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

NASA Astrophysics Data System (ADS)

Taghvaei, Sajjad; Kosuge, Kazuhiro

2017-10-01

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

Ground truth management system to support multispectral scanner /MSS/ digital analysis

NASA Technical Reports Server (NTRS)

Coiner, J. C.; Ungar, S. G.

1977-01-01

A computerized geographic information system for management of ground truth has been designed and implemented to relate MSS classification results to in situ observations. The ground truth system transforms, generalizes and rectifies ground observations to conform to the pixel size and shape of high resolution MSS aircraft data. These observations can then be aggregated for comparison to lower resolution sensor data. Construction of a digital ground truth array allows direct pixel by pixel comparison between classification results of MSS data and ground truth. By making comparisons, analysts can identify spatial distribution of error within the MSS data as well as usual figures of merit for the classifications. Use of the ground truth system permits investigators to compare a variety of environmental or anthropogenic data, such as soil color or tillage patterns, with classification results and allows direct inclusion of such data into classification operations. To illustrate the system, examples from classification of simulated Thematic Mapper data for agricultural test sites in North Dakota and Kansas are provided.

Classification and Mapping of Agricultural Land for National Water-Quality Assessment

USGS Publications Warehouse

Gilliom, Robert J.; Thelin, Gail P.

1997-01-01

Agricultural land use is one of the most important influences on water quality at national and regional scales. Although there is great diversity in the character of agricultural land, variations follow regional patterns that are influenced by environmental setting and economics. These regional patterns can be characterized by the distribution of crops. A new approach to classifying and mapping agricultural land use for national water-quality assessment was developed by combining information on general land-use distribution with information on crop patterns from agricultural census data. Separate classification systems were developed for row crops and for orchards, vineyards, and nurseries. These two general categories of agricultural land are distinguished from each other in the land-use classification system used in the U.S. Geological Survey national Land Use and Land Cover database. Classification of cropland was based on the areal extent of crops harvested. The acreage of each crop in each county was divided by total row-crop area or total orchard, vineyard, and nursery area, as appropriate, thus normalizing the crop data and making the classification independent of total cropland area. The classification system was developed using simple percentage criteria to define combinations of 1 to 3 crops that account for 50 percent or more or harvested acreage in a county. The classification system consists of 21 level I categories and 46 level II subcategories for row crops, and 26 level I categories and 19 level II subcategories for orchards, vineyards, and nurseries. All counties in the United States with reported harvested acreage are classified in these categories. The distribution of agricultural land within each county, however, must be evaluated on the basis of general land-use data. This can be done at the national scale using 'Major Land Uses of the United States,' at the regional scale using data from the national Land Use and Land Cover database, or at smaller scales using locally available data.

TCP/IP Implementations and Vendors Guide,

DTIC Science & Technology

1986-02-01

DOCUMENTATION PAGE la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/ AVAILABILIT OF...UNIX System V (5.2) IMPLEMENTATION-LANGUAGE: C DISTRIBUTOR: UNIQ Digital Technologies 28 S. Water St. Batavia, fI1 60510 (312) 879-1008 CONTACT

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Sainani, Varsha

The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

Low-Level Wind Systems in the Warsaw Pact Countries.

DTIC Science & Technology

1985-03-01

CLASSIFICATION OF THIS PAGE o i REPORT DOCUMENTATION PAGE I le. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS Unclassified 2e, SECURITY...CLASSIFICATION AUTHORITY 3. OISTRIBUTION/AVAI LAOBILfTY OF REPORT 2b. ECLSSIICAIONDOWNRADNG CHEULEApproved for public release; distribution * 2b OELASSFICTIO...OOWGRAING CHEULEunlimited * 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) USAFETAC/TN-85/0Ol 6a. NAME OF

Acute Oral Toxicity of Nitroguanidine in Male and Female Rats

DTIC Science & Technology

1988-03-01

results place nitroguanidlne in the practically nontoxic category based on the toxicity classification system of Hodge and Sterner. 20 DISTRIBUTION...nose and mouth. These results place nitroguanidine in the practically nontoxic category based on the toxicity classification system of Hodge and...O. Lollini, DVM, VC, Diplomate, American College of Veterinary Pathologists DATA MANAGERS: Carolyn M. Lewis, MS, Yvonne C. Le Tellier , BS REPORT

A Study of Mesoscale Probability Forecasting Performance Based on an Advanced Image Display System.

DTIC Science & Technology

1984-04-30

CLASSIFICATION lb. RESTRICTIVE MARKINGS Uncl assified 2&. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAI LABILITY OF REPORT 2b. DE CLASSI FICAT... sensors in the surface network, an air-to-ground lightning detection system, and NWS 6Brown, R. C., 1983: Anatomy of a nesoscale instrumentation system...W. B. Sweezy, R. G. Strauch, E. R. Westwater, and C. G. Little, 1983: An automatic Profiler of the temperatura , wind, and humidity in the troposphere

Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

PubMed

Jiang, Yizhang; Wu, Dongrui; Deng, Zhaohong; Qian, Pengjiang; Wang, Jun; Wang, Guanjin; Chung, Fu-Lai; Choi, Kup-Sze; Wang, Shitong

2017-12-01

Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and the amount of training data may not be enough. In addition, most machine learning approaches generate black-box models that are difficult to interpret. In this paper, we integrate transductive transfer learning, semi-supervised learning and TSK fuzzy system to tackle these three problems. More specifically, we use transfer learning to reduce the discrepancy in data distribution between the training and testing data, employ semi-supervised learning to use the unlabeled testing data to remedy the shortage of training data, and adopt TSK fuzzy system to increase model interpretability. Two learning algorithms are proposed to train the system. Our experimental results show that the proposed approaches can achieve better performance than many state-of-the-art seizure classification algorithms.

A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

PubMed

Foo, Brian; van der Schaar, Mihaela

2010-11-01

In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

A hierarchical classification of freshwater mussel diversity in North America

Treesearch

Wendell R. Haag

2010-01-01

Aim North America harbours the most diverse freshwater mussel fauna on Earth. This fauna has high endemism at the continental scale and within individual river systems. Previous faunal classifications for North America were based on intuitive, subjective assessments of species distributions, primarily the occurrence of endemic species, and do not portray continent-wide...

Bag-of-features approach for improvement of lung tissue classification in diffuse lung disease

NASA Astrophysics Data System (ADS)

Kato, Noriji; Fukui, Motofumi; Isozaki, Takashi

2009-02-01

Many automated techniques have been proposed to classify diffuse lung disease patterns. Most of the techniques utilize texture analysis approaches with second and higher order statistics, and show successful classification result among various lung tissue patterns. However, the approaches do not work well for the patterns with inhomogeneous texture distribution within a region of interest (ROI), such as reticular and honeycombing patterns, because the statistics can only capture averaged feature over the ROI. In this work, we have introduced the bag-of-features approach to overcome this difficulty. In the approach, texture images are represented as histograms or distributions of a few basic primitives, which are obtained by clustering local image features. The intensity descriptor and the Scale Invariant Feature Transformation (SIFT) descriptor are utilized to extract the local features, which have significant discriminatory power due to their specificity to a particular image class. In contrast, the drawback of the local features is lack of invariance under translation and rotation. We improved the invariance by sampling many local regions so that the distribution of the local features is unchanged. We evaluated the performance of our system in the classification task with 5 image classes (ground glass, reticular, honeycombing, emphysema, and normal) using 1109 ROIs from 211 patients. Our system achieved high classification accuracy of 92.8%, which is superior to that of the conventional system with the gray level co-occurrence matrix (GLCM) feature especially for inhomogeneous texture patterns.

Performance analysis of distributed applications using automatic classification of communication inefficiencies

DOEpatents

Vetter, Jeffrey S.

2005-02-01

The method and system described herein presents a technique for performance analysis that helps users understand the communication behavior of their message passing applications. The method and system described herein may automatically classifies individual communication operations and reveal the cause of communication inefficiencies in the application. This classification allows the developer to quickly focus on the culprits of truly inefficient behavior, rather than manually foraging through massive amounts of performance data. Specifically, the method and system described herein trace the message operations of Message Passing Interface (MPI) applications and then classify each individual communication event using a supervised learning technique: decision tree classification. The decision tree may be trained using microbenchmarks that demonstrate both efficient and inefficient communication. Since the method and system described herein adapt to the target system's configuration through these microbenchmarks, they simultaneously automate the performance analysis process and improve classification accuracy. The method and system described herein may improve the accuracy of performance analysis and dramatically reduce the amount of data that users must encounter.

A new pre-classification method based on associative matching method

NASA Astrophysics Data System (ADS)

Katsuyama, Yutaka; Minagawa, Akihiro; Hotta, Yoshinobu; Omachi, Shinichiro; Kato, Nei

2010-01-01

Reducing the time complexity of character matching is critical to the development of efficient Japanese Optical Character Recognition (OCR) systems. To shorten processing time, recognition is usually split into separate preclassification and recognition stages. For high overall recognition performance, the pre-classification stage must both have very high classification accuracy and return only a small number of putative character categories for further processing. Furthermore, for any practical system, the speed of the pre-classification stage is also critical. The associative matching (AM) method has often been used for fast pre-classification, because its use of a hash table and reliance solely on logical bit operations to select categories makes it highly efficient. However, redundant certain level of redundancy exists in the hash table because it is constructed using only the minimum and maximum values of the data on each axis and therefore does not take account of the distribution of the data. We propose a modified associative matching method that satisfies the performance criteria described above but in a fraction of the time by modifying the hash table to reflect the underlying distribution of training characters. Furthermore, we show that our approach outperforms pre-classification by clustering, ANN and conventional AM in terms of classification accuracy, discriminative power and speed. Compared to conventional associative matching, the proposed approach results in a 47% reduction in total processing time across an evaluation test set comprising 116,528 Japanese character images.

Feasibility of the MUSIC Algorithm for the Active Protection System

DTIC Science & Technology

2001-03-01

Feasibility of the MUSIC Algorithm for the Active Protection System ARL-MR-501 March 2001 Canh Ly Approved for public release; distribution... MUSIC Algorithm for the Active Protection System Canh Ly Sensors and Electron Devices Directorate Approved for public release; distribution unlimited...This report compares the accuracy of the doppler frequency of an incoming projectile with the use of the MUSIC (multiple signal classification

Sea ice type maps from Alaska synthetic aperture radar facility imagery: An assessment

NASA Technical Reports Server (NTRS)

Fetterer, Florence M.; Gineris, Denise; Kwok, Ronald

1994-01-01

Synthetic aperture radar (SAR) imagery received at the Alaskan SAR Facility is routinely and automatically classified on the Geophysical Processor System (GPS) to create ice type maps. We evaluated the wintertime performance of the GPS classification algorithm by comparing ice type percentages from supervised classification with percentages from the algorithm. The root mean square (RMS) difference for multiyear ice is about 6%, while the inconsistency in supervised classification is about 3%. The algorithm separates first-year from multiyear ice well, although it sometimes fails to correctly classify new ice and open water owing to the wide distribution of backscatter for these classes. Our results imply a high degree of accuracy and consistency in the growing archive of multiyear and first-year ice distribution maps. These results have implications for heat and mass balance studies which are furthered by the ability to accurately characterize ice type distributions over a large part of the Arctic.

A statistical approach to root system classification

PubMed Central

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

2013-01-01

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

A statistical approach to root system classification.

PubMed

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

2013-01-01

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

Application of Bayesian Classification to Content-Based Data Management

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Berrick, S.; Gopalan, A.; Hua, X.; Shen, S.; Smith, P.; Yang, K-Y.; Wheeler, K.; Curry, C.

2004-01-01

The high volume of Earth Observing System data has proven to be challenging to manage for data centers and users alike. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), about 1 TB of new data are archived each day. Distribution to users is also about 1 TB/day. A substantial portion of this distribution is MODIS calibrated radiance data, which has a wide variety of uses. However, much of the data is not useful for a particular user's needs: for example, ocean color users typically need oceanic pixels that are free of cloud and sun-glint. The GES DAAC is using a simple Bayesian classification scheme to rapidly classify each pixel in the scene in order to support several experimental content-based data services for near-real-time MODIS calibrated radiance products (from Direct Readout stations). Content-based subsetting would allow distribution of, say, only clear pixels to the user if desired. Content-based subscriptions would distribute data to users only when they fit the user's usability criteria in their area of interest within the scene. Content-based cache management would retain more useful data on disk for easy online access. The classification may even be exploited in an automated quality assessment of the geolocation product. Though initially to be demonstrated at the GES DAAC, these techniques have applicability in other resource-limited environments, such as spaceborne data systems.

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

PubMed

Ghasemzadeh, Hassan; Loseu, Vitali; Jafari, Roozbeh

2010-03-01

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

Abiotic Supramolecular Systems

DTIC Science & Technology

2011-05-02

REPORT Abiotic Supramolecular Systems 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The goal of this research project was to develop new concepts for the...decision, unless so designated by other documentation. 12. DISTRIBUTION AVAILIBILITY STATEMENT Approved for Public Release; Distribution Unlimited UU...9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 6. AUTHORS 7. PERFORMING ORGANIZATION NAMES AND ADDRESSES U.S. Army Research Office P.O

A New Tool for Classifying Small Solar System Objects

NASA Astrophysics Data System (ADS)

Desfosses, Ryan; Arel, D.; Walker, M. E.; Ziffer, J.; Harvell, T.; Campins, H.; Fernandez, Y. R.

2011-05-01

An artificial intelligence program, AutoClass, which was developed by NASA's Artificial Intelligence Branch, uses Bayesian classification theory to automatically choose the most probable classification distribution to describe a dataset. To investigate its usefulness to the Planetary Science community, we tested its ability to reproduce the taxonomic classes as defined by Tholen and Barucci (1989). Of the 406 asteroids from the Eight Color Asteroid Survey (ECAS) we chose for our test, 346 were firmly classified and all but 3 (<1%) were classified by Autoclass as they had been in the previous classification system (Walker et al., 2011). We are now applying it to larger datasets to improve the taxonomy of currently unclassified objects. Having demonstrated AutoClass's ability to recreate existing classification effectively, we extended this work to investigations of albedo-based classification systems. To determine how predictive albedo can be, we used data from the Infrared Astronomical Satellite (IRAS) database in conjunction with the large Sloan Digital Sky Survey (SDSS), which contains color and position data for over 200,000 classified and unclassified asteroids (Ivesic et al., 2001). To judge our success we compared our results with a similar approach to classifying objects using IRAS albedo and asteroid color by Tedesco et al. (1989). Understanding the distribution of the taxonomic classes is important to understanding the history and evolution of our Solar System. AutoClass's success in categorizing ECAS, IRAS and SDSS asteroidal data highlights its potential to scan large domains for natural classes in small solar system objects. Based upon our AutoClass results, we intend to make testable predictions about asteroids observed with the Wide-field Infrared Survey Explorer (WISE).

