hands had a tendency (p temperature along with increased BF%. T Mean , T Max and T Min of trunk, upper and lower limbs were negatively correlated with BF% and the fat percentage of each segment (upper limbs, lower limbs and trunk). The highest correlations found in women were between posterior trunk and BF% (rho = -0.564, p temperature than men, which was related with higher BF%. Facial temperature seems not to be influenced by body fat. With the future collection of data on the relationship between BF% and skin temperature while taking into account factors such as body morphology, gender, and ethnicity, we conclude that measurement of BF may be reliably estimated with the use of thermal imaging technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

Radiation Detection and Classification of Heavy Oxide Inorganic Scintillator Crystals for Detection of Fast Neutrons

Science.gov (United States)

2016-06-01

response, diffuse source, collimated source 15. NUMBER OF PAGES 101 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18...protecting the homeland, building security globally, and projecting power and winning decisively [1]. Nuclear material detection is embedded in two...detection. According to Glasstone and Dolan [4] as well as numerous other experts, there are fundamentally three isotopes that could practically be used

Effects of the exposure to self- and other-referential bodies on state body image and negative affect in resistance-trained men.

Science.gov (United States)

Cordes, Martin; Vocks, Silja; Düsing, Rainer; Waldorf, Manuel

2017-06-01

Previous body image research suggests that first, exposure to body stimuli can negatively affect men's body satisfaction and second, body concerns are associated with dysfunctional gaze behavior. To date, however, the effects of self- vs. other-referential body stimuli and of gaze behavior on body image in men under exposure conditions have not been investigated. Therefore, 49 weight-trained men were presented with pictures of their own and other bodies of different builds (i.e., normal, muscular, hyper-muscular) while being eye-tracked. Participants completed pre- and post-exposure measures of body image and affect. Results indicated that one's own and the muscular body negatively affected men's body image to a comparable degree. Exposure to one's own body also led to increased negative affect. Increased attention toward disliked own body parts was associated with a more negative post-exposure body image and affect. These results suggest a crucial role of critical self-examination in maintaining body dissatisfaction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Retrieval and classification of food images.

Science.gov (United States)

Farinella, Giovanni Maria; Allegra, Dario; Moltisanti, Marco; Stanco, Filippo; Battiato, Sebastiano

2016-10-01

Automatic food understanding from images is an interesting challenge with applications in different domains. In particular, food intake monitoring is becoming more and more important because of the key role that it plays in health and market economies. In this paper, we address the study of food image processing from the perspective of Computer Vision. As first contribution we present a survey of the studies in the context of food image processing from the early attempts to the current state-of-the-art methods. Since retrieval and classification engines able to work on food images are required to build automatic systems for diet monitoring (e.g., to be embedded in wearable cameras), we focus our attention on the aspect of the representation of the food images because it plays a fundamental role in the understanding engines. The food retrieval and classification is a challenging task since the food presents high variableness and an intrinsic deformability. To properly study the peculiarities of different image representations we propose the UNICT-FD1200 dataset. It was composed of 4754 food images of 1200 distinct dishes acquired during real meals. Each food plate is acquired multiple times and the overall dataset presents both geometric and photometric variabilities. The images of the dataset have been manually labeled considering 8 categories: Appetizer, Main Course, Second Course, Single Course, Side Dish, Dessert, Breakfast, Fruit. We have performed tests employing different representations of the state-of-the-art to assess the related performances on the UNICT-FD1200 dataset. Finally, we propose a new representation based on the perceptual concept of Anti-Textons which is able to encode spatial information between Textons outperforming other representations in the context of food retrieval and Classification. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interactive classification and content-based retrieval of tissue images

Science.gov (United States)

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

2002-11-01

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

Fuzzy Multicriteria ABC Supplier Classification in Global Supply Chain

Directory of Open Access Journals (Sweden)

Petar Kefer

2016-01-01

Full Text Available The determination of the optimal purchasing strategy in enterprise that is a part of global supply chain could be performed in two steps. In step one, a classification of potential suppliers is performed in order to determine the optimal portfolio of suppliers. This is delivered by using the fuzzy multicriteria proposed ABC classification method. Uncertainties in relative importance of criteria and their values are described by linguistic expressions. Modelling of linguistic expressions is based on the fuzzy sets theory. In the second step, ranking of optimal portfolio of suppliers is performed by using the modified ELECTRE method. The obtained results represent valuable input for determining the long time purchasing strategy and building partnership with the best suppliers. The developed two-step model is verified on real life data. The obtained results indicate good compliance with the opinions management in this type of industry. It is worth to mention that the proposed model can be easily extended and adopted to the analysis of other issues of management which could be applicable in different research areas.

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

Soil classification basing on the spectral characteristics of topsoil samples

Science.gov (United States)

Liu, Huanjun; Zhang, Xiaokang; Zhang, Xinle

2016-04-01

Soil taxonomy plays an important role in soil utility and management, but China has only course soil map created based on 1980s data. New technology, e.g. spectroscopy, could simplify soil classification. The study try to classify soils basing on the spectral characteristics of topsoil samples. 148 topsoil samples of typical soils, including Black soil, Chernozem, Blown soil and Meadow soil, were collected from Songnen plain, Northeast China, and the room spectral reflectance in the visible and near infrared region (400-2500 nm) were processed with weighted moving average, resampling technique, and continuum removal. Spectral indices were extracted from soil spectral characteristics, including the second absorption positions of spectral curve, the first absorption vale's area, and slope of spectral curve at 500-600 nm and 1340-1360 nm. Then K-means clustering and decision tree were used respectively to build soil classification model. The results indicated that 1) the second absorption positions of Black soil and Chernozem were located at 610 nm and 650 nm respectively; 2) the spectral curve of the meadow is similar to its adjacent soil, which could be due to soil erosion; 3) decision tree model showed higher classification accuracy, and accuracy of Black soil, Chernozem, Blown soil and Meadow are 100%, 88%, 97%, 50% respectively, and the accuracy of Blown soil could be increased to 100% by adding one more spectral index (the first two vole's area) to the model, which showed that the model could be used for soil classification and soil map in near future.