Shape Modification and Size Classification of Microcrystalline Graphite Powder as Anode Material for Lithium-Ion Batteries

NASA Astrophysics Data System (ADS)

Wang, Cong; Gai, Guosheng; Yang, Yufen

2018-03-01

Natural microcrystalline graphite (MCG) composed of many crystallites is a promising new anode material for lithium-ion batteries (LiBs) and has received considerable attention from researchers. MCG with narrow particle size distribution and high sphericity exhibits excellent electrochemical performance. A nonaddition process to prepare natural MCG as a high-performance LiB anode material is described. First, raw MCG was broken into smaller particles using a pulverization system. Then, the particles were modified into near-spherical shape using a particle shape modification system. Finally, the particle size distribution was narrowed using a centrifugal rotor classification system. The products with uniform hemispherical shape and narrow size distribution had mean particle size of approximately 9 μm, 10 μm, 15 μm, and 20 μm. Additionally, the innovative pilot experimental process increased the product yield of the raw material. Finally, the electrochemical performance of the prepared MCG was tested, revealing high reversible capacity and good cyclability.

Determining bathymetric distributions of the eelgrass Zostera ...

EPA Pesticide Factsheets

Improved methods for determining bathymetric distributions of dominant intertidal plants throughout their estuarine range are needed. Zostera marina is a seagrass native to estuaries of the northeastern Pacific and many other sectors of the world ocean. The technique described here employed large format aerial photography using false color near-infrared film with digital image classification, and the production of digital bathymetric models of shallow estuaries such as those occurring in turbid waters of the Pacific Northwest USA. Application of geographic information system procedures to the eelgrass classifications and bathymetry distributions yielded digital bathymetric distributions based upon a very large number of observations. Similar bathymetric patterns were obtained for the three estuaries surveyed, and approximately 90% of the classified eelgrass occurred within the depth range -1.0 m to +1.0 m (MLLW). Comparison of these distributions with ground surveys of eelgrass lower depth limits indicated that the area of undetected subtidal eelgrass constituted 86% overall accuracy) in each estuary. The pattern of eelgrass in one estuary was distinctly different from those in the other two systems, illustrating the potential usefulness of this technique in exploring causative factors for such differences in estuarine intertidal vegetation distributions. Improved methods for determining bathymetric distributions of dominant intertidal plants throughout

Classification of cognitive systems dedicated to data sharing

NASA Astrophysics Data System (ADS)

Ogiela, Lidia; Ogiela, Marek R.

2017-08-01

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

Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

NASA Astrophysics Data System (ADS)

Gautam, Nitin

The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global distribution of these six classes is also compared with the earlier results obtained from Comprehensive Ocean Atmosphere Data Sets (COADS). It is found that the gross pattern of the distributions obtained from SSM/I and COADS data match remarkably well with each other.

A proposal for the annotation of recurrent colorectal cancer: the 'Sheffield classification'.

PubMed

Majeed, A W; Shorthouse, A J; Blakeborough, A; Bird, N C

2011-11-01

Current classification systems of large bowel cancer only refer to metastatic disease as M0, M1 or Mx. Recurrent colorectal cancer primarily occurs in the liver, lungs, nodes or peritoneum. The management of each of these sites of recurrence has made significant advances and each is a subspecialty in its own right. The aim of this paper was to devise a classification system which accurately describes the site and extent of metastatic spread. An amendment of the current system is proposed in which liver, lung and peritoneal metastases are annotated by 'Liv 0,1', 'Pul 0,1' and 'Per 0,1' in describing the primary presentation. These are then subclassified, taking into account the chronology, size, number and geographical distribution of metastatic disease or logoregional recurrence and its K-Ras status. This discussion document proposes a classification system which is logical and simple to use. We plan to validate it prospectively. © 2011 The Authors. Colorectal Disease © 2011 The Association of Coloproctology of Great Britain and Ireland.

Classification and management of extensive obstetric perineal injuries in the Czech and Slovak Republics.

PubMed

Zahumensky, Jozef; Menzlova, Erika; Korbel, Miroslav; Zmrhalova, Barbora; Vasicka, Ian; Sottner, Oldrich

2010-09-01

To assess the classification, repair, and follow up of extensive obstetric perineal injuries in the Czech and Slovak Republics. A survey conducted in 2009 using questionnaires distributed to obstetric departments regarding classification and management of obstetric perineal injuries. Although 15 centers in the Czech Republic and 2 in the Slovak Republic indicated use of a 4-degree classification system, none of these centers reported using the classification accepted by the Royal College of Obstetricians and Gynaecologists. Use of a 3-degree classification system in accordance with definitions in Czech textbooks was reported by 14 Czech and 3 Slovak maternity hospitals. There was significant heterogeneity in clinical practice regarding techniques to repair extensive obstetric perineal injuries, antibiotic prophylaxis, early postpartum care, and follow up. There is great inconsistency in the classification and management of extensive obstetric perineal injuries. Uniform recommendations should be created and accepted, not only in the Czech and Slovak Republics, but worldwide. Copyright 2010 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

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

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

System Error Budgets, Target Distributions and Hitting Performance Estimates for General-Purpose Rifles and Sniper Rifles of 7.62 x 51 mm and Larger Calibers

DTIC Science & Technology

1990-05-01

CLASSIFICATION AUTPOVITY 3. DISTRIBUTION IAVAILABILITY OF REPORT 2b. P OCLASSIFICATION/OOWNGRADING SC14DULE Approved for public release; distribution 4...in the Red Book should obtain a copy of the Engineering Design Handbook, Army Weapon System Analysis, Part One, DARCOM- P 706-101, November 1977; a...companion volume: Army Weapon System Analysis, Part Two, DARCOM- P 706-102, October 1979, also makes worthwhile study. Both of these documents, written by

Etiological classifications of transient ischemic attacks: subtype classification by TOAST, CCS and ASCO--a pilot study.

PubMed

Amort, Margareth; Fluri, Felix; Weisskopf, Florian; Gensicke, Henrik; Bonati, Leo H; Lyrer, Philippe A; Engelter, Stefan T

2012-01-01

In patients with transient ischemic attacks (TIA), etiological classification systems are not well studied. The Trial of ORG 10172 in Acute Stroke Treatment (TOAST), the Causative Classification System (CCS), and the Atherosclerosis Small Vessel Disease Cardiac Source Other Cause (ASCO) classification may be useful to determine the underlying etiology. We aimed at testing the feasibility of each of the 3 systems. Furthermore, we studied and compared their prognostic usefulness. In a single-center TIA registry prospectively ascertained over 2 years, we applied 3 etiological classification systems. We compared the distribution of underlying etiologies, the rates of patients with determined versus undetermined etiology, and studied whether etiological subtyping distinguished TIA patients with versus without subsequent stroke or TIA within 3 months. The 3 systems were applicable in all 248 patients. A determined etiology with the highest level of causality was assigned similarly often with TOAST (35.9%), CCS (34.3%), and ASCO (38.7%). However, the frequency of undetermined causes differed significantly between the classification systems and was lowest for ASCO (TOAST: 46.4%; CCS: 37.5%; ASCO: 18.5%; p < 0.001). In TOAST, CCS, and ASCO, cardioembolism (19.4/14.5/18.5%) was the most common etiology, followed by atherosclerosis (11.7/12.9/14.5%). At 3 months, 33 patients (13.3%, 95% confidence interval 9.3-18.2%) had recurrent cerebral ischemic events. These were strokes in 13 patients (5.2%; 95% confidence interval 2.8-8.8%) and TIAs in 20 patients (8.1%, 95% confidence interval 5.0-12.2%). Patients with a determined etiology (high level of causality) had higher rates of subsequent strokes than those without a determined etiology [TOAST: 6.7% (95% confidence interval 2.5-14.1%) vs. 4.4% (95% confidence interval 1.8-8.9%); CSS: 9.3% (95% confidence interval 4.1-17.5%) vs. 3.1% (95% confidence interval 1.0-7.1%); ASCO: 9.4% (95% confidence interval 4.4-17.1%) vs. 2.6% (95% confidence interval 0.7-6.6%)]. However, this difference was only significant in the ASCO classification (p = 0.036). Using ASCO, there was neither an increase in risk of subsequent stroke among patients with incomplete diagnostic workup (at least one subtype scored 9) compared with patients with adequate workup (no subtype scored 9), nor among patients with multiple causes compared with patients with a single cause. In TIA patients, all etiological classification systems provided a similar distribution of underlying etiologies. The increase in stroke risk in TIA patients with determined versus undetermined etiology was most evident using the ASCO classification. Copyright © 2012 S. Karger AG, Basel.

A Systematic Classification for HVAC Systems and Components

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

Li, Han; Chen, Yan; Zhang, Jian

Depending on the application, the complexity of an HVAC system can range from a small fan coil unit to a large centralized air conditioning system with primary and secondary distribution loops, and central plant components. Currently, the taxonomy of HVAC systems and the components has various aspects, which can get quite complex because of the various components and system configurations. For example, based on cooling and heating medium delivered to terminal units, systems can be classified as either air systems, water systems or air-water systems. In addition, some of the system names might be commonly used in a confusing manner,more » such as “unitary system” vs. “packaged system.” Without a systematic classification, these components and system terminology can be confusing to understand or differentiate from each other, and it creates ambiguity in communication, interpretation, and documentation. It is valuable to organize and classify HVAC systems and components so that they can be easily understood and used in a consistent manner. This paper aims to develop a systematic classification of HVAC systems and components. First, we summarize the HVAC component information and definitions based on published literature, such as ASHRAE handbooks, regulations, and rating standards. Then, we identify common HVAC system types and map them to the collected components in a meaningful way. Classification charts are generated and described based on the component information. Six main categories are identified for the HVAC components and equipment, i.e., heating and cooling production, heat extraction and rejection, air handling process, distribution system, terminal use, and stand-alone system. Components for each main category are further analyzed and classified in detail. More than fifty system names are identified and grouped based on their characteristics. The result from this paper will be helpful for education, communication, and systems and component documentation.« less

Use of collateral information to improve LANDSAT classification accuracies

NASA Technical Reports Server (NTRS)

Strahler, A. H. (Principal Investigator)

1981-01-01

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

Classification of kidney and liver tissue using ultrasound backscatter data

NASA Astrophysics Data System (ADS)

Aalamifar, Fereshteh; Rivaz, Hassan; Cerrolaza, Juan J.; Jago, James; Safdar, Nabile; Boctor, Emad M.; Linguraru, Marius G.

2015-03-01

Ultrasound (US) tissue characterization provides valuable information for the initialization of automatic segmentation algorithms, and can further provide complementary information for diagnosis of pathologies. US tissue characterization is challenging due to the presence of various types of image artifacts and dependence on the sonographer's skills. One way of overcoming this challenge is by characterizing images based on the distribution of the backscatter data derived from the interaction between US waves and tissue. The goal of this work is to classify liver versus kidney tissue in 3D volumetric US data using the distribution of backscatter US data recovered from end-user displayed Bmode image available in clinical systems. To this end, we first propose the computation of a large set of features based on the homodyned-K distribution of the speckle as well as the correlation coefficients between small patches in 3D images. We then utilize the random forests framework to select the most important features for classification. Experiments on in-vivo 3D US data from nine pediatric patients with hydronephrosis showed an average accuracy of 94% for the classification of liver and kidney tissues showing a good potential of this work to assist in the classification and segmentation of abdominal soft tissue.

Video event classification and image segmentation based on noncausal multidimensional hidden Markov models.

PubMed

Ma, Xiang; Schonfeld, Dan; Khokhar, Ashfaq A

2009-06-01

In this paper, we propose a novel solution to an arbitrary noncausal, multidimensional hidden Markov model (HMM) for image and video classification. First, we show that the noncausal model can be solved by splitting it into multiple causal HMMs and simultaneously solving each causal HMM using a fully synchronous distributed computing framework, therefore referred to as distributed HMMs. Next we present an approximate solution to the multiple causal HMMs that is based on an alternating updating scheme and assumes a realistic sequential computing framework. The parameters of the distributed causal HMMs are estimated by extending the classical 1-D training and classification algorithms to multiple dimensions. The proposed extension to arbitrary causal, multidimensional HMMs allows state transitions that are dependent on all causal neighbors. We, thus, extend three fundamental algorithms to multidimensional causal systems, i.e., 1) expectation-maximization (EM), 2) general forward-backward (GFB), and 3) Viterbi algorithms. In the simulations, we choose to limit ourselves to a noncausal 2-D model whose noncausality is along a single dimension, in order to significantly reduce the computational complexity. Simulation results demonstrate the superior performance, higher accuracy rate, and applicability of the proposed noncausal HMM framework to image and video classification.

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

PubMed

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

2010-01-01

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

Seismic event classification system

DOEpatents

Dowla, F.U.; Jarpe, S.P.; Maurer, W.

1994-12-13

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities. 21 figures.

Seismic event classification system

DOEpatents

Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

1994-01-01

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Swain, P. H. (Principal Investigator); Vardeman, S. B.

1981-01-01

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

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

PubMed

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

2015-05-01

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

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

NASA Astrophysics Data System (ADS)

Wan, Yi

2011-06-01

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

Real-time distributed fiber optic sensor for security systems: Performance, event classification and nuisance mitigation

NASA Astrophysics Data System (ADS)

Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

2012-09-01

The success of any perimeter intrusion detection system depends on three important performance parameters: the probability of detection (POD), the nuisance alarm rate (NAR), and the false alarm rate (FAR). The most fundamental parameter, POD, is normally related to a number of factors such as the event of interest, the sensitivity of the sensor, the installation quality of the system, and the reliability of the sensing equipment. The suppression of nuisance alarms without degrading sensitivity in fiber optic intrusion detection systems is key to maintaining acceptable performance. Signal processing algorithms that maintain the POD and eliminate nuisance alarms are crucial for achieving this. In this paper, a robust event classification system using supervised neural networks together with a level crossings (LCs) based feature extraction algorithm is presented for the detection and recognition of intrusion and non-intrusion events in a fence-based fiber-optic intrusion detection system. A level crossings algorithm is also used with a dynamic threshold to suppress torrential rain-induced nuisance alarms in a fence system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr with the simultaneous detection of intrusion events. The use of a level crossing based detection and novel classification algorithm is also presented for a buried pipeline fiber optic intrusion detection system for the suppression of nuisance events and discrimination of intrusion events. The sensor employed for both types of systems is a distributed bidirectional fiber-optic Mach-Zehnder (MZ) interferometer.

Distinguishing between the Permeability Relationships with Absorption and Metabolism To Improve BCS and BDDCS Predictions in Early Drug Discovery

PubMed Central

2015-01-01

The biopharmaceutics classification system (BCS) and biopharmaceutics drug distribution classification system (BDDCS) are complementary classification systems that can improve, simplify, and accelerate drug discovery, development, and regulatory processes. Drug permeability has been widely accepted as a screening tool for determining intestinal absorption via the BCS during the drug development and regulatory approval processes. Currently, predicting clinically significant drug interactions during drug development is a known challenge for industry and regulatory agencies. The BDDCS, a modification of BCS that utilizes drug metabolism instead of intestinal permeability, predicts drug disposition and potential drug–drug interactions in the intestine, the liver, and most recently the brain. Although correlations between BCS and BDDCS have been observed with drug permeability rates, discrepancies have been noted in drug classifications between the two systems utilizing different permeability models, which are accepted as surrogate models for demonstrating human intestinal permeability by the FDA. Here, we recommend the most applicable permeability models for improving the prediction of BCS and BDDCS classifications. We demonstrate that the passive transcellular permeability rate, characterized by means of permeability models that are deficient in transporter expression and paracellular junctions (e.g., PAMPA and Caco-2), will most accurately predict BDDCS metabolism. These systems will inaccurately predict BCS classifications for drugs that particularly are substrates of highly expressed intestinal transporters. Moreover, in this latter case, a system more representative of complete human intestinal permeability is needed to accurately predict BCS absorption. PMID:24628254

Distinguishing between the permeability relationships with absorption and metabolism to improve BCS and BDDCS predictions in early drug discovery.

PubMed

Larregieu, Caroline A; Benet, Leslie Z

2014-04-07

The biopharmaceutics classification system (BCS) and biopharmaceutics drug distribution classification system (BDDCS) are complementary classification systems that can improve, simplify, and accelerate drug discovery, development, and regulatory processes. Drug permeability has been widely accepted as a screening tool for determining intestinal absorption via the BCS during the drug development and regulatory approval processes. Currently, predicting clinically significant drug interactions during drug development is a known challenge for industry and regulatory agencies. The BDDCS, a modification of BCS that utilizes drug metabolism instead of intestinal permeability, predicts drug disposition and potential drug-drug interactions in the intestine, the liver, and most recently the brain. Although correlations between BCS and BDDCS have been observed with drug permeability rates, discrepancies have been noted in drug classifications between the two systems utilizing different permeability models, which are accepted as surrogate models for demonstrating human intestinal permeability by the FDA. Here, we recommend the most applicable permeability models for improving the prediction of BCS and BDDCS classifications. We demonstrate that the passive transcellular permeability rate, characterized by means of permeability models that are deficient in transporter expression and paracellular junctions (e.g., PAMPA and Caco-2), will most accurately predict BDDCS metabolism. These systems will inaccurately predict BCS classifications for drugs that particularly are substrates of highly expressed intestinal transporters. Moreover, in this latter case, a system more representative of complete human intestinal permeability is needed to accurately predict BCS absorption.

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

PubMed Central

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

2002-01-01

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

A neural network approach to burst detection.

PubMed

Mounce, S R; Day, A J; Wood, A S; Khan, A; Widdop, P D; Machell, J

2002-01-01

This paper describes how hydraulic and water quality data from a distribution network may be used to provide a more efficient leakage management capability for the water industry. The research presented concerns the application of artificial neural networks to the issue of detection and location of leakage in treated water distribution systems. An architecture for an Artificial Neural Network (ANN) based system is outlined. The neural network uses time series data produced by sensors to directly construct an empirical model for predication and classification of leaks. Results are presented using data from an experimental site in Yorkshire Water's Keighley distribution system.

Curriculum Materials for "Distributive Education." Annotated Listing of Materials Available from Public Education Agencies.

ERIC Educational Resources Information Center

Bureau of Adult, Vocational, and Technical Education (DHEW/OE), Washington, DC.

This annotated listing of curriculum materials for Distributive Education provides planners, administrators, vocational educators, and others with information as to available curriculum materials developed by the various States. The materials are identified with the instructional titles and codes from the classification system of the Office of…

Investigating the Utility of Coupling Cocomo with a System Dynamics Simulation of Software Development

DTIC Science & Technology

1991-09-01

SOFTWARE DEVELOPMENT by Richard W. Smith September, 1991 Thesis Advisor: Tarek K. Abdel-Hamid Approved for public release; distribution is unlimited...REPORT Approved for public release; distribution is unlimited. 2b DECLASSIFICATION/DOWNGRADING SCHEDULE 4 PERFORMING ORGANIZATION REPORT NUMBER(S) S...exhausted SECURITY CLASSIFICATION OF THIS P (it All other edttiois are obsotete U NCLASSIFIE) Approved for public release; distribution is unlimited

A tutorial on the use of ROC analysis for computer-aided diagnostic systems.

PubMed

Scheipers, Ulrich; Perrey, Christian; Siebers, Stefan; Hansen, Christian; Ermert, Helmut

2005-07-01

The application of the receiver operating characteristic (ROC) curve for computer-aided diagnostic systems is reviewed. A statistical framework is presented and different methods of evaluating the classification performance of computer-aided diagnostic systems, and, in particular, systems for ultrasonic tissue characterization, are derived. Most classifiers that are used today are dependent on a separation threshold, which can be chosen freely in many cases. The separation threshold separates the range of output values of the classification system into different target groups, thus conducting the actual classification process. In the first part of this paper, threshold specific performance measures, e.g., sensitivity and specificity, are presented. In the second part, a threshold-independent performance measure, the area under the ROC curve, is reviewed. Only the use of separation threshold-independent performance measures provides classification results that are overall representative for computer-aided diagnostic systems. The following text was motivated by the lack of a complete and definite discussion of the underlying subject in available textbooks, references and publications. Most manuscripts published so far address the theme of performance evaluation using ROC analysis in a manner too general to be practical for everyday use in the development of computer-aided diagnostic systems. Nowadays, the user of computer-aided diagnostic systems typically handles huge amounts of numerical data, not always distributed normally. Many assumptions made in more or less theoretical works on ROC analysis are no longer valid for real-life data. The paper aims at closing the gap between theoretical works and real-life data. The review provides the interested scientist with information needed to conduct ROC analysis and to integrate algorithms performing ROC analysis into classification systems while understanding the basic principles of classification.

Local soil classification and crop suitability: Implications for the historical land use and soil management in Monti di Trapani (Sicily)

NASA Astrophysics Data System (ADS)

Garcia-Vila, Margarita; Corselli, Rocco; Bonet, María Teresa; Lopapa, Giuseppe; Pillitteri, Valentina; Fereres, Elias

2017-04-01

In the past, the lack of technologies (e.g. synthetic fertilizers) to overcome biophysical limitations has played a central role in land use planning. Thus, landscape management and agronomic practices are reactions to local knowledge and perceptions on natural resources, particularly soil. In the framework of the European research project MEMOLA (FP7), the role of local farmers knowledge and perceptions on soil for the historical land use through the spatial distribution of crops and the various management practices have been assessed in three different areas of Monti di Trapani region (Sicily). The identification of the soil classification systems of farmers and the criteria on which it is based, linked to the evaluation of the farmers' ability to identify and map the different soil types, was a key step. Nevertheless, beyond the comparison of the ethnopedological classification approach versus standard soil classification systems, the study also aims at understanding local soil management and land use decisions. The applied methodology was based on an interdisciplinary approach, combining soil science methods and participatory appraisal tools, particularly: i) semi-structured interviews; ii) soil sampling and analysis; iii) discussion groups; and iv) a workshop with local edafologists and agronomists. A rich local glossary of terms associated with the soil conditions and an own soil classification system have been identified in the region. Also, a detailed soil map, including process of soil degradation and soil capability, has been generated. This traditional soil knowledge has conditioned the management and the spatial distribution of the crops, and therefore the configuration of the landscape, until the 1990s. Acknowledgements This work has been funded by the European Union project MEMOLA (Grant agreement no: 613265).

Lava Morphology Classification of a Fast-Spreading Ridge Using Deep-Towed Sonar Data: East Pacific Rise

NASA Astrophysics Data System (ADS)

Meyer, J.; White, S.

2005-05-01

Classification of lava morphology on a regional scale contributes to the understanding of the distribution and extent of lava flows at a mid-ocean ridge. Seafloor classification is essential to understand the regional undersea environment at midocean ridges. In this study, the development of a classification scheme is found to identify and extract textural patterns of different lava morphologies along the East Pacific Rise using DSL-120 side-scan and ARGO camera imagery. Application of an accurate image classification technique to side-scan sonar allows us to expand upon the locally available visual ground reference data to make the first comprehensive regional maps of small-scale lava morphology present at a mid-ocean ridge. The submarine lava morphologies focused upon in this study; sheet flows, lobate flows, and pillow flows; have unique textures. Several algorithms were applied to the sonar backscatter intensity images to produce multiple textural image layers useful in distinguishing the different lava morphologies. The intensity and spatially enhanced images were then combined and applied to a hybrid classification technique. The hybrid classification involves two integrated classifiers, a rule-based expert system classifier and a machine learning classifier. The complementary capabilities of the two integrated classifiers provided a higher accuracy of regional seafloor classification compared to using either classifier alone. Once trained, the hybrid classifier can then be applied to classify neighboring images with relative ease. This classification technique has been used to map the lava morphology distribution and infer spatial variability of lava effusion rates along two segments of the East Pacific Rise, 17 deg S and 9 deg N. Future use of this technique may also be useful for attaining temporal information. Repeated documentation of morphology classification in this dynamic environment can be compared to detect regional seafloor change.

A Study of MX Environmental Management Information System (MXEMIS) Needs.

DTIC Science & Technology

1983-12-01

ENVIRONMENTAL MANAGEMENT INFORMATION SYSTEM (MXEMIS) NEEDS by Ronald Webster Ralph Mitchell Valorie Young -J : 2 34 LA--. Approved for public release...System (SAIFS) The MX Management Information System (MX MIS) The Mobilization Early Warning System (MEWS) The Computer-Aided Environmental Baseline...26 REFERENCES DISTRIBUTION I5 S’ t A STUDY OF MX ENVIRONMENTAL 2 EXISTING SYSTEMS CLASSIFICATION MANAGEMENT INFORMATION SYSTEM (MXEMIS

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

PubMed

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

2017-12-28

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

Molecular Phylogeny of the Widely Distributed Marine Protists, Phaeodaria (Rhizaria, Cercozoa).

PubMed

Nakamura, Yasuhide; Imai, Ichiro; Yamaguchi, Atsushi; Tuji, Akihiro; Not, Fabrice; Suzuki, Noritoshi

2015-07-01

Phaeodarians are a group of widely distributed marine cercozoans. These plankton organisms can exhibit a large biomass in the environment and are supposed to play an important role in marine ecosystems and in material cycles in the ocean. Accurate knowledge of phaeodarian classification is thus necessary to better understand marine biology, however, phylogenetic information on Phaeodaria is limited. The present study analyzed 18S rDNA sequences encompassing all existing phaeodarian orders, to clarify their phylogenetic relationships and improve their taxonomic classification. The monophyly of Phaeodaria was confirmed and strongly supported by phylogenetic analysis with a larger data set than in previous studies. The phaeodarian clade contained 11 subclades which generally did not correspond to the families and orders of the current classification system. Two families (Challengeriidae and Aulosphaeridae) and two orders (Phaeogromida and Phaeocalpida) are possibly polyphyletic or paraphyletic, and consequently the classification needs to be revised at both the family and order levels by integrative taxonomy approaches. Two morphological criteria, 1) the scleracoma type and 2) its surface structure, could be useful markers at the family level. Copyright © 2015 Elsevier GmbH. All rights reserved.

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

ISIS: A System for Fault-Tolerant Distributed Computing

DTIC Science & Technology

1986-04-01

SECURITY CLASSIMCMTIQN OP THIS PACIE S REPORT DOCUMENTATION PAGE /|^/f /^ ^^O mA \\ la REPORT SICUWTY CLASSIFICATION IS C...Mirrmteil hv me DHtense ^ilsanced ii.ttheiin n Pfnitcts Auftwv IüOD’ iiiuct \\RP\\ inier S .]7H. i ntin’ \\lt)A9<i;MS-( olj;. m<l bv ihe...DOWNGRADING SCHEDULE 3 DISTRIBUTION/AVAILABILITY OF REPORT Approved for Public Release Distribution Unlimited i PERFORMING ORGANUATION REPORT NUMBER( S

Crop classification modelling using remote sensing and environmental data in the Greater Platte River Basin, USA

USGS Publications Warehouse

Howard, Daniel M.; Wylie, Bruce K.; Tieszen, Larry L.