Ichthyoplankton Classification Tool using Generative Adversarial Networks and Transfer Learning

KAUST Repository

Aljaafari, Nura

2018-04-15

The study and the analysis of marine ecosystems is a significant part of the marine science research. These systems are valuable resources for fisheries, improving water quality and can even be used in drugs production. The investigation of ichthyoplankton inhabiting these ecosystems is also an important research field. Ichthyoplankton are fish in their early stages of life. In this stage, the fish have relatively similar shape and are small in size. The currently used way of identifying them is not optimal. Marine scientists typically study such organisms by sending a team that collects samples from the sea which is then taken to the lab for further investigation. These samples need to be studied by an expert and usually end needing a DNA sequencing. This method is time-consuming and requires a high level of experience. The recent advances in AI have helped to solve and automate several difficult tasks which motivated us to develop a classification tool for ichthyoplankton. We show that using machine learning techniques, such as generative adversarial networks combined with transfer learning solves such a problem with high accuracy. We show that using traditional machine learning algorithms fails to solve it. We also give a general framework for creating a classification tool when the dataset used for training is a limited dataset. We aim to build a user-friendly tool that can be used by any user for the classification task and we aim to give a guide to the researchers so that they can follow in creating a classification tool.

VARIANT FOR CONSTRUCTION, REPAIR OR RECONSTRUCTION OF BUILDING

Directory of Open Access Journals (Sweden)

S. N. Osipov

2016-01-01

Full Text Available In the XXI century moral depreciation concept comprises not only deterioration of outside appearance of construction elements in the course of time but accelerated fashion changes in respect of interior design and rapid increase in technical level for residence buildings. For this reason if average rate of building dilapidation in the buildings of series 1–335, 1–335А and 1–464А constructed in Minsk within the period of 1957–1975 and being operated till 2005–2006 has constituted 25–29 % and their moral depreciation has been equal to more than 40 % then rate of the moral depreciation has significantly increased in the XXI century. Such situation requires execution of special investigations. High operating rates of refinancing have led to the necessity for record keeping of initial expenses and repairability levels because selection of building construction, repair or reconstruction variant depends on these parameters. Repairability classification of main elements of residence buildings and premises has been proposed for regulation of such selection procedure. In this case it is recommended to take into account technological effectiveness of repair and technical service, verifiability, accessibility, easy dismountability, substitutability and interchangeability of construction elements and technical devices. The paper presents nomograms that permit to make easier practical calculations on determination of cost-efficient time period for operation of the element prior to its substitution at various refinancing rates and also for comparison of relative initial expenses according to time service. 

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

Science.gov (United States)

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

2007-01-01

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

Dentistry and Ayurveda - IV: Classification and management of common oral diseases

Directory of Open Access Journals (Sweden)

Amruthesh Sunita

2008-01-01

Full Text Available This article, the fourth in the series titled ′Dentistry and Ayurveda,′ describes in brief the panchakarma therapy, which is a distinctive feature of the Ayurvedic method of detoxifying the body. The various therapies and medicines used in Ayurveda have been elaborated. Further, an attempt has been made to correlate dental diseases in Ayurveda with the modern-day classification, clinical features, and management.

How to Build an Embodiment Lab: Achieving Body Representation Illusions in Virtual Reality

Directory of Open Access Journals (Sweden)

Bernhard eSpanlang

2014-11-01

Full Text Available Advances in computer graphics algorithms and virtual reality (VR systems, together with the reduction in cost of associated equipment, have led scientists to consider VR as a useful tool for conducting experimental studies in fields such as neuroscience and experimental psychology. In particular virtual body ownership, where the feeling of ownership over a virtual body is elicited in the participant, has become a useful tool in the study of body representation, in cognitive neuroscience and psychology, concerned with how the brain represents the body. Although VR has been shown to be a useful tool for exploring body ownership illusions, integrating the various technologies necessary for such a system can be daunting. In this paper we discuss the technical infrastructure necessary to achieve virtual embodiment. We describe a basic VR system and how it may be used for this purpose, and then extend this system with the introduction of real-time motion capture, a simple haptics system and the integration of physiological and brain electrical activity recordings.

Classification of Targets and Distractors Present in Visual Hemifields Using Time-Frequency Domain EEG Features

Directory of Open Access Journals (Sweden)

Sweeti

2018-01-01

Full Text Available This paper presents a classification system to classify the cognitive load corresponding to targets and distractors present in opposite visual hemifields. The approach includes the study of EEG (electroencephalogram signal features acquired in a spatial attention task. The process comprises of EEG feature selection based on the feature distribution, followed by the stepwise discriminant analysis- (SDA- based channel selection. Repeated measure analysis of variance (rANOVA is applied to test the statistical significance of the selected features. Classifiers are developed and compared using the selected features to classify the target and distractor present in visual hemifields. The results provide a maximum classification accuracy of 87.2% and 86.1% and an average classification accuracy of 76.5 ± 4% and 76.2 ± 5.3% over the thirteen subjects corresponding to the two task conditions. These correlates present a step towards building a feature-based neurofeedback system for visual attention.

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

Science.gov (United States)

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

2013-10-04

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

Measuring of the moisture content in brick walls of historical buildings - the overview of methods

Science.gov (United States)

Hola, A.

2017-10-01

The paper deals with the issue of measuring the moisture content of brick walls in buildings of high historical value. It includes a classification of known methods used to measure the moisture content and their valorisation with regards to the legitimacy of using them in historical buildings. Moreover, the most important considerations for conducting such measurements are also described, which include the choice of an appropriate method for a specific situation, the determination of a correlative or hypothetical dependency for equipment used in tests and also the method of distributing measurement points.