2012-01-01

With an ever expanding population, potential climate variability and an increasing demand for agriculture-based alternative fuels, accurate agricultural land-cover classification for specific crops and their spatial distributions are becoming critical to researchers, policymakers, land managers and farmers. It is important to ensure the sustainability of these and other land uses and to quantify the net impacts that certain management practices have on the environment. Although other quality crop classification products are often available, temporal and spatial coverage gaps can create complications for certain regional or time-specific applications. Our goal was to develop a model capable of classifying major crops in the Greater Platte River Basin (GPRB) for the post-2000 era to supplement existing crop classification products. This study identifies annual spatial distributions and area totals of corn, soybeans, wheat and other crops across the GPRB from 2000 to 2009. We developed a regression tree classification model based on 2.5 million training data points derived from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) in relation to a variety of other relevant input environmental variables. The primary input variables included the weekly 250 m US Geological Survey Earth Observing System Moderate Resolution Imaging Spectroradiometer normalized differential vegetation index, average long-term growing season temperature, average long-term growing season precipitation and yearly start of growing season. An overall model accuracy rating of 78% was achieved for a test sample of roughly 215 000 independent points that were withheld from model training. Ten 250 m resolution annual crop classification maps were produced and evaluated for the GPRB region, one for each year from 2000 to 2009. In addition to the model accuracy assessment, our validation focused on spatial distribution and county-level crop area totals in comparison with the NASS CDL and county statistics from the US Department of Agriculture (USDA) Census of Agriculture. The results showed that our model produced crop classification maps that closely resembled the spatial distribution trends observed in the NASS CDL and exhibited a close linear agreement with county-by-county crop area totals from USDA census data (R 2 = 0.90).

[Study of inversion and classification of particle size distribution under dependent model algorithm].

PubMed

Sun, Xiao-Gang; Tang, Hong; Yuan, Gui-Bin

2008-05-01

For the total light scattering particle sizing technique, an inversion and classification method was proposed with the dependent model algorithm. The measured particle system was inversed simultaneously by different particle distribution functions whose mathematic model was known in advance, and then classified according to the inversion errors. The simulation experiments illustrated that it is feasible to use the inversion errors to determine the particle size distribution. The particle size distribution function was obtained accurately at only three wavelengths in the visible light range with the genetic algorithm, and the inversion results were steady and reliable, which decreased the number of multi wavelengths to the greatest extent and increased the selectivity of light source. The single peak distribution inversion error was less than 5% and the bimodal distribution inversion error was less than 10% when 5% stochastic noise was put in the transmission extinction measurement values at two wavelengths. The running time of this method was less than 2 s. The method has advantages of simplicity, rapidity, and suitability for on-line particle size measurement.

A Scalable, Collaborative, Interactive Light-field Display System

DTIC Science & Technology

2014-06-01

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

Using Artificial Physics to Control Agents

DTIC Science & Technology

1999-11-01

unlimited 13. SUPPLEMENTARY NOTES IEEE International Conference on Information, Intelligence, and Systems, Oct 31 -Nov 3,1999. Bethesda, MD 14. ABSTRACT...distributed control can also perform distributed computation. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same...1995. [9] H. Pattee. Artificial life needs a real epistemology. In Moran, Moreno, Merelo, and Chacon , editors, Advances in Artificial Life, pages

A fuzzy automated object classification by infrared laser camera

NASA Astrophysics Data System (ADS)

Kanazawa, Seigo; Taniguchi, Kazuhiko; Asari, Kazunari; Kuramoto, Kei; Kobashi, Syoji; Hata, Yutaka

2011-06-01

Home security in night is very important, and the system that watches a person's movements is useful in the security. This paper describes a classification system of adult, child and the other object from distance distribution measured by an infrared laser camera. This camera radiates near infrared waves and receives reflected ones. Then, it converts the time of flight into distance distribution. Our method consists of 4 steps. First, we do background subtraction and noise rejection in the distance distribution. Second, we do fuzzy clustering in the distance distribution, and form several clusters. Third, we extract features such as the height, thickness, aspect ratio, area ratio of the cluster. Then, we make fuzzy if-then rules from knowledge of adult, child and the other object so as to classify the cluster to one of adult, child and the other object. Here, we made the fuzzy membership function with respect to each features. Finally, we classify the clusters to one with the highest fuzzy degree among adult, child and the other object. In our experiment, we set up the camera in room and tested three cases. The method successfully classified them in real time processing.

Low energy physical activity recognition system on smartphones.

PubMed

Soria Morillo, Luis Miguel; Gonzalez-Abril, Luis; Ortega Ramirez, Juan Antonio; de la Concepcion, Miguel Angel Alvarez

2015-03-03

An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an innovative discretization and classification technique is presented based on the χ2 distribution. Furthermore, the entire recognition process is executed on the smartphone, which determines not only the activity performed, but also the frequency at which it is carried out. These techniques and the new classification system presented reduce energy consumption caused by the activity monitoring system. The energy saved increases smartphone usage time to more than 27 h without recharging while maintaining accuracy.

Studies of volatiles and organic materials in early terrestrial and present-day outer solar system environments

NASA Technical Reports Server (NTRS)

Sagan, Carl; Thompson, W. Reid; Chyba, Christopher F.; Khare, B. N.

1991-01-01

A review and partial summary of projects within several areas of research generally involving the origin, distribution, chemistry, and spectral/dielectric properties of volatiles and organic materials in the outer solar system and early terrestrial environments are presented. The major topics covered include: (1) impact delivery of volatiles and organic compounds to the early terrestrial planets; (2) optical constants measurements; (3) spectral classification, chemical processes, and distribution of materials; and (4) radar properties of ice, hydrocarbons, and organic heteropolymers.

Modeling occupancy distribution in large spaces with multi-feature classification algorithm

DOE PAGES

Wang, Wei; Chen, Jiayu; Hong, Tianzhen

2018-04-07

We present that occupancy information enables robust and flexible control of heating, ventilation, and air-conditioning (HVAC) systems in buildings. In large spaces, multiple HVAC terminals are typically installed to provide cooperative services for different thermal zones, and the occupancy information determines the cooperation among terminals. However, a person count at room-level does not adequately optimize HVAC system operation due to the movement of occupants within the room that creates uneven load distribution. Without accurate knowledge of the occupants’ spatial distribution, the uneven distribution of occupants often results in under-cooling/heating or over-cooling/heating in some thermal zones. Therefore, the lack of high-resolutionmore » occupancy distribution is often perceived as a bottleneck for future improvements to HVAC operation efficiency. To fill this gap, this study proposes a multi-feature k-Nearest-Neighbors (k-NN) classification algorithm to extract occupancy distribution through reliable, low-cost Bluetooth Low Energy (BLE) networks. An on-site experiment was conducted in a typical office of an institutional building to demonstrate the proposed methods, and the experiment outcomes of three case studies were examined to validate detection accuracy. One method based on City Block Distance (CBD) was used to measure the distance between detected occupancy distribution and ground truth and assess the results of occupancy distribution. Finally, the results show the accuracy when CBD = 1 is over 71.4% and the accuracy when CBD = 2 can reach up to 92.9%.« less

Modeling occupancy distribution in large spaces with multi-feature classification algorithm

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

Wang, Wei; Chen, Jiayu; Hong, Tianzhen

We present that occupancy information enables robust and flexible control of heating, ventilation, and air-conditioning (HVAC) systems in buildings. In large spaces, multiple HVAC terminals are typically installed to provide cooperative services for different thermal zones, and the occupancy information determines the cooperation among terminals. However, a person count at room-level does not adequately optimize HVAC system operation due to the movement of occupants within the room that creates uneven load distribution. Without accurate knowledge of the occupants’ spatial distribution, the uneven distribution of occupants often results in under-cooling/heating or over-cooling/heating in some thermal zones. Therefore, the lack of high-resolutionmore » occupancy distribution is often perceived as a bottleneck for future improvements to HVAC operation efficiency. To fill this gap, this study proposes a multi-feature k-Nearest-Neighbors (k-NN) classification algorithm to extract occupancy distribution through reliable, low-cost Bluetooth Low Energy (BLE) networks. An on-site experiment was conducted in a typical office of an institutional building to demonstrate the proposed methods, and the experiment outcomes of three case studies were examined to validate detection accuracy. One method based on City Block Distance (CBD) was used to measure the distance between detected occupancy distribution and ground truth and assess the results of occupancy distribution. Finally, the results show the accuracy when CBD = 1 is over 71.4% and the accuracy when CBD = 2 can reach up to 92.9%.« less

New feature extraction method for classification of agricultural products from x-ray images

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.; Lee, Ha-Woon; Keagy, Pamela M.; Schatzki, Thomas F.

1999-01-01

Classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non- invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items. This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discrimination between damaged and clean items. This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work the MRDF is applied to standard features. The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC data.

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

PubMed

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

2005-01-01

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

Methods in hair research: how to objectively distinguish between anagen and catagen in human hair follicle organ culture.

PubMed

Kloepper, Jennifer Elisabeth; Sugawara, Koji; Al-Nuaimi, Yusur; Gáspár, Erzsébet; van Beek, Nina; Paus, Ralf

2010-03-01

The organ culture of human scalp hair follicles (HFs) is the best currently available assay for hair research in the human system. In order to determine the hair growth-modulatory effects of agents in this assay, one critical read-out parameter is the assessment of whether the test agent has prolonged anagen duration or induced catagen in vitro. However, objective criteria to distinguish between anagen VI HFs and early catagen in human HF organ culture, two hair cycle stages with a deceptively similar morphology, remain to be established. Here, we develop, document and test an objective classification system that allows to distinguish between anagen VI and early catagen in organ-cultured human HFs, using both qualitative and quantitative parameters that can be generated by light microscopy or immunofluorescence. Seven qualitative classification criteria are defined that are based on assessing the morphology of the hair matrix, the dermal papilla and the distribution of pigmentary markers (melanin, gp100). These are complemented by ten quantitative parameters. We have tested this classification system by employing the clinically used topical hair growth inhibitor, eflornithine, and show that eflornithine indeed produces the expected premature catagen induction, as identified by the novel classification criteria reported here. Therefore, this classification system offers a standardized, objective and reproducible new experimental method to reliably distinguish between human anagen VI and early catagen HFs in organ culture.

New insight into defining the lakes of the southern Baltic coastal zone.

PubMed

Cieśliński, Roman; Olszewska, Alicja

2018-01-29

There exist many classification systems of hydrographic entities such as lakes found along the coastlines of seas and oceans. Each system has its advantages and can be used with some success in the area of protection and management. This paper aims to evaluate whether the studied lakes are only coastal lakes or rather bodies of water of a completely different hydrological and hydrochemical nature. The attempt to create a new classification system of Polish coastal lakes is related to the incompleteness of lake information in existing classifications. Thus far, the most frequently used are classifications based solely on lake basin morphogenesis or hydrochemical properties. The classifications in this paper are based not only on the magnitude of lake water salinity or hydrochemical analysis but also on isolation from the Baltic Sea and other sources of water. The key element of the new classification system for coastal bodies of water is a departure from the existing system used to classify lakes in Poland and the introduction of ion-"tracking" methods designed to identify anion and cation distributions in each body of water of interest. As a result of the work, a new classification of lakes of the southern Baltic Sea coastal zone was created. Featured objects such as permanently brackish lakes, brackish lakes that may turn into freshwater lakes from time to time, freshwater lakes that may turn into brackish lakes from time to time, freshwater lakes that experience low levels of salinity due to specific incidents, and permanently freshwater lakes. The authors have adopted 200 mg Cl -  dm -3 as a maximum value of lake water salinity. There are many conditions that determine the membership of a lake to a particular group, but the most important is the isolation lakes from the Baltic Sea. Changing a condition may change the classification of a lake.

Multinomial mixture model with heterogeneous classification probabilities

USGS Publications Warehouse

Holland, M.D.; Gray, B.R.

2011-01-01

Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.

An Evolving Digital Telecommunications Industry and Its Impact on the Operational Environment of the Nationwide Emergency Telecommunication System (NETS).

DTIC Science & Technology

1985-03-01

005 4-, /nImII 1 liIm ulnli iiliiii I I UNCLASSIFIED SECURITY CLASSIFICATION OF TNIS PAGE ("on Data Bnter6t0 REPORT DOCUMENTATION PAGE READ...II different from ControllIng Office) 15. SECURITY CLASS (of thin report) Unclassified IS. OECLASSIFICATION/ DOWNGRADING SCMEDULE 1. DISTRIBUTION...EDITION OF I NOV 65 IS OBSOLETE UNCLASSIFIED N0102LF-0146601 1 UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (When Dote wrteed) ,IA UNCLASSIFIED

Theoretical Studies of Small-System Thermodynamics in Energetic Materials

DTIC Science & Technology

2016-01-06

SECURITY CLASSIFICATION OF: This is a comprehensive theoretical research program to investigate the fundamental principles of small-system thermodynamics ...a.k.a. nanothermodynamics). The proposed work is motivated by our desire to better understand the fundamental dynamics and thermodynamics of...for Public Release; Distribution Unlimited Final Report: Theoretical Studies of Small-System Thermodynamics in Energetic Materials The views, opinions

Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Badhwar, G.

1980-01-01

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Reliability testing of the Larsen and Sharp classifications for rheumatoid arthritis of the elbow.

PubMed

Jew, Nicholas B; Hollins, Anthony M; Mauck, Benjamin M; Smith, Richard A; Azar, Frederick M; Miller, Robert H; Throckmorton, Thomas W

2017-01-01

Two popular systems for classifying rheumatoid arthritis affecting the elbow are the Larsen and Sharp schemes. To our knowledge, no study has investigated the reliability of these 2 systems. We compared the intraobserver and interobserver agreement of the 2 systems to determine whether one is more reliable than the other. The radiographs of 45 patients diagnosed with rheumatoid arthritis affecting the elbow were evaluated. Anteroposterior and lateral radiographs were deidentified and distributed to 6 evaluators (4 fellowship-trained upper extremity surgeons and 2 orthopedic trainees). Each evaluator graded all 45 radiographs according to the Larsen and Sharp scoring methods on 2 occasions, at least 2 weeks apart. Overall intraobserver reliability was 0.93 (95% confidence interval [CI], 0.90-0.95) for the Larsen system and 0.92 (95% CI, 0.86-0.96) for the Sharp classification, both indicating substantial agreement. Overall interobserver reliability was 0.70 (95% CI, 0.60-0.80) for the Larsen classification and 0.68 (95% CI, 0.54-0.81) for the Sharp system, both indicating good agreement. There were no significant differences in the intraobserver or interobserver reliability of the systems overall and no significant differences in reliability between attending surgeons and trainees for either classification system. The Larsen and Sharp systems both show substantial intraobserver reliability and good interobserver agreement for the radiographic classification of rheumatoid arthritis affecting the elbow. Differences in training level did not result in substantial variances in reliability for either system. We conclude that both systems can be reliably used to evaluate rheumatoid arthritis of the elbow by observers of varying training levels. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Complexity, Robustness, and Multistability in Network Systems with Switching Topologies: A Hierarchical Hybrid Control Approach

DTIC Science & Technology

2015-05-22

sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor

Time frequency analysis for automated sleep stage identification in fullterm and preterm neonates.

PubMed

Fraiwan, Luay; Lweesy, Khaldon; Khasawneh, Natheer; Fraiwan, Mohammad; Wenz, Heinrich; Dickhaus, Hartmut

2011-08-01

This work presents a new methodology for automated sleep stage identification in neonates based on the time frequency distribution of single electroencephalogram (EEG) recording and artificial neural networks (ANN). Wigner-Ville distribution (WVD), Hilbert-Hough spectrum (HHS) and continuous wavelet transform (CWT) time frequency distributions were used to represent the EEG signal from which features were extracted using time frequency entropy. The classification of features was done using feed forward back-propagation ANN. The system was trained and tested using data taken from neonates of post-conceptual age of 40 weeks for both preterm (14 recordings) and fullterm (15 recordings). The identification of sleep stages was successfully implemented and the classification based on the WVD outperformed the approaches based on CWT and HHS. The accuracy and kappa coefficient were found to be 0.84 and 0.65 respectively for the fullterm neonates' recordings and 0.74 and 0.50 respectively for preterm neonates' recordings.

Bidirectional reflectance distribution function based surface modeling of non-Lambertian using intensity data of light detection and ranging.

PubMed

Li, Xiaolu; Liang, Yu; Xu, Lijun

2014-09-01

To provide a credible model for light detection and ranging (LiDAR) target classification, the focus of this study is on the relationship between intensity data of LiDAR and the bidirectional reflectance distribution function (BRDF). An integration method based on the built-in-lab coaxial laser detection system was advanced. A kind of intermediary BRDF model advanced by Schlick was introduced into the integration method, considering diffuse and specular backscattering characteristics of the surface. A group of measurement campaigns were carried out to investigate the influence of the incident angle and detection range on the measured intensity data. Two extracted parameters r and S(λ) are influenced by different surface features, which illustrate the surface features of the distribution and magnitude of reflected energy, respectively. The combination of two parameters can be used to describe the surface characteristics for target classification in a more plausible way.

The Fracture Project

DTIC Science & Technology

2017-09-01

report was cleared for public release by the 88th ABW, Wright-Patterson AFB Public Affairs Office and is available to the general public, including...AFRL/RI 11. SPONSOR/MONITOR’S REPORT NUMBER AFRL-RI-RS-TR-2017-178 12. DISTRIBUTION AVAILABILITY STATEMENT Approved for Public Release; Distribution...Formal Verification, Red Team, High Assurance Cyber Military Systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES

Status, Vision, and Challenges of an Intelligent Distributed Engine Control Architecture (Postprint)

DTIC Science & Technology

2007-09-18

TERMS turbine engine control, engine health management, FADEC , Universal FADEC , Distributed Controls, UF, UF Platform, common FADEC , Generic FADEC ...Modular FADEC , Adaptive Control 16. SECURITY CLASSIFICATION OF: 19a. NAME OF RESPONSIBLE PERSON (Monitor) a. REPORT Unclassified b. ABSTRACT...Eventually the Full Authority Digital Electronic Control ( FADEC ) became the norm. Presently, this control system architecture accounts for 15 to 20% of

Co-Adaptive Aiding and Automation Enhance Operator Performance

DTIC Science & Technology

2013-03-01

activation system. There is a close relation between physiologically activated adaptive aiding and brain- computer interfaces ( BCI ). BCI here refers...classification of EEG signals (Farwell & Donchin, 1988). Physiologically activated adaptive aiding is, in a sense, a special case of BCI wherein the...as passive BCI , e.g. Zander, Kothe, Jatzev, & 3 Distribution A: Approved for public release; distribution unlimited. 88 ABW Cleared 05/13/2013

A Distributed Artificial Intelligence Approach To Object Identification And Classification

NASA Astrophysics Data System (ADS)

Sikka, Digvijay I.; Varshney, Pramod K.; Vannicola, Vincent C.

1989-09-01

This paper presents an application of Distributed Artificial Intelligence (DAI) tools to the data fusion and classification problem. Our approach is to use a blackboard for information management and hypothe-ses formulation. The blackboard is used by the knowledge sources (KSs) for sharing information and posting their hypotheses on, just as experts sitting around a round table would do. The present simulation performs classification of an Aircraft(AC), after identifying it by its features, into disjoint sets (object classes) comprising of the five commercial ACs; Boeing 747, Boeing 707, DC10, Concord and Boeing 727. A situation data base is characterized by experimental data available from the three levels of expert reasoning. Ohio State University ElectroScience Laboratory provided this experimental data. To validate the architecture presented, we employ two KSs for modeling the sensors, aspect angle polarization feature and the ellipticity data. The system has been implemented on Symbolics 3645, under Genera 7.1, in Common LISP.

Threshold of toxicological concern values for non-genotoxic effects in industrial chemicals: re-evaluation of the Cramer classification.

PubMed

Kalkhof, H; Herzler, M; Stahlmann, R; Gundert-Remy, U

2012-01-01

The TTC concept employs available data from animal testing to derive a distribution of NOAELs. Taking a probabilistic view, the 5th percentile of the distribution is taken as a threshold value for toxicity. In this paper, we use 824 NOAELs from repeated dose toxicity studies of industrial chemicals to re-evaluate the currently employed TTC values, which have been derived for substances grouped according to the Cramer scheme (Cramer et al. in Food Cosm Toxicol 16:255-276, 1978) by Munro et al. (Food Chem Toxicol 34:829-867, 1996) and refined by Kroes and Kozianowski (Toxicol Lett 127:43-46, 2002), Kroes et al. 2000. In our data set, consisting of 756 NOAELs from 28-day repeated dose testing and 57 NOAELs from 90-days repeated dose testing, the experimental NOAEL had to be extrapolated to chronic TTC using regulatory accepted extrapolation factors. The TTC values derived from our data set were higher than the currently used TTC values confirming the safety of the latter. We analysed the prediction of the Cramer classification by comparing the classification by this tool with the guidance values for classification according to the Globally Harmonised System of classification and labelling of the United Nations (GHS). Nearly 90% of the chemicals were in Cramer class 3 and assumed as highly toxic compared to 22% according to the GHS. The Cramer classification does underestimate the toxicity of chemicals only in 4.6% of the cases. Hence, from a regulatory perspective, the Cramer classification scheme might be applied as it overestimates hazard of a chemical.

Numeric pathologic lymph node classification shows prognostic superiority to topographic pN classification in esophageal squamous cell carcinoma.

PubMed

Sugawara, Kotaro; Yamashita, Hiroharu; Uemura, Yukari; Mitsui, Takashi; Yagi, Koichi; Nishida, Masato; Aikou, Susumu; Mori, Kazuhiko; Nomura, Sachiyo; Seto, Yasuyuki

2017-10-01

The current eighth tumor node metastasis lymph node category pathologic lymph node staging system for esophageal squamous cell carcinoma is based solely on the number of metastatic nodes and does not consider anatomic distribution. We aimed to assess the prognostic capability of the eighth tumor node metastasis pathologic lymph node staging system (numeric-based) compared with the 11th Japan Esophageal Society (topography-based) pathologic lymph node staging system in patients with esophageal squamous cell carcinoma. We retrospectively reviewed the clinical records of 289 patients with esophageal squamous cell carcinoma who underwent esophagectomy with extended lymph node dissection during the period from January 2006 through June 2016. We compared discrimination abilities for overall survival, recurrence-free survival, and cancer-specific survival between these 2 staging systems using C-statistics. The median number of dissected and metastatic nodes was 61 (25% to 75% quartile range, 45 to 79) and 1 (25% to 75% quartile range, 0 to 3), respectively. The eighth tumor node metastasis pathologic lymph node staging system had a greater ability to accurately determine overall survival (C-statistics: tumor node metastasis classification, 0.69, 95% confidence interval, 0.62-0.76; Japan Esophageal Society classification; 0.65, 95% confidence interval, 0.58-0.71; P = .014) and cancer-specific survival (C-statistics: tumor node metastasis classification, 0.78, 95% confidence interval, 0.70-0.87; Japan Esophageal Society classification; 0.72, 95% confidence interval, 0.64-0.80; P = .018). Rates of total recurrence rose as the eighth tumor node metastasis pathologic lymph node stage increased, while stratification of patients according to the topography-based node classification system was not feasible. Numeric nodal staging is an essential tool for stratifying the oncologic outcomes of patients with esophageal squamous cell carcinoma even in the cohort in which adequate numbers of lymph nodes were harvested. Copyright © 2017 Elsevier Inc. All rights reserved.

Breast density characterization using texton distributions.

PubMed

Petroudi, Styliani; Brady, Michael

2011-01-01

Breast density has been shown to be one of the most significant risks for developing breast cancer, with women with dense breasts at four to six times higher risk. The Breast Imaging Reporting and Data System (BI-RADS) has a four class classification scheme that describes the different breast densities. However, there is great inter and intra observer variability among clinicians in reporting a mammogram's density class. This work presents a novel texture classification method and its application for the development of a completely automated breast density classification system. The new method represents the mammogram using textons, which can be thought of as the building blocks of texture under the operational definition of Leung and Malik as clustered filter responses. The new proposed method characterizes the mammographic appearance of the different density patterns by evaluating the texton spatial dependence matrix (TDSM) in the breast region's corresponding texton map. The TSDM is a texture model that captures both statistical and structural texture characteristics. The normalized TSDM matrices are evaluated for mammograms from the different density classes and corresponding texture models are established. Classification is achieved using a chi-square distance measure. The fully automated TSDM breast density classification method is quantitatively evaluated on mammograms from all density classes from the Oxford Mammogram Database. The incorporation of texton spatial dependencies allows for classification accuracy reaching over 82%. The breast density classification accuracy is better using texton TSDM compared to simple texton histograms.

Guidance for Determining the Acceptability of Environmental Fate Studies Conducted with Foreign Soils

EPA Pesticide Factsheets

International and U.S. soil taxonomical classification systems, distribution of soil orders in the United States, specific criteria to help scientists determine when foreign soils are representative of U.S. soils at intended pesticide use sites.

Cooperative Learning for Distributed In-Network Traffic Classification

NASA Astrophysics Data System (ADS)

Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

2017-04-01

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

Empirical Analysis and Automated Classification of Security Bug Reports

NASA Technical Reports Server (NTRS)

Tyo, Jacob P.

2016-01-01

With the ever expanding amount of sensitive data being placed into computer systems, the need for effective cybersecurity is of utmost importance. However, there is a shortage of detailed empirical studies of security vulnerabilities from which cybersecurity metrics and best practices could be determined. This thesis has two main research goals: (1) to explore the distribution and characteristics of security vulnerabilities based on the information provided in bug tracking systems and (2) to develop data analytics approaches for automatic classification of bug reports as security or non-security related. This work is based on using three NASA datasets as case studies. The empirical analysis showed that the majority of software vulnerabilities belong only to a small number of types. Addressing these types of vulnerabilities will consequently lead to cost efficient improvement of software security. Since this analysis requires labeling of each bug report in the bug tracking system, we explored using machine learning to automate the classification of each bug report as a security or non-security related (two-class classification), as well as each security related bug report as specific security type (multiclass classification). In addition to using supervised machine learning algorithms, a novel unsupervised machine learning approach is proposed. An ac- curacy of 92%, recall of 96%, precision of 92%, probability of false alarm of 4%, F-Score of 81% and G-Score of 90% were the best results achieved during two-class classification. Furthermore, an accuracy of 80%, recall of 80%, precision of 94%, and F-score of 85% were the best results achieved during multiclass classification.

Digital processing of satellite imagery application to jungle areas of Peru

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

PubMed

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

2013-11-01

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

High-Assurance Spiral

DTIC Science & Technology

2017-11-01

Public Release; Distribution Unlimited. PA# 88ABW-2017-5388 Date Cleared: 30 OCT 2017 13. SUPPLEMENTARY NOTES 14. ABSTRACT Cyber- physical systems... physical processes that interact in intricate manners. This makes verification of the software complex and unwieldy. In this report, an approach towards...resulting implementations. 15. SUBJECT TERMS Cyber- physical systems, Formal guarantees, Code generation 16. SECURITY CLASSIFICATION OF: 17

Disposal of Chemotherapeutic Agent -- Contaminated Waste

DTIC Science & Technology

1989-03-01

RESTRICTIVE MARKINGS 2a SECURITY CLASSIFICATION AUTHORITY 3 . DISTRIBUTION/AVAILABILITY OF REPORT 2b. DECLASSIFICATION/DOWNGRADING SCHEDULE Approved for Public...AIR .............. 22 INCINERATION SYSTEM 2 CHEMOTHERAPEUTIC WASTE THERMAL ...... 32 DESTRUCTION DISPOSAL SYSTEM 3 FRONT VIEW OF INCINERATION...The Environmental Protection Agency has published a manual (Reference 1) which provides guidelines on handling and 3 disposal of infectious waste from

[Characteristic study on village landscape patterns in Sichuan Basin hilly region based on high resolution IKONOS remote sensing].

PubMed

Li, Shoucheng; Liu, Wenquan; Cheng, Xu; Ellis, Erle C

2005-10-01

To realize the landscape programming of agro-ecosystem management, landscape-stratification can provide us the best understanding of landscape ecosystem at very detailed scales. For this purpose, the village landscapes in densely populated Jintang and Jianyang Counties of Sichuan Basin hilly region were mapped from high resolution (1 m) IKONOS satellite imagery by using a standardized 4 level ecological landscape classification and mapping system in a regionally-representative sample of five 500 x 500 m2 landscape quadrats (sample plots). Based on these maps, the spatial patterns were analyzed by landscape indicators, which demonstrated a large variety of landscape types or ecotopes across the village landscape of this region, with diversity indexes ranging from 1.08 to 2.26 at different levels of the landscape classification system. The richness indices ranged from 42.2% to 58.6 %, except that for the landcover at 85 %. About 12.5 % of the ecotopes were distributed in the same way in each landscape sample, and the remaining 87.5% were distributed differently. The landscape fragmentation indices varied from 2.93 to 4.27 across sample plots, and from 2.86 to 5.63 across classification levels. The population density and the road and hamlet areas had strong linear correlations with some landscape indicators, and especially, the correlation coefficients of hamlet areas with fractal indexes and fragmental dimensions were 0.957* and 0.991**, respectively. The differences in most landscape pattern indices across sample plots and landscape classes were statistically significant, indicating that cross-scale mapping and classification of village landscapes could provide more detailed information on landscape patterns than those from a single level of classification.