A COMPARISON STUDY OF DIFFERENT MARKER SELECTION METHODS FOR SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES

Directory of Open Access Journals (Sweden)

D. Akbari

2015-12-01

Full Text Available An effective approach based on the Minimum Spanning Forest (MSF, grown from automatically selected markers using Support Vector Machines (SVM, has been proposed for spectral-spatial classification of hyperspectral images by Tarabalka et al. This paper aims at improving this approach by using image segmentation to integrate the spatial information into marker selection process. In this study, the markers are extracted from the classification maps, obtained by both SVM and segmentation algorithms, and then are used to build the MSF. The segmentation algorithms are the watershed, expectation maximization (EM and hierarchical clustering. These algorithms are used in parallel and independently to segment the image. Moreover, the pixels of each class, with the largest population in the classification map, are kept for each region of the segmentation map. Lastly, the most reliable classified pixels are chosen from among the exiting pixels as markers. Two benchmark urban hyperspectral datasets are used for evaluation: Washington DC Mall and Berlin. The results of our experiments indicate that, compared to the original MSF approach, the marker selection using segmentation algorithms leads in more accurate classification maps.

The environmental perspective in the territorial classification

International Nuclear Information System (INIS)

Leyva Franco, Pablo

1998-01-01

The article is about the environmental aspects in the territorial classification, of the constitutional structure and its reaches, of the precision in the approaches and procedures and of the law 388 of 1997 it understands each other for the environmental thing the relationship between the systems and natural processes and the systems and social, economic and cultural processes; this way the environmental thing transcends the ecological thing and the geographical thing to become a new dimension of the science, of the knowledge and of the culture. The environmental thing also acquires a particular concretion when serving like basic instrument for the interpretation of the necessities of the society and in the way of satisfying them without damage of the natural thing and territorial classification as the process of reflection of a society on the form of occupying the space, of taking advantage of the natural resources, of building establishments, of establishing an infrastructure and of managing the relationships and the economic flows, to obtain a disposition and space arrangements of their activities finally, in harmony with the nature that they correspond to their culture and the form like it wants to maintain or to improve their quality of life in a sustainable way

Consideration of the Construction Code for TBM-body in ASME BPVC

International Nuclear Information System (INIS)

Kim, Dongjun; Kim, Yunjae; Kim, Suk Kwon; Park, Sung Dae; Lee, Dong Won

2016-01-01

In this paper, ASME code is briefly introduced, and the TBM-body is classified for selecting the ASME section. With the classification of TBM-body, the appropriate section is determined. Helium Cooled Ceramic Reflector (HCCR) Test Blanket System (TBS) has been designed to research on the functions of breeding blanket by KO TBM team. The functions has three subjects as 1) Tritium breeding, 2) Heat conversion and extraction, and 3) Neutron and Gamma-ray shielding. For the process of design, it is needed to select the appropriate construction code as the design criteria. ITER Organization (IO) has proposed that RCC-MR Edition 2007 ver. shall be used for TBM-shield. Because the TBM-shield is connected to the vacuum boundary. For the other part of TBM-set, TBM-body, there is no constraint on the selected code, and the manufacturer can appropriately select the construction code to apply design and fabrication parts. KO TBM Team has considered whether it is appropriate to choose any code for TBM-body. One of the things is ASME code. The advantage of ASME choice is suitable to the domestic status. In the domestic nuclear plant, ASME or KEPIC code is used as regulatory requirements. Based on this, it is possible to prepare a domestic fusion plant regulatory. In this paper, the construction code of TBM-body was determined in ASME BPVC. For the determination of code, the structure of ASME BPVC was introduced and the classification for TBM-body was conducted by the ITER criteria. And the operation conditions of TBM-body that contained creep and irradiation effects was considered to determine the construction code

Consideration of the Construction Code for TBM-body in ASME BPVC

Energy Technology Data Exchange (ETDEWEB)

Kim, Dongjun; Kim, Yunjae [Korea Univ., Seoul (Korea, Republic of); Kim, Suk Kwon; Park, Sung Dae; Lee, Dong Won [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

In this paper, ASME code is briefly introduced, and the TBM-body is classified for selecting the ASME section. With the classification of TBM-body, the appropriate section is determined. Helium Cooled Ceramic Reflector (HCCR) Test Blanket System (TBS) has been designed to research on the functions of breeding blanket by KO TBM team. The functions has three subjects as 1) Tritium breeding, 2) Heat conversion and extraction, and 3) Neutron and Gamma-ray shielding. For the process of design, it is needed to select the appropriate construction code as the design criteria. ITER Organization (IO) has proposed that RCC-MR Edition 2007 ver. shall be used for TBM-shield. Because the TBM-shield is connected to the vacuum boundary. For the other part of TBM-set, TBM-body, there is no constraint on the selected code, and the manufacturer can appropriately select the construction code to apply design and fabrication parts. KO TBM Team has considered whether it is appropriate to choose any code for TBM-body. One of the things is ASME code. The advantage of ASME choice is suitable to the domestic status. In the domestic nuclear plant, ASME or KEPIC code is used as regulatory requirements. Based on this, it is possible to prepare a domestic fusion plant regulatory. In this paper, the construction code of TBM-body was determined in ASME BPVC. For the determination of code, the structure of ASME BPVC was introduced and the classification for TBM-body was conducted by the ITER criteria. And the operation conditions of TBM-body that contained creep and irradiation effects was considered to determine the construction code.

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.

Talar Fractures and Dislocations: A Radiologist's Guide to Timely Diagnosis and Classification.