Seizures, syndromes, and etiologies in childhood epilepsy: The International League Against Epilepsy 1981, 1989, and 2017 classifications used in a population-based cohort.

PubMed

Aaberg, Kari Modalsli; Surén, Pål; Søraas, Camilla Lund; Bakken, Inger Johanne; Lossius, Morten I; Stoltenberg, Camilla; Chin, Richard

2017-11-01

The study provides updated information about the distribution of seizures, epilepsies, and etiologies of epilepsy in the general child population, and compares the old and new classification systems from the International League Against Epilepsy (ILAE). The study platform was the Norwegian Mother and Child Cohort Study. Cases of epilepsy were identified through registry linkages and sequential parental questionnaires. Epilepsy diagnoses were validated using a standardized protocol, and seizures, epilepsies, and etiologies were classified according to the old (ILAE 1981/1989) and new (ILAE 2017) classifications. Information was collected through medical record reviews and/or parental telephone interviews. The study population included 112,744 children aged 3-13 years at the end of follow-up on December 31, 2012. Of these, there were 606 children with epilepsy (CWE). Distribution of seizure types varied by age of onset. Multiple seizure types were common with early onset. Focal epilepsies were the most common, occurring in 317 per 100,000 children in the study population and in 59% of CWE. Generalized epilepsies were found in 190 per 100,000 (35% of CWE). CWE with onset during the first 2 years of life had an even distribution of focal and generalized epilepsies, whereas focal epilepsies became dominant at later ages of onset. A definite cause of epilepsy had been demonstrated in 33% of CWE. The ILAE 1989 classification allowed for a broad syndrome category in 93% of CWE and a defined epileptic syndrome in 37%. With the ILAE 2017 classification, 41% of CWE had a defined epileptic syndrome and 63% had either a defined syndrome or structural-metabolic etiology. The distribution of seizures and epilepsies is strongly dependent on age of onset. Despite diagnostic advances, the causes of epilepsy are still unknown in two-thirds of CWE. The ILAE 2017 classifications allow for a higher precision of diagnoses, but at the expense of leaving more epilepsies classifiable only at the mode of onset level. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Research on simulation based material delivery system for an automobile company with multi logistics center

NASA Astrophysics Data System (ADS)

Luo, D.; Guan, Z.; Wang, C.; Yue, L.; Peng, L.

2017-06-01

Distribution of different parts to the assembly lines is significant for companies to improve production. Current research investigates the problem of distribution method optimization of a logistics system in a third party logistic company that provide professional services to an automobile manufacturing case company in China. Current research investigates the logistics leveling the material distribution and unloading platform of the automobile logistics enterprise and proposed logistics distribution strategy, material classification method, as well as logistics scheduling. Moreover, the simulation technology Simio is employed on assembly line logistics system which helps to find and validate an optimization distribution scheme through simulation experiments. Experimental results indicate that the proposed scheme can solve the logistic balance and levels the material problem and congestion of the unloading pattern in an efficient way as compared to the original method employed by the case company.

Subtlenoise: sonification of distributed computing operations

NASA Astrophysics Data System (ADS)

Love, P. A.

2015-12-01

The operation of distributed computing systems requires comprehensive monitoring to ensure reliability and robustness. There are two components found in most monitoring systems: one being visually rich time-series graphs and another being notification systems for alerting operators under certain pre-defined conditions. In this paper the sonification of monitoring messages is explored using an architecture that fits easily within existing infrastructures based on mature opensource technologies such as ZeroMQ, Logstash, and Supercollider (a synth engine). Message attributes are mapped onto audio attributes based on broad classification of the message (continuous or discrete metrics) but keeping the audio stream subtle in nature. The benefits of audio rendering are described in the context of distributed computing operations and may provide a less intrusive way to understand the operational health of these systems.

40 CFR 152.167 - Distribution and sale of restricted use products.

Code of Federal Regulations, 2012 CFR

2012-07-01

... (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.167 Distribution and sale of restricted use products. Unless modified by the Agency, the...

40 CFR 152.167 - Distribution and sale of restricted use products.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.167 Distribution and sale of restricted use products. Unless modified by the Agency, the...

40 CFR 152.167 - Distribution and sale of restricted use products.

Code of Federal Regulations, 2014 CFR

2014-07-01

... (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.167 Distribution and sale of restricted use products. Unless modified by the Agency, the...

40 CFR 152.167 - Distribution and sale of restricted use products.

Code of Federal Regulations, 2013 CFR

2013-07-01

... (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.167 Distribution and sale of restricted use products. Unless modified by the Agency, the...

40 CFR 152.167 - Distribution and sale of restricted use products.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (CONTINUED) PESTICIDE PROGRAMS PESTICIDE REGISTRATION AND CLASSIFICATION PROCEDURES Classification of Pesticides § 152.167 Distribution and sale of restricted use products. Unless modified by the Agency, the...

An inter-comparison of similarity-based methods for organisation and classification of groundwater hydrographs

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Barthel, Roland

2018-04-01

Classification and similarity based methods, which have recently received major attention in the field of surface water hydrology, namely through the PUB (prediction in ungauged basins) initiative, have not yet been applied to groundwater systems. However, it can be hypothesised, that the principle of "similar systems responding similarly to similar forcing" applies in subsurface hydrology as well. One fundamental prerequisite to test this hypothesis and eventually to apply the principle to make "predictions for ungauged groundwater systems" is efficient methods to quantify the similarity of groundwater system responses, i.e. groundwater hydrographs. In this study, a large, spatially extensive, as well as geologically and geomorphologically diverse dataset from Southern Germany and Western Austria was used, to test and compare a set of 32 grouping methods, which have previously only been used individually in local-scale studies. The resulting groupings are compared to a heuristic visual classification, which serves as a baseline. A performance ranking of these classification methods is carried out and differences in homogeneity of grouping results were shown, whereby selected groups were related to hydrogeological indices and geological descriptors. This exploratory empirical study shows that the choice of grouping method has a large impact on the object distribution within groups, as well as on the homogeneity of patterns captured in groups. The study provides a comprehensive overview of a large number of grouping methods, which can guide researchers when attempting similarity-based groundwater hydrograph classification.

Comparing ecoregional classifications for natural areas management in the Klamath Region, USA

USGS Publications Warehouse

Sarr, Daniel A.; Duff, Andrew; Dinger, Eric C.; Shafer, Sarah L.; Wing, Michael; Seavy, Nathaniel E.; Alexander, John D.

2015-01-01

We compared three existing ecoregional classification schemes (Bailey, Omernik, and World Wildlife Fund) with two derived schemes (Omernik Revised and Climate Zones) to explore their effectiveness in explaining species distributions and to better understand natural resource geography in the Klamath Region, USA. We analyzed presence/absence data derived from digital distribution maps for trees, amphibians, large mammals, small mammals, migrant birds, and resident birds using three statistical analyses of classification accuracy (Analysis of Similarity, Canonical Analysis of Principal Coordinates, and Classification Strength). The classifications were roughly comparable in classification accuracy, with Omernik Revised showing the best overall performance. Trees showed the strongest fidelity to the classifications, and large mammals showed the weakest fidelity. We discuss the implications for regional biogeography and describe how intermediate resolution ecoregional classifications may be appropriate for use as natural areas management domains.

Photometry and Classification of Stars around the Reflection Nebula NGC 7023 IN Cepheus. II. Interstellar Extinction and Cloud Distances

NASA Astrophysics Data System (ADS)

Zdanavičius, K.; Zdanavičius, J.; Straižys, V.; Maskoliūnas, M.

Interstellar extinction is investigated in a 1.5 square degree area in the direction of the reflection nebula NGC 7023 at ℓ = 104.1\\degr, b = +14.2\\degr. The study is based on photometric classification and the determination of interstellar extinctions and distances of 480 stars down to V = 16.5 mag from photometry in the Vilnius seven-color system published in Paper I (2008). The investigated area is divided into five smaller subareas with slightly different dependence of the extinction on distance. The distribution of reddened stars is in accordance with the presence of two dust clouds at 282 pc and 715 pc, however in some directions the dust distribution can be continuous or more clouds can be present.

Adaptive distributed outlier detection for WSNs.

PubMed

De Paola, Alessandra; Gaglio, Salvatore; Lo Re, Giuseppe; Milazzo, Fabrizio; Ortolani, Marco

2015-05-01

The paradigm of pervasive computing is gaining more and more attention nowadays, thanks to the possibility of obtaining precise and continuous monitoring. Ease of deployment and adaptivity are typically implemented by adopting autonomous and cooperative sensory devices; however, for such systems to be of any practical use, reliability and fault tolerance must be guaranteed, for instance by detecting corrupted readings amidst the huge amount of gathered sensory data. This paper proposes an adaptive distributed Bayesian approach for detecting outliers in data collected by a wireless sensor network; our algorithm aims at optimizing classification accuracy, time complexity and communication complexity, and also considering externally imposed constraints on such conflicting goals. The performed experimental evaluation showed that our approach is able to improve the considered metrics for latency and energy consumption, with limited impact on classification accuracy.

Some sequential, distribution-free pattern classification procedures with applications

NASA Technical Reports Server (NTRS)

Poage, J. L.

1971-01-01

Some sequential, distribution-free pattern classification techniques are presented. The decision problem to which the proposed classification methods are applied is that of discriminating between two kinds of electroencephalogram responses recorded from a human subject: spontaneous EEG and EEG driven by a stroboscopic light stimulus at the alpha frequency. The classification procedures proposed make use of the theory of order statistics. Estimates of the probabilities of misclassification are given. The procedures were tested on Gaussian samples and the EEG responses.

12 CFR 1229.5 - Capital distributions for adequately capitalized Banks.

Code of Federal Regulations, 2010 CFR

2010-01-01

... CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.5 Capital... classification of adequately capitalized. A Bank may not make a capital distribution if such distribution would... redeem its shares of stock if the transaction is made in connection with the issuance of additional Bank...

Scalable Mobile Ad Hoc Network (MANET) to Enhance Situational Awareness in Distributed Small Unit Operations

DTIC Science & Technology

2015-06-01

raspberry pi , robotic operation system (ros), arduino 15. NUMBER OF PAGES 123 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...51  2.  Raspberry Pi ...52  Figure 21.  The Raspberry Pi B+ model, from [24

Quantitation of flavonoid constituents in citrus fruits.

PubMed

Kawaii, S; Tomono, Y; Katase, E; Ogawa, K; Yano, M

1999-09-01

Twenty-four flavonoids have been determined in 66 Citrus species and near-citrus relatives, grown in the same field and year, by means of reversed phase high-performance liquid chromatography analysis. Statistical methods have been applied to find relations among the species. The F ratios of 21 flavonoids obtained by applying ANOVA analysis are significant, indicating that a classification of the species using these variables is reasonable to pursue. Principal component analysis revealed that the distributions of Citrus species belonging to different classes were largely in accordance with Tanaka's classification system.

A Directed Acyclic Graph-Large Margin Distribution Machine Model for Music Symbol Classification

PubMed Central

Wen, Cuihong; Zhang, Jing; Rebelo, Ana; Cheng, Fanyong

2016-01-01

Optical Music Recognition (OMR) has received increasing attention in recent years. In this paper, we propose a classifier based on a new method named Directed Acyclic Graph-Large margin Distribution Machine (DAG-LDM). The DAG-LDM is an improvement of the Large margin Distribution Machine (LDM), which is a binary classifier that optimizes the margin distribution by maximizing the margin mean and minimizing the margin variance simultaneously. We modify the LDM to the DAG-LDM to solve the multi-class music symbol classification problem. Tests are conducted on more than 10000 music symbol images, obtained from handwritten and printed images of music scores. The proposed method provides superior classification capability and achieves much higher classification accuracy than the state-of-the-art algorithms such as Support Vector Machines (SVMs) and Neural Networks (NNs). PMID:26985826

A Directed Acyclic Graph-Large Margin Distribution Machine Model for Music Symbol Classification.

PubMed

Wen, Cuihong; Zhang, Jing; Rebelo, Ana; Cheng, Fanyong

2016-01-01

Optical Music Recognition (OMR) has received increasing attention in recent years. In this paper, we propose a classifier based on a new method named Directed Acyclic Graph-Large margin Distribution Machine (DAG-LDM). The DAG-LDM is an improvement of the Large margin Distribution Machine (LDM), which is a binary classifier that optimizes the margin distribution by maximizing the margin mean and minimizing the margin variance simultaneously. We modify the LDM to the DAG-LDM to solve the multi-class music symbol classification problem. Tests are conducted on more than 10000 music symbol images, obtained from handwritten and printed images of music scores. The proposed method provides superior classification capability and achieves much higher classification accuracy than the state-of-the-art algorithms such as Support Vector Machines (SVMs) and Neural Networks (NNs).

The spectra of the chemically peculiar stars

NASA Astrophysics Data System (ADS)

Hack, M.

The spectral properties of the chemically peculiar (CP) stars and the information which is obtainable from them are reviewed. The identification and classification of CP stars in the basis of their spectra is discussed with particular emphasis on the He-rich stars and CNO stars, and recent classification systems based on narrow-band photometry, low-resolution spectrometry or UV spectra are considered. Attention is given to continuum flux distributions, particularly the infrared excesses and UV deficiencies, and the stellar properties (effective temperature and gravity, line blocking, discontinuities, mass and radius) that may be derived from them, and to the magnetic field measurements and evidence for spotted element distributions that may be inferred from spectral surface composition analyses made using LTE model atmospheres are considered which involve both large sample of stars and individual stars, and statistical studies of rotation, magnetic braking and membership in binary systems and clusters are indicated. Finally, UV and X-ray evidence for chromospheres and coronas in some CP stars is noted.