Science.gov (United States)

Melenevsky, Yulia; Mackey, Robert A; Abrahams, R Brad; Thomson, Norman B

2015-01-01

The talus, the second largest tarsal bone, has distinctive imaging characteristics and injury patterns. The predominantly extraosseous vascular supply of the talus predisposes it to significant injury in the setting of trauma. In addition, the lack of muscular attachments and absence of a secondary blood supply can lead to subsequent osteonecrosis. Although talar fractures account for less than 1% of all fractures, they commonly result from high-energy trauma and may lead to complications and long-term morbidity if not recognized and managed appropriately. While initial evaluation is with foot and ankle radiographs, computed tomography (CT) is often performed to evaluate the extent of the fracture, displacement, comminution, intra-articular extension, and associated injuries. Talar fractures are divided by anatomic region: head, neck, and body. Talar head fractures can be treated conservatively if nondisplaced, warranting careful radiographic and CT evaluation to assess rotation, displacement, and extension into the neck. The modified Hawkins-Canale classification of talar neck fractures is most commonly used due to its simplicity, usefulness in guiding treatment, and prognostic value, as it correlates associated malalignment with risk of subsequent osteonecrosis. Isolated talar body fractures may be more common than previously thought. The Sneppen classification further divides talar body fractures into osteochondral talar dome, lateral and posterior process, and shear and crush comminuted central body fractures. Crush comminuted central body fractures carry a poor prognosis due to nonanatomic reduction, bone loss, and subsequent osteonecrosis. Lateral process fractures can be radiographically occult and require a higher index of suspicion for successful diagnosis. Subtalar dislocations are often accompanied by fractures, necessitating postreduction CT. Familiarity with the unique talar anatomy and injury patterns is essential for radiologists to facilitate

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...

Comparative Policy Study for Green Buildings in U.S. and China

Energy Technology Data Exchange (ETDEWEB)

Khanna, Nina; Romankiewicz, John; Feng, Wei; Zhou, Nan; Ye, Qing

2014-04-01

Prominent barriers facing the U.S. green building industry include the fact that government bodies that supervise health, fire safety, land, and other public operations are slow to revise codes to accommodate green building (regulatory barrier). In China, the lack of a green building professional accreditation process similar to the Leadership in Energy and Environmental Design (LEED) AP process limits the green building workforce capacity development (informational barrier). The main policies highlighted in this report to tackle these barriers are 1) comprehensive codes and labeling plan (informational, institutional), 2) government-led targets and demonstrations (risk), 3) education and awareness programs (informational), 4) fiscal policy that supports green building investment (financial), and 5) integrated design promotion (institutional, financial).

Heuristic approach to the classification of postpartum endometritis and its forms

Directory of Open Access Journals (Sweden)

E. A. Balashova

2017-01-01

Full Text Available Тhe work is dedicated to the development of a method of automated medical diagnosis based on the description of biomedical systems using two parameters: energy, reflecting the interaction of its elements, and entropy characterizing the organization of the system. The violations of the energy-entropy cycle of biomedical systems is reflected in the symptoms of the disease. Statistical link between the symptoms of the condition of the body and the nature of excitation of its elements best expressed in the heuristic description of the system state. High accuracy classification of the patient's condition is achieved by using heuristic detection methods. In the proposed approach, allowing to estimate the probability of correct diagnosis increases the accuracy of the classification, and the estimated minimum amount of training samples and the capacity of its constituent signs. Classification technique consists in averaging the characteristic values in the selected classes, the preparation of the complex of symptoms of the most important signs of the disease, to conduct a "rough" diagnostic threshold rules that allow to distinguish severe forms of the disease, then differential diagnosis the severity of the disease. The proposed method was tested for classification of the forms of puerperal endometritis (mild, moderate, severe. The training sample contained 70 case histories. Syndrome to classify the patient's condition was composed of 17 characteristics. Threshold diagnosis has allowed to establish the presence of disease and to separate heavy. Differential diagnosis was used for classification of mild and moderate severity of postpartum endometritis. The accuracy of the classification of forms of postpartum endometritis amounted to 97.1%.

Perceptions of healthcare professionals regarding their own body ...

African Journals Online (AJOL)

... is a risk factor for obesity. It is important to focus on the health of this group of workers, on whom the health of South Africans depends and who should be the drivers of healthy living for all. Correct classification of their own body weight will encourage people to take action in a bid to combat their own and others' obesity.

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)...

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.

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.

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.

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...

Chocolate Classification by an Electronic Nose with Pressure Controlled Generated Stimulation

Directory of Open Access Journals (Sweden)

Luis F. Valdez

2016-10-01

Full Text Available In this work, we will analyze the response of a Metal Oxide Gas Sensor (MOGS array to a flow controlled stimulus generated in a pressure controlled canister produced by a homemade olfactometer to build an E-nose. The built E-nose is capable of chocolate identification between the 26 analyzed chocolate bar samples and four features recognition (chocolate type, extra ingredient, sweetener and expiration date status. The data analysis tools used were Principal Components Analysis (PCA and Artificial Neural Networks (ANNs. The chocolate identification E-nose average classification rate was of 81.3% with 0.99 accuracy (Acc, 0.86 precision (Prc, 0.84 sensitivity (Sen and 0.99 specificity (Spe for test. The chocolate feature recognition E-nose gives a classification rate of 85.36% with 0.96 Acc, 0.86 Prc, 0.85 Sen and 0.96 Spe. In addition, a preliminary sample aging analysis was made. The results prove the pressure controlled generated stimulus is reliable for this type of studies.

Chocolate Classification by an Electronic Nose with Pressure Controlled Generated Stimulation.

Science.gov (United States)

Valdez, Luis F; Gutiérrez, Juan Manuel

2016-10-20

In this work, we will analyze the response of a Metal Oxide Gas Sensor (MOGS) array to a flow controlled stimulus generated in a pressure controlled canister produced by a homemade olfactometer to build an E-nose. The built E-nose is capable of chocolate identification between the 26 analyzed chocolate bar samples and four features recognition (chocolate type, extra ingredient, sweetener and expiration date status). The data analysis tools used were Principal Components Analysis (PCA) and Artificial Neural Networks (ANNs). The chocolate identification E-nose average classification rate was of 81.3% with 0.99 accuracy (Acc), 0.86 precision (Prc), 0.84 sensitivity (Sen) and 0.99 specificity (Spe) for test. The chocolate feature recognition E-nose gives a classification rate of 85.36% with 0.96 Acc, 0.86 Prc, 0.85 Sen and 0.96 Spe. In addition, a preliminary sample aging analysis was made. The results prove the pressure controlled generated stimulus is reliable for this type of studies.

A classification of marked hijaiyah letters' pronunciation using hidden Markov model

Science.gov (United States)

Wisesty, Untari N.; Mubarok, M. Syahrul; Adiwijaya

2017-08-01

Hijaiyah letters are the letters that arrange the words in Al Qur'an consisting of 28 letters. They symbolize the consonant sounds. On the other hand, the vowel sounds are symbolized by harokat/marks. Speech recognition system is a system used to process the sound signal to be data so that it can be recognized by computer. To build the system, some stages are needed i.e characteristics/feature extraction and classification. In this research, LPC and MFCC extraction method, K-Means Quantization vector and Hidden Markov Model classification are used. The data used are the 28 letters and 6 harakat with the total class of 168. After several are testing done, it can be concluded that the system can recognize the pronunciation pattern of marked hijaiyah letter very well in the training data with its highest accuracy of 96.1% using the feature of LPC extraction and 94% using the MFCC. Meanwhile, when testing system is used, the accuracy decreases up to 41%.

A three-way approach for protein function classification.

Directory of Open Access Journals (Sweden)

Hafeez Ur Rehman

Full Text Available The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS and Information-Theoretic Rough Sets (ITRS for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy.

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.

Use of Ecohydraulic-Based Mesohabitat Classification and Fish Species Traits for Stream Restoration Design

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John S. Schwartz

2016-11-01

Full Text Available Stream restoration practice typically relies on a geomorphological design approach in which the integration of ecological criteria is limited and generally qualitative, although the most commonly stated project objective is to restore biological integrity by enhancing habitat and water quality. Restoration has achieved mixed results in terms of ecological successes and it is evident that improved methodologies for assessment and design are needed. A design approach is suggested for mesohabitat restoration based on a review and integration of fundamental processes associated with: (1 lotic ecological concepts; (2 applied geomorphic processes for mesohabitat self-maintenance; (3 multidimensional hydraulics and habitat suitability modeling; (4 species functional traits correlated with fish mesohabitat use; and (5 multi-stage ecohydraulics-based mesohabitat classification. Classification of mesohabitat units demonstrated in this article were based on fish preferences specifically linked to functional trait strategies (i.e., feeding resting, evasion, spawning, and flow refugia, recognizing that habitat preferences shift by season and flow stage. A multi-stage classification scheme developed under this premise provides the basic “building blocks” for ecological design criteria for stream restoration. The scheme was developed for Midwest US prairie streams, but the conceptual framework for mesohabitat classification and functional traits analysis can be applied to other ecoregions.

Land use and land cover classification for rural residential areas in China using soft-probability cascading of multifeatures

Science.gov (United States)

Zhang, Bin; Liu, Yueyan; Zhang, Zuyu; Shen, Yonglin

2017-10-01

A multifeature soft-probability cascading scheme to solve the problem of land use and land cover (LULC) classification using high-spatial-resolution images to map rural residential areas in China is proposed. The proposed method is used to build midlevel LULC features. Local features are frequently considered as low-level feature descriptors in a midlevel feature learning method. However, spectral and textural features, which are very effective low-level features, are neglected. The acquisition of the dictionary of sparse coding is unsupervised, and this phenomenon reduces the discriminative power of the midlevel feature. Thus, we propose to learn supervised features based on sparse coding, a support vector machine (SVM) classifier, and a conditional random field (CRF) model to utilize the different effective low-level features and improve the discriminability of midlevel feature descriptors. First, three kinds of typical low-level features, namely, dense scale-invariant feature transform, gray-level co-occurrence matrix, and spectral features, are extracted separately. Second, combined with sparse coding and the SVM classifier, the probabilities of the different LULC classes are inferred to build supervised feature descriptors. Finally, the CRF model, which consists of two parts: unary potential and pairwise potential, is employed to construct an LULC classification map. Experimental results show that the proposed classification scheme can achieve impressive performance when the total accuracy reached about 87%.

Assessing reserve-building pursuits and person characteristics: psychometric validation of the Reserve-Building Measure.

Science.gov (United States)

Schwartz, Carolyn E; Michael, Wesley; Zhang, Jie; Rapkin, Bruce D; Sprangers, Mirjam A G

2018-02-01

A growing body of research suggests that regularly engaging in stimulating activities across multiple domains-physical, cultural, intellectual, communal, and spiritual-builds resilience. This project investigated the psychometric characteristics of the DeltaQuest Reserve-Building Measure for use in prospective research. The study included Rare Patient Voice panel participants. The web-based survey included the Reserve-Building Measure with one-week re-test, measures of quality of life (QOL) and well-being (PROMIS General Health; NeuroQOL Cognitive Function and Positive Affect & Well-Being short-forms; Ryff Environmental Mastery subscale); and the Big Five Inventory-10 personality measure. Classical test theory and item response theory (IRT) analyses investigated psychometric characteristics of the Reserve-Building Measure. This North American sample (n = 592) included both patients and caregivers [mean age = 44, SD 19)]. Psychometric analyses revealed distinct subscales measuring current reserve-building activities (Active in the World, Games, Outdoors, Creative, Religious/Spiritual, Exercise, Inner Life, Shopping/Cooking, Passive Media Consumption,), past reserve-building activities (Childhood Activities, Achievement), and reserve-related person-factors (Perseverance, Current and Past Social Support, and Work Value). Test-retest stability (n = 101) was moderately high for 11 of 15 subscales (ICC range 0.78-0.99); four were below 0.59 indicating a need for further refinement. IRT analyses supported the item functioning of all subscales. Correlational analyses suggest the measure's subscales tap distinct constructs (range r = 0.11-0.46) which are not redundant with QOL, well-being, or personality (range r = 0.11-0.48). The Reserve-Building Measure provides a measure of activities and person-factors related to reserve that may potentially be useful in prospective research.