New algorithm and system for measuring size distribution of blood cells

NASA Astrophysics Data System (ADS)

Yao, Cuiping; Li, Zheng; Zhang, Zhenxi

2004-06-01

In optical scattering particle sizing, a numerical transform is sought so that a particle size distribution can be determined from angular measurements of near forward scattering, which has been adopted in the measurement of blood cells. In this paper a new method of counting and classification of blood cell, laser light scattering method from stationary suspensions, is presented. The genetic algorithm combined with nonnegative least squared algorithm is employed to inverse the size distribution of blood cells. Numerical tests show that these techniques can be successfully applied to measuring size distribution of blood cell with high stability.

In-flight fiber optic acoustic emission sensor (FAESense) system for the real time detection, localization, and classification of damage in composite aircraft structures

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian

2013-05-01

Acoustic emission sensing is a leading structural health monitoring technique use for the early warning detection of structural damage associated with impacts, cracks, fracture, and delaminations in advanced materials. Current AE systems based on electronic PZT transducers suffer from various limitations that prevent its wide dynamic use in practical avionics and aerospace applications where weight, size and power are critical for operation. This paper describes progress towards the development of a wireless in-flight distributed fiber optic acoustic emission monitoring system (FAESense™) suitable for the onboard-unattended detection, localization, and classification of damage in avionics and aerospace structures. Fiber optic AE sensors offer significant advantages over its counterpart electronic AE sensors by using a high-density array of micron-size AE transducers distributed and multiplex over long lengths of a standard single mode optical fiber. Immediate SHM applications are found in commercial and military aircraft, helicopters, spacecraft, wind mil turbine blades, and in next generation weapon systems, as well as in the petrochemical and aerospace industries, civil structures, power utilities, and a wide spectrum of other applications.

Plasmonic modes in nanowire dimers: A study based on the hydrodynamic Drude model including nonlocal and nonlinear effects

NASA Astrophysics Data System (ADS)

Moeferdt, Matthias; Kiel, Thomas; Sproll, Tobias; Intravaia, Francesco; Busch, Kurt

2018-02-01

A combined analytical and numerical study of the modes in two distinct plasmonic nanowire systems is presented. The computations are based on a discontinuous Galerkin time-domain approach, and a fully nonlinear and nonlocal hydrodynamic Drude model for the metal is utilized. In the linear regime, these computations demonstrate the strong influence of nonlocality on the field distributions as well as on the scattering and absorption spectra. Based on these results, second-harmonic-generation efficiencies are computed over a frequency range that covers all relevant modes of the linear spectra. In order to interpret the physical mechanisms that lead to corresponding field distributions, the associated linear quasielectrostatic problem is solved analytically via conformal transformation techniques. This provides an intuitive classification of the linear excitations of the systems that is then applied to the full Maxwell case. Based on this classification, group theory facilitates the determination of the selection rules for the efficient excitation of modes in both the linear and nonlinear regimes. This leads to significantly enhanced second-harmonic generation via judiciously exploiting the system symmetries. These results regarding the mode structure and second-harmonic generation are of direct relevance to other nanoantenna systems.

D Land Cover Classification Based on Multispectral LIDAR Point Clouds

NASA Astrophysics Data System (ADS)

Zou, Xiaoliang; Zhao, Guihua; Li, Jonathan; Yang, Yuanxi; Fang, Yong

2016-06-01

Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green), at 1064 nm near infrared (NIR) and at 1550nm intermediate infrared (IR). It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA) approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

A Comparison of Local Variance, Fractal Dimension, and Moran's I as Aids to Multispectral Image Classification

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Sig-NganLam, Nina; Quattrochi, Dale A.

2004-01-01

The accuracy of traditional multispectral maximum-likelihood image classification is limited by the skewed statistical distributions of reflectances from the complex heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery. Tools available in the Image Characterization and Modeling System (ICAMS) were used to analyze Landsat 7 imagery of Atlanta, Georgia. Although segmentation of panchromatic images is possible using indicators of spatial complexity, different land covers often yield similar values of these indices. Better results are obtained when a surface of local fractal dimension or spatial autocorrelation is combined as an additional layer in a supervised maximum-likelihood multispectral classification. The addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques.

Classification and recognition of dynamical models: the role of phase, independent components, kernels and optimal transport.

PubMed

Bissacco, Alessandro; Chiuso, Alessandro; Soatto, Stefano

2007-11-01

We address the problem of performing decision tasks, and in particular classification and recognition, in the space of dynamical models in order to compare time series of data. Motivated by the application of recognition of human motion in image sequences, we consider a class of models that include linear dynamics, both stable and marginally stable (periodic), both minimum and non-minimum phase, driven by non-Gaussian processes. This requires extending existing learning and system identification algorithms to handle periodic modes and nonminimum phase behavior, while taking into account higher-order statistics of the data. Once a model is identified, we define a kernel-based cord distance between models that includes their dynamics, their initial conditions as well as input distribution. This is made possible by a novel kernel defined between two arbitrary (non-Gaussian) distributions, which is computed by efficiently solving an optimal transport problem. We validate our choice of models, inference algorithm, and distance on the tasks of human motion synthesis (sample paths of the learned models), and recognition (nearest-neighbor classification in the computed distance). However, our work can be applied more broadly where one needs to compare historical data while taking into account periodic trends, non-minimum phase behavior, and non-Gaussian input distributions.

A classification scheme for edge-localized modes based on their probability distributions

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

Shabbir, A., E-mail: aqsa.shabbir@ugent.be; Max Planck Institute for Plasma Physics, D-85748 Garching; Hornung, G.

We present here an automated classification scheme which is particularly well suited to scenarios where the parameters have significant uncertainties or are stochastic quantities. To this end, the parameters are modeled with probability distributions in a metric space and classification is conducted using the notion of nearest neighbors. The presented framework is then applied to the classification of type I and type III edge-localized modes (ELMs) from a set of carbon-wall plasmas at JET. This provides a fast, standardized classification of ELM types which is expected to significantly reduce the effort of ELM experts in identifying ELM types. Further, themore » classification scheme is general and can be applied to various other plasma phenomena as well.« less

Acuity systems dialogue and patient classification system essentials.

PubMed

Harper, Kelle; McCully, Crystal

2007-01-01

Obtaining resources for quality patient care is a major responsibility of nurse leaders and requires accurate information in the political world of budgeting. Patient classification systems (PCS) assist nurse managers in controlling cost and improving patient care while appropriately using financial resources. This paper communicates acuity systems development, background, flaws, and components while discussing a few tools currently available. It also disseminates the development of a new acuity tool, the Patient Classification System. The PCS tool, developed in a small rural hospital, uses 5 broad concepts: (1) medications, (2) complicated procedures, (3) education, (4) psychosocial issues, and (5) complicated intravenous medications. These concepts embrace a 4-tiered scale that differentiates significant patient characteristics and assists in staffing measures for equality in patient staffing and improving quality of care and performance. Data obtained through use of the PCS can be used by nurse leaders to effectively and objectively lobby for appropriate patient care resources. Two questionnaires distributed to registered nurses on a medical-surgical unit evaluated the nurses' opinion of the 5 concepts and the importance for establishing patient acuity for in-patient care. Interrater reliability among nurses was 87% with the author's acuity tool.

Two-tier tissue decomposition for histopathological image representation and classification.

PubMed

Gultekin, Tunc; Koyuncu, Can Fahrettin; Sokmensuer, Cenk; Gunduz-Demir, Cigdem

2015-01-01

In digital pathology, devising effective image representations is crucial to design robust automated diagnosis systems. To this end, many studies have proposed to develop object-based representations, instead of directly using image pixels, since a histopathological image may contain a considerable amount of noise typically at the pixel-level. These previous studies mostly employ color information to define their objects, which approximately represent histological tissue components in an image, and then use the spatial distribution of these objects for image representation and classification. Thus, object definition has a direct effect on the way of representing the image, which in turn affects classification accuracies. In this paper, our aim is to design a classification system for histopathological images. Towards this end, we present a new model for effective representation of these images that will be used by the classification system. The contributions of this model are twofold. First, it introduces a new two-tier tissue decomposition method for defining a set of multityped objects in an image. Different than the previous studies, these objects are defined combining texture, shape, and size information and they may correspond to individual histological tissue components as well as local tissue subregions of different characteristics. As its second contribution, it defines a new metric, which we call dominant blob scale, to characterize the shape and size of an object with a single scalar value. Our experiments on colon tissue images reveal that this new object definition and characterization provides distinguishing representation of normal and cancerous histopathological images, which is effective to obtain more accurate classification results compared to its counterparts.

The Adam Walsh Act: An Examination of Sex Offender Risk Classification Systems.

PubMed

Zgoba, Kristen M; Miner, Michael; Levenson, Jill; Knight, Raymond; Letourneau, Elizabeth; Thornton, David

2016-12-01

This study was designed to compare the Adam Walsh Act (AWA) classification tiers with actuarial risk assessment instruments and existing state classification schemes in their respective abilities to identify sex offenders at high risk to re-offend. Data from 1,789 adult sex offenders released from prison in four states were collected (Minnesota, New Jersey, Florida, and South Carolina). On average, the sexual recidivism rate was approximately 5% at 5 years and 10% at 10 years. AWA Tier 2 offenders had higher Static-99R scores and higher recidivism rates than Tier 3 offenders, and in Florida, these inverse correlations were statistically significant. Actuarial measures and existing state tier systems, in contrast, did a better job of identifying high-risk offenders and recidivists. As well, we examined the distribution of risk assessment scores within and across tier categories, finding that a majority of sex offenders fall into AWA Tier 3, but more than half score low or moderately low on the Static-99R. The results indicate that the AWA sex offender classification scheme is a poor indicator of relative risk and is likely to result in a system that is less effective in protecting the public than those currently implemented in the states studied. © The Author(s) 2015.

Single-Frame Terrain Mapping Software for Robotic Vehicles

NASA Technical Reports Server (NTRS)

Rankin, Arturo L.

2011-01-01

This software is a component in an unmanned ground vehicle (UGV) perception system that builds compact, single-frame terrain maps for distribution to other systems, such as a world model or an operator control unit, over a local area network (LAN). Each cell in the map encodes an elevation value, terrain classification, object classification, terrain traversability, terrain roughness, and a confidence value into four bytes of memory. The input to this software component is a range image (from a lidar or stereo vision system), and optionally a terrain classification image and an object classification image, both registered to the range image. The single-frame terrain map generates estimates of the support surface elevation, ground cover elevation, and minimum canopy elevation; generates terrain traversability cost; detects low overhangs and high-density obstacles; and can perform geometry-based terrain classification (ground, ground cover, unknown). A new origin is automatically selected for each single-frame terrain map in global coordinates such that it coincides with the corner of a world map cell. That way, single-frame terrain maps correctly line up with the world map, facilitating the merging of map data into the world map. Instead of using 32 bits to store the floating-point elevation for a map cell, the vehicle elevation is assigned to the map origin elevation and reports the change in elevation (from the origin elevation) in terms of the number of discrete steps. The single-frame terrain map elevation resolution is 2 cm. At that resolution, terrain elevation from 20.5 to 20.5 m (with respect to the vehicle's elevation) is encoded into 11 bits. For each four-byte map cell, bits are assigned to encode elevation, terrain roughness, terrain classification, object classification, terrain traversability cost, and a confidence value. The vehicle s current position and orientation, the map origin, and the map cell resolution are all included in a header for each map. The map is compressed into a vector prior to delivery to another system.

Morphological variation, taxonomic distribution, and phylogenetic significance of cornuti in Tortricinae (Lepidoptera: Tortricidae)

USDA-ARS?s Scientific Manuscript database

Based on the examination of 4,218 slide-mounted preparations of male and female genitalia of tortricine moths, representing all major clades of the subfamily worldwide, we propose a classification system for cornuti based on four criteria: (1) presence/absence; (2) deciduous/non-deciduous; (3) type ...

Implications of the Budgeting Process on State-of-the-Art (SOA) Extensions.

DTIC Science & Technology

1987-12-01

CLASSIFICATION AUTHORITY 3 DISTRIBUTION /AVAILABILITY OF REPORT Approved for public release; Zb DECLASSiFICATION1DOWNGRADING SCHEDULE Distribution is...PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO NO ACCESSION NO 11. TITLE (Include Security Classification ) IMPLICATIONS OF THE BUDGETING PROCESS ON STATE...20 DISTRIBUTIONAVAILABILITY OF ABSTRACT 21 ABSTRACT SECURITY CLASSIFICATION 0 UNCLASSIFIED,UNLIMI"ED 0 SAME AS RPT QJ DTIC USERS UNCLASSIFIED 22a

Protective Chafing Gear for Salvage Operations - Field Report

DTIC Science & Technology

1980-05-01

1980J E Approved for public release; distribution unlimited - INAVAL OCEAN SYSTEMS CENTER SAN DIEGO, CALIFORNIA 92152 80 6 20 008 * NAVAL OCEAN SYSTEMS...Officer of Reserve Harbor Clear- ance Unit 620. The initial suits were hand carried and evaluated during the cleanup task. A Navy Science Assistance...Systems Division Environmental Sciences Department II 𔃾 ? .4 F ~ ~~~~UNCLASSIFIED__ _ _ _ _ _ _ _ I7 f S~ECU I TY CLASSIFICATION OF THIS PAGE (ften

Converting Hangar High Expansion Foam Systems to Prevent Cockpit Damage: Full-Scale Validation Tests

DTIC Science & Technology

2017-09-01

AFCEC-CO-TY-TR-2018-0001 CONVERTING HANGAR HIGH EXPANSION FOAM SYSTEMS TO PREVENT COCKPIT DAMAGE: FULL-SCALE VALIDATION TESTS Gerard G...REPORT NUMBER(S) 12. DISTRIBUTION/ AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a. REPORT b...09-2017 Final Test Report May 2017 Converting Hangar High Expansion Foam Systems to Prevent Cockpit Damage: Full-Scale Validation Tests N00173-15-D

Acquisition of Stereoscopic Particle Image Velocimetry System for Investigation of Unsteady Flows

DTIC Science & Technology

2016-04-30

SECURITY CLASSIFICATION OF: The objective of the project titled “Acquisition of Stereoscopic Particle Image Velocimetry (S-PIV) System for...Distribution Unlimited UU UU UU UU 30-04-2016 1-Feb-2015 31-Jan-2016 Final Report: Acquisition of Stereoscopic Particle Image Velocimetry System For...ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Particle Image Velocimetry REPORT DOCUMENTATION PAGE 11

Classification Model for Forest Fire Hotspot Occurrences Prediction Using ANFIS Algorithm

NASA Astrophysics Data System (ADS)

Wijayanto, A. K.; Sani, O.; Kartika, N. D.; Herdiyeni, Y.