Application of a neural network for reflectance spectrum classification

Science.gov (United States)

Yang, Gefei; Gartley, Michael

2017-05-01

Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

Guidelines for Building Science Education

Energy Technology Data Exchange (ETDEWEB)

Metzger, Cheryn E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rashkin, Samuel [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Huelman, Pat [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-11-01

building science education. This report summarizes the steps DOE has taken to develop guidance for building science education and outlines a path forward towards creating real change for an industry in need. The Guidelines for Building Science Education outlined in Appendix A of this report have been developed for external stakeholders to use to certify that their programs are incorporating the most important aspects of building science at the most appropriate proficiency level for their role. The guidelines are intended to be used primarily by training organizations, universities, and certification bodies. Each guideline can be printed or saved as a stand-alone document for ease-of-use by the respective stakeholder group. In 2015, DOE, with leadership from Pacific Northwest National Laboratory (PNNL), is launching a multi-year campaign to promote the adoption of the Guidelines for Building Science Education in a variety of training settings.

Body composition and perception of teenagers from public schools

Directory of Open Access Journals (Sweden)

Ana Paula Araújo Ferreira

2013-10-01

Full Text Available Adolescence is accompanied by cognitive, emotional, social and biological changes; situations that increase the risk for development of psychosomatic disorders. This study measured and classified body composition and compared it to body self-perception in adolescents. Students from the seventh to ninth grade in public primary education in Distrito Federal, Brazil, answered socio-demographic and body self-perception questionnaires. Weight and height were measured and body mass index (BMI was calculated for body composition classification. From the 977 adolescents, 79.1% presented eutrophic BMI. Of the 473 boys, 11.4% were overweight and 4.7% underweight, 23.8% perceived the body as smaller than it really is and 25.5% tried to gain body mass. Of the 504 girls, 11.9% were overweight and 13.4% underweight, 24.1% perceived the body as larger than it really is and 32.5% tried to lose body mass. Inadequate body composition, prevalent in 20.9% of adolescents, may harm growth, development and health. These problems may be aggravated by the high prevalence of distorted body self-perception and attitudes for bodily changes. It is recommended the implementation of educational interventions on body composition, perception and culture and health, with different approaches by gender.

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.

Investigations of radioactivity of building raw and materials

International Nuclear Information System (INIS)

Zak, A.; Biernacka, M.; Jagielak, J.; Lipinski, P.

1993-01-01

In 1980, Ministry of Building and Building Materials Industry, the Central Laboratory for Radiological Protection (abbreviated as CLRP), Ministry of Health and Social Welfare have agreed to issue the compulsory regulation of performing the validation of investigations of building raw and materials. Methods of measurement, apparatus and method of evaluation of results of the investigations have been recommended for the whole country. The following two criteria of usefulness of a building material for housing and public building have been accepted, f 1 = 0.00027 S K + 0.0027 S Ra0 .0043 S Th ≤ 1 (this one limit exposition of the whole body to gamma radiation); f 2 = S Ra ≤ 185 Bq/kg (this one limits exposition of lung epithelium to progeny of radon 222 Rn exhaled from the building walls). The CLRP and Institute of Building Technology supervise over correctness (agreement with the regulations) of operation of laboratories in Departments of Building Industry and Energy, organize training of the personnel and collect results of the measurements. From 1980 till 1991, results of measurements of 6550 samples from 550 localities were collected in computer data base organized in CLRP. In this paper, results of examination of selected groups of building raw and materials have been presented. Annual average values of the qualification coefficients f 1 and f 2 have been also analyzed. (author). 7 refs, 13 figs, 2 tabs

Graph-based Techniques for Topic Classification of Tweets in Spanish

Directory of Open Access Journals (Sweden)

Hector Cordobés

2014-03-01

Full Text Available Topic classification of texts is one of the most interesting challenges in Natural Language Processing (NLP. Topic classifiers commonly use a bag-of-words approach, in which the classifier uses (and is trained with selected terms from the input texts. In this work we present techniques based on graph similarity to classify short texts by topic. In our classifier we build graphs from the input texts, and then use properties of these graphs to classify them. We have tested the resulting algorithm by classifying Twitter messages in Spanish among a predefined set of topics, achieving more than 70% accuracy.

The construction of human body--from model to reality.

Science.gov (United States)

Motoc, A; Motoc, Marilena; Bolintineanu, S; Muşuroi, Corina; Munteanu, M

2005-01-01

The human body building represented a complex research topic for the scientist in the most diverse domains. Although their interests and reasons were different, the goal was always the same: establishing a relation to verify the ratio between the dimensions of the constituent segments It appears that the mystery was solved out in the XIX-th century by Adolf Zeising, a German, who, using the statistic calculus, defined the division of a segment by the gold section. This purely mathematic logic confirms the human body's integration in proportion to the finest segments, thus providing the technical instrument of building a fully harmonious human body. The present study aims to compare the ideal, the calculated perfection to the reality, namely the theoretically obtained values to the average values of an 18-year-old male. It appears that the differences refer especially to the limbs; both the superior ones and the inferior ones being longer comparing to the ideal pattern while the bust is shorter and broader.

REMOTE SENSING IMAGE CLASSIFICATION APPLIED TO THE FIRST NATIONAL GEOGRAPHICAL INFORMATION CENSUS OF CHINA

Directory of Open Access Journals (Sweden)

X. Yu

2016-06-01

Full Text Available Image classification will still be a long way in the future, although it has gone almost half a century. In fact, researchers have gained many fruits in the image classification domain, but there is still a long distance between theory and practice. However, some new methods in the artificial intelligence domain will be absorbed into the image classification domain and draw on the strength of each to offset the weakness of the other, which will open up a new prospect. Usually, networks play the role of a high-level language, as is seen in Artificial Intelligence and statistics, because networks are used to build complex model from simple components. These years, Bayesian Networks, one of probabilistic networks, are a powerful data mining technique for handling uncertainty in complex domains. In this paper, we apply Tree Augmented Naive Bayesian Networks (TAN to texture classification of High-resolution remote sensing images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples. Since 2013, China government has started the first national geographical information census project, which mainly interprets geographical information based on high-resolution remote sensing images. Therefore, this paper tries to apply Bayesian network to remote sensing image classification, in order to improve image interpretation in the first national geographical information census project. In the experiment, we choose some remote sensing images in Beijing. Experimental results demonstrate TAN outperform than Naive Bayesian Classifier (NBC and Maximum Likelihood Classification Method (MLC in the overall classification accuracy. In addition, the proposed method can reduce the workload of field workers and improve the work efficiency. Although it is time consuming, it will be an attractive and effective method for assisting office operation of image interpretation.

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.

Obsessive-compulsive skin disorders: a novel classification based on degree of insight.

Science.gov (United States)

Zhu, Tian Hao; Nakamura, Mio; Farahnik, Benjamin; Abrouk, Michael; Reichenberg, Jason; Bhutani, Tina; Koo, John

2017-06-01

Individuals with obsessive-compulsive features frequently visit dermatologists for complaints of the skin, hair or nails, and often progress towards a chronic relapsing course due to the challenge associated with accurate diagnosis and management of their psychiatric symptoms. The current DSM-5 formally recognizes body dysmorphic disorder, trichotillomania, neurotic excoriation and body focused repetitive behavior disorder as psychodermatological disorders belonging to the category of Obsessive-Compulsive and Related Disorders. However there is evidence that other relevant skin diseases such as delusions of parasitosis, dermatitis artefacta, contamination dermatitis, AIDS phobia, trichotemnomania and even lichen simplex chronicus possess prominent obsessive-compulsive characteristics that do not necessarily fit the full diagnostic criteria of the DSM-5. Therefore, to increase dermatologists' awareness of this unique group of skin disorders with OCD features, we propose a novel classification system called Obsessive-Compulsive Insight Continuum. Under this new classification system, obsessive-compulsive skin manifestations are categorized along a continuum based on degree of insight, from minimal insight with delusional obsessions to good insight with minimal obsessions. Understanding the level of insight is thus an important first step for clinicians who routinely interact with these patients.

Activity classification based on inertial and barometric pressure sensors at different anatomical locations.

Science.gov (United States)

Moncada-Torres, A; Leuenberger, K; Gonzenbach, R; Luft, A; Gassert, R

2014-07-01

Miniature, wearable sensor modules are a promising technology to monitor activities of daily living (ADL) over extended periods of time. To assure both user compliance and meaningful results, the selection and placement site of sensors requires careful consideration. We investigated these aspects for the classification of 16 ADL in 6 healthy subjects under laboratory conditions using ReSense, our custom-made inertial measurement unit enhanced with a barometric pressure sensor used to capture activity-related altitude changes. Subjects wore a module on each wrist and ankle, and one on the trunk. Activities comprised whole body movements as well as gross and dextrous upper-limb activities. Wrist-module data outperformed the other locations for the three activity groups. Specifically, overall classification accuracy rates of almost 93% and more than 95% were achieved for the repeated holdout and user-specific validation methods, respectively, for all 16 activities. Including the altitude profile resulted in a considerable improvement of up to 20% in the classification accuracy for stair ascent and descent. The gyroscopes provided no useful information for activity classification under this scheme. The proposed sensor setting could allow for robust long-term activity monitoring with high compliance in different patient populations.

Activity classification based on inertial and barometric pressure sensors at different anatomical locations

International Nuclear Information System (INIS)

Moncada-Torres, A; Leuenberger, K; Gassert, R; Gonzenbach, R; Luft, A

2014-01-01

Miniature, wearable sensor modules are a promising technology to monitor activities of daily living (ADL) over extended periods of time. To assure both user compliance and meaningful results, the selection and placement site of sensors requires careful consideration. We investigated these aspects for the classification of 16 ADL in 6 healthy subjects under laboratory conditions using ReSense, our custom-made inertial measurement unit enhanced with a barometric pressure sensor used to capture activity-related altitude changes. Subjects wore a module on each wrist and ankle, and one on the trunk. Activities comprised whole body movements as well as gross and dextrous upper-limb activities. Wrist-module data outperformed the other locations for the three activity groups. Specifically, overall classification accuracy rates of almost 93% and more than 95% were achieved for the repeated holdout and user-specific validation methods, respectively, for all 16 activities. Including the altitude profile resulted in a considerable improvement of up to 20% in the classification accuracy for stair ascent and descent. The gyroscopes provided no useful information for activity classification under this scheme. The proposed sensor setting could allow for robust long-term activity monitoring with high compliance in different patient populations. (paper)

Classification of deadlift biomechanics with wearable inertial measurement units.

Science.gov (United States)

O'Reilly, Martin A; Whelan, Darragh F; Ward, Tomas E; Delahunt, Eamonn; Caulfield, Brian M

2017-06-14

The deadlift is a compound full-body exercise that is fundamental in resistance training, rehabilitation programs and powerlifting competitions. Accurate quantification of deadlift biomechanics is important to reduce the risk of injury and ensure training and rehabilitation goals are achieved. This study sought to develop and evaluate deadlift exercise technique classification systems utilising Inertial Measurement Units (IMUs), recording at 51.2Hz, worn on the lumbar spine, both thighs and both shanks. It also sought to compare classification quality when these IMUs are worn in combination and in isolation. Two datasets of IMU deadlift data were collected. Eighty participants first completed deadlifts with acceptable technique and 5 distinct, deliberately induced deviations from acceptable form. Fifty-five members of this group also completed a fatiguing protocol (3-Repition Maximum test) to enable the collection of natural deadlift deviations. For both datasets, universal and personalised random-forests classifiers were developed and evaluated. Personalised classifiers outperformed universal classifiers in accuracy, sensitivity and specificity in the binary classification of acceptable or aberrant technique and in the multi-label classification of specific deadlift deviations. Whilst recent research has favoured universal classifiers due to the reduced overhead in setting them up for new system users, this work demonstrates that such techniques may not be appropriate for classifying deadlift technique due to the poor accuracy achieved. However, personalised classifiers perform very well in assessing deadlift technique, even when using data derived from a single lumbar-worn IMU to detect specific naturally occurring technique mistakes. Copyright © 2017 Elsevier Ltd. All rights reserved.

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…

Neural network models: from biology to many - body phenomenology

International Nuclear Information System (INIS)

Clark, J.W.

1993-01-01

The current surge of research on practical side of neural networks and their utility in memory storage/recall, pattern recognition and classification is given in this article. The initial attraction of neural networks as dynamical and statistical system has been investigated. From the view of many-body theorist, the neurons may be thought of as particles, and the weighted connection between the units, as the interaction between these particles. Finally, the author has seen the impressive capabilities of artificial neural networks in pattern recognition and classification may be exploited to solve data management problems in experimental physics and the discovery of radically new theoretically description of physical problems and neural networks can be used in physics. (A.B.)

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

Face classification using electronic synapses

Science.gov (United States)

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

2017-05-01

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

CBM Resources/reserves classification and evaluation based on PRMS rules

Science.gov (United States)

Fa, Guifang; Yuan, Ruie; Wang, Zuoqian; Lan, Jun; Zhao, Jian; Xia, Mingjun; Cai, Dechao; Yi, Yanjing

2018-02-01

This paper introduces a set of definitions and classification requirements for coalbed methane (CBM) resources/reserves, based on Petroleum Resources Management System (PRMS). The basic CBM classification criterions of 1P, 2P, 3P and contingent resources are put forward from the following aspects: ownership, project maturity, drilling requirements, testing requirements, economic requirements, infrastructure and market, timing of production and development, and so on. The volumetric method is used to evaluate the OGIP, with focuses on analyses of key parameters and principles of the parameter selection, such as net thickness, ash and water content, coal rank and composition, coal density, cleat volume and saturation and absorbed gas content etc. A dynamic method is used to assess the reserves and recovery efficiency. Since the differences in rock and fluid properties, displacement mechanism, completion and operating practices and wellbore type resulted in different production curve characteristics, the factors affecting production behavior, the dewatering period, pressure build-up and interference effects were analyzed. The conclusion and results that the paper achieved can be used as important references for reasonable assessment of CBM resources/reserves.

Investigating the removal of body piercings.

Science.gov (United States)

Armstrong, Myrna L; Roberts, Alden E; Koch, Jerome R; Saunders, Jana C; Owen, Donna C

2007-05-01

Although body piercing procurement continues to increase, 13% to 18% of them are removed. Reasons for piercing removal in college students were examined with three groups: (a) those who kept all their piercings, (b) those who removed some, or (c) those who removed all of their body piercings. Of the sample, 41% were still pierced; 50% in their lifetime. Their major purpose for the body piercing was "helped them feel unique." Females obtained more (in high school) and then removed more, usually as upperclassmen. Males and females reported themselves as risk takers at procedure time and currently; however, only 10% cited deviancy as a reason for the body piercing(s). Only removal elements of "I just got tired of it" and "I just decided to remove it" were present, especially with the Some Removed Group. Further examination of body piercing building personal distinctiveness and self-identity to promote their need of uniqueness is suggested.

Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

Science.gov (United States)

Parida, G.; Rajan, K. S.

2017-05-01

The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

LOCALIZED SEGMENT BASED PROCESSING FOR AUTOMATIC BUILDING EXTRACTION FROM LiDAR DATA

Directory of Open Access Journals (Sweden)

G. Parida

2017-05-01

Full Text Available The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

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.

Building energy retrofit index for policy making and decision support at regional and national scales

International Nuclear Information System (INIS)

Khayatian, Fazel; Sarto, Luca; Dall'O', Giuliano

2017-01-01

Highlights: •Machine learning is used for pre-processing, fine-tuning and post-processing data. •A new indicator is introduced to support building energy retrofit policies. •The presented indicator is evaluated by a case study of 4767 buildings. •Current energy indicators can misrepresent the building energy retrofit potential. -- Abstract: The vast data collected since the enforcement of building energy labelling in Italy has provided valuable information that is useful for planning the future of building energy efficiency. However, the indicators provided through energy certificates are not suitable to support decisions, which target building energy retrofit in a regional scale. Considering the bias of the energy performance index toward a building’s shape, decisions based on this index will favor buildings with a specific geometric characteristics. This study tends to overcome this issue by introducing a new indicator, tailored to rank buildings based on retrofitable characteristics. The proposed framework is validated by a case study, in which a large dataset of office buildings are assigned with the new index. Results indicate that the proposed indicator succeeds to extract a single index, which is representative of all building characteristics subject to energy retrofit. A new labeling procedure is also compared with the conventional classification of buildings. It is observed that the proposed labels properly partitions the dataset, according to buildings’ potential to undergo energy retrofit.

Stratification of a cityscape using census and land use variables for inventory of building materials

Science.gov (United States)

Rosenfield, G.H.; Fitzpatrick-Lins, K.; Johnson, T.L.

1987-01-01

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional

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

Classification of Alzheimer's Patients through Ubiquitous Computing.

Science.gov (United States)

Nieto-Reyes, Alicia; Duque, Rafael; Montaña, José Luis; Lage, Carmen

2017-07-21

Functional data analysis and artificial neural networks are the building blocks of the proposed methodology that distinguishes the movement patterns among c's patients on different stages of the disease and classifies new patients to their appropriate stage of the disease. The movement patterns are obtained by the accelerometer device of android smartphones that the patients carry while moving freely. The proposed methodology is relevant in that it is flexible on the type of data to which it is applied. To exemplify that, it is analyzed a novel real three-dimensional functional dataset where each datum is observed in a different time domain. Not only is it observed on a difference frequency but also the domain of each datum has different length. The obtained classification success rate of 83 % indicates the potential of the proposed methodology.

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.

Oesophageal foreign body and a double aortic arch: rare dual pathology.