2017-01-01

This study proposed the application of data mining technique namely Adaptive Neuro-Fuzzy inference system (ANFIS) on forest fires hotspot data to develop classification models for hotspots occurrence in Central Kalimantan. Hotspot is a point that is indicated as the location of fires. In this study, hotspot distribution is categorized as true alarm and false alarm. ANFIS is a soft computing method in which a given inputoutput data set is expressed in a fuzzy inference system (FIS). The FIS implements a nonlinear mapping from its input space to the output space. The method of this study classified hotspots as target objects by correlating spatial attributes data using three folds in ANFIS algorithm to obtain the best model. The best result obtained from the 3rd fold provided low error for training (error = 0.0093676) and also low error testing result (error = 0.0093676). Attribute of distance to road is the most determining factor that influences the probability of true and false alarm where the level of human activities in this attribute is higher. This classification model can be used to develop early warning system of forest fire.

The Total Field in Collective Bremsstrahlung in a Nonequilibrium Relativistic Beam-Plasma System.

DTIC Science & Technology

1983-09-01

Of S"ANDARDS-1963-A L i o UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (1111bo Does Banero REPOR DOCUMENTATION PAGE READ INSTRUCTIONS r. REPORT...release; distribution unlimited. 17. DISTRIBUTION STATEMENT (of Me. absract mimed I Block it, different from Aepoft) 1S. SUPPLEMEMY1INANY NOTES kiDL...the nonradlative part of the field of the par- I ticls and a stochastic part corresponding to the bremsstrahlung radiation field. The relations

The Development and Inter-Rater Reliability of the Department of Defense Human Factors Analysis and Classification System, Version 7.0

DTIC Science & Technology

2015-04-09

Anthony Wurmstein, Lt Col Brian (Moose) Musselman, & Maj Alejandro Ramos (U.S. Air Force). Finally, Lt Col Mary E. Arnholt and Maj Ernest Herrera, Jr ...Wright- Patterson AFB, OH 45433-7913 Distribution A: Approved for public release; distribution is unlimited. Case Number: 88ABW-2015-2334, 12...School of Aerospace Medicine Aerospace Medicine Department Aerospace Education Branch 2510 Fifth St. Wright- Patterson AFB, OH 45433-7913 8

Changing the diagnostic criteria for myocardial infarction in patients with a suspected heart attack affects the measurement of 30 day mortality but not long term survival

PubMed Central

Packham, C; Gray, D; Weston, C; Large, A; Silcocks, P; Hampton, J

2002-01-01

Objectives: To explore the effects of alternative methods of defining myocardial infarction on the numbers and survival patterns of patients identified as having sustained a confirmed myocardial infarct. Design: An inclusive historical cohort of patients admitted with a suspected heart attack. Patients were recoded from raw clinical data (collected at the index admission) to the epidemiological definitions of myocardial infarction used by the Nottingham heart attack register (NHAR), the World Health Organization (MONICA), and the UK heart attack study. Setting: Single health district. Patients: The NHAR identified all patients admitted in 1992 with suspected myocardial infarction. Outcome measures: Survival at 30 days and four year postdischarge. Results: 2739 patients were identified, of whom 90% survived to discharge. Recoding increased the numbers of patients defined as having confirmed myocardial infarction from 26% under the original NHAR classification to 69%, depending on the classification system used. In confirmed myocardial infarction, subsequent 30 day survival from admission varied from 77–86% depending on the classification system; four year survival after discharge was not affected. The distribution of important prognostic variables differed significantly between groups of patients with confirmed myocardial infarction defined by different systems. Patients with suspected but unconfirmed myocardial infarction under all classification systems had a worse postdischarge mortality. Conclusions: The classification system used had a substantial effect on the numbers of patients identified as having had a myocardial infarct, and on the 30 day survival. There were significant numbers of patients with more atypical presentations, not labelled as myocardial infarction, who did badly following discharge. More research is needed on these patients. PMID:12231586

Inspection of wear particles in oils by using a fuzzy classifier

NASA Astrophysics Data System (ADS)

Hamalainen, Jari J.; Enwald, Petri

1994-11-01

The reliability of stand-alone machines and larger production units can be improved by automated condition monitoring. Analysis of wear particles in lubricating or hydraulic oils helps diagnosing the wear states of machine parts. This paper presents a computer vision system for automated classification of wear particles. Digitized images from experiments with a bearing test bench, a hydraulic system with an industrial company, and oil samples from different industrial sources were used for algorithm development and testing. The wear particles were divided into four classes indicating different wear mechanisms: cutting wear, fatigue wear, adhesive wear, and abrasive wear. The results showed that the fuzzy K-nearest neighbor classifier utilized gave the same distribution of wear particles as the classification by a human expert.

2008 International Conference on Ectodermal Dysplasias Classification Conference Report

PubMed Central

Salinas, Carlos F.; Jorgenson, Ronald J.; Wright, J. Timothy; DiGiovanna, John J.; Fete, Mary D.

2009-01-01

There are many ways to classify ectodermal dysplasia syndromes. Clinicians in practice use a list of syndromes from which to choose a potential diagnosis, paging through a volume, such as Freire-Maia and Pinheiro's corpus, matching their patient's findings to listed syndromes. Medical researchers may want a list of syndromes that share one (monothetic system) or several (polythetic system) traits in order to focus research on a narrowly defined group. Special interest groups may want a list from which they can choose constituencies, and insurance companies and government agencies may want a list to determine for whom to provide (or deny) health care coverage. Furthermore, various molecular biologists are now promoting classification systems based on gene mutation (e.g. TP63 associated syndromes) or common molecular pathways. The challenge will be to balance comprehensiveness within the classification with usability and accessibility so that the benefits truly serve the needs of researchers, health care providers and ultimately the individuals and families directly affected by ectodermal dysplasias. It is also recognized that a new classification approach is an ongoing process and will require periodical reviews or updates. Whatever scheme is developed, however, will have far-reaching application for other groups of disorders for which classification is complicated by the number of interested parties and advances in diagnostic acumen. Consensus among interested parties is necessary for optimizing communication among the diverse groups whether it be for equitable distribution of funds, correctness of diagnosis and treatment, or focusing research efforts. PMID:19681152

Pyelocaliceal Distribution of Kidney Stones Used as an Outcome Predictor in Percutaneous Nephrolithotomy After Being Evaluated with Preoperative and Postoperative CT Scan.

PubMed

Tirapegui, Federico Ignacio; González, Mariano Sebastian; González, Ignacio Pablo Tobía; Daels, Francisco P

2015-06-01

To identify kidney stone characteristics that will determine either success or failure of a percutaneous nephrolithotomy (PCNL) and design a classification system to predict results according to these characteristics. One hundred thirty-eight patients were assessed with multislice abdominal and pelvic CT before and after PCNL. With regard to pyelocaliceal stone distribution, we classified our patients in two groups that we called "no extra stone in middle calix" (NESMC) and "extra stone in middle calix" (ESMC), according to the difficulty in reaching the stones. We did a univariate and a multivariate analysis, as well as a receiving operating curve (ROC) of the proposed classification, based on the foreseen probabilities, to determine the diagnostic yield. Global residual lithiasis (RL) was 26.08%. The proportion of patients with RL according to classification was NESMC 11.5% and ESMC 59.5%. In the univariate logistic regression analysis of the distribution, number, total volumetry, side, type, radio-opacity of stones, and the presence or not of preoperatory urinary tract infection, the variables related to RL were the distribution (11.3; 95% confidence interval [95% CI] 4.7, 27.4), volumetry (odds ratio [OR] 1.01; 95% CI 1.004, 1.014), and the presence of staghorn stones (OR 6.64; 95% CI 2.463, 17.905). In the multivariate analysis, distribution was statistically significant (OR 8.687; 95% CI 2.69, 28.06), whereas total volumetry and the presence of staghorn stones were not (OR 1; 95% CI 1.000, 1.000 and OR 2.7; 95% CI 0.35, 20.57, respectively). The ROC showed an area under the curve of 0.77. In our experience, the distribution of kidney stones is the most important predictor of RL after PCNL. The results also suggest that the presence of stones in the middle calix has a direct impact on the stone-free rate. We put forward a simple and reproducible classification, easy to apply, and useful to estimate the chances of success of the procedure using preoperatory CT scans.

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

PubMed

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

Peripheral vascular tumors and vascular malformations: imaging (magnetic resonance imaging and conventional angiography), pathologic correlation and treatment options.

PubMed

El-Merhi, Fadi; Garg, Deepak; Cura, Marco; Ghaith, Ola

2013-02-01

Vascular anomalies are classified into vascular tumors (infantile hemangioma) and vascular malformations. Vascular malformations are divided into slow flow and high flow subtypes. Magnetic resonance imaging helps in classification and assessing extent and distribution. Conventional angiography also known as digital subtraction angiography is pivotal in assessment of fine vascular details and treatment planning. Imaging correlates well with histopathology. We review recent development in imaging techniques of various vascular anomalies most of which are affecting the peripheral system which potentially may broaden understanding of their diagnosis, classification and treatment.

Fault detection and classification in electrical power transmission system using artificial neural network.

PubMed

Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

2015-01-01

This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

Nonlinear features for product inspection

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1999-03-01

Classification of real-time X-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non-invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work, the MRDF is applied to standard features (rather than iconic data). The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC (receiver operating characteristic) data.

First steps towards a novel European forest fuel classification systems and a European forest fuel map

NASA Astrophysics Data System (ADS)

Sebastián-López, Ana; Urbieta, Itziar R.; de La Fuente Blanco, David; García Mateo, Rubén.; Moreno Rodríguez, José Manuel; Eftichidis, George; Varela, Vassiliki; Cesari, Véronique; Mário Ribeiro, Luís.; Viegas, Domingos Xavier; Lanorte, Antonio; Lasaponara, Rosa; Camia, Andrea; San Miguel, Jesús

2010-05-01

Forest fires burn at the local scale, but their massive occurrence causes effects which have global dimensions. Furthermore climate change projections associate global warming to a significant increase in forest fire activity. Warmer and drier conditions are expected to increase the frequency, duration and intensity of fires, and greater amounts of fuel associated with forest areas in decline may cause more frequent and larger fires. These facts create the need for establishing strategies for harmonizing fire danger rating, fire risk assessment, and fire prevention policies at a supranational level. Albeit forest fires are a permanent threat for European ecosystems, particularly in the south, there is no commonly accepted fuel classification scheme adopted for operational use by the Member States of the EU. The European Commission (EC) DG Environment and JRC have launched a set of studies following a resolution of the European Parliament on the further development and enhancement of the European Forest Fire Information System (EFFIS), the EC focal point for information on forest fires in Europe. One of the studies that are being funded is the FUELMAP project. The objective of FUELMAP is to develop a novel fuel classification system and a new European fuel map that will be based on a comprehensive classification of fuel complexes representing the various vegetation types across EU27, plus Switzerland, Croatia and Turkey. The overall work plan is grounded on a throughout knowledge of European forest landscapes and the key features of fuel situations occurring in natural areas. The method makes extended use of existing databases available in the Member States and European Institutions. Specifically, our proposed classification combines relevant information on ecoregions, land cover and uses, potential and actual vegetation, and stand structure. GIS techniques are used in order to define the geographic extent of the classification units and for identifying the main driving factors that determine the spatial distribution of the resulting fuel complexes. Furthermore, relevant parameters influencing fire potential and effects such as fuel load, live/dead ratio, and fuels' size classes' distribution are considered. National- and local-scale datasets (vegetation maps, forest inventory plots, fuel maps...) will be also studied and compared. Local ground- truth data will be used to assess the accuracy of the classification and will contribute, along with literature values and experts' opinion, to characterize the fuels' physical properties. The resulting classification aims to support the characterization of the fire potential, serve as input in fire emissions models, and be used to assess the expected impact of fire in the European landscapes. The work plan includes the development of a GIS software tool to automatically update the fuel map from modified (up-to-date) input data layers. The fuel map of Europe is mainly intended to support the implementation of the EFFIS modules that can be enhanced by the use of improved information on forest fuel properties and spatial distribution, though it is also envisaged that the results of the project might be useful for other relevant applications at different spatial scales. To this purpose, the classification will be designed with a hierarchical and flexible structure for describing heterogeneous landscapes. The work is on-going and this presentation shows the first results towards the envisaged European fuel map.

Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction.

PubMed

Faust, Kevin; Xie, Quin; Han, Dominick; Goyle, Kartikay; Volynskaya, Zoya; Djuric, Ugljesa; Diamandis, Phedias

2018-05-16

There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce. Here, we leverage t-distributed Stochastic Neighbor Embedding (t-SNE) to reduce dimensionality and depict how CNNs organize histomorphologic information. Unique to our workflow, we develop a quantitative and transparent approach to visualizing classification decisions prior to softmax compression. By discretizing the relationships between classes on the t-SNE plot, we show we can super-impose randomly sampled regions of test images and use their distribution to render statistically-driven classifications. Therefore, in addition to providing intuitive outputs for human review, this visual approach can carry out automated and objective multi-class classifications similar to more traditional and less-transparent categorical probability distribution scores. Importantly, this novel classification approach is driven by a priori statistically defined cutoffs. It therefore serves as a generalizable classification and anomaly detection tool less reliant on post-hoc tuning. Routine incorporation of this convenient approach for quantitative visualization and error reduction in histopathology aims to accelerate early adoption of CNNs into generalized real-world applications where unanticipated and previously untrained classes are often encountered.

Qcorp: an annotated classification corpus of Chinese health questions.

PubMed

Guo, Haihong; Na, Xu; Li, Jiao

2018-03-22

Health question-answering (QA) systems have become a typical application scenario of Artificial Intelligent (AI). An annotated question corpus is prerequisite for training machines to understand health information needs of users. Thus, we aimed to develop an annotated classification corpus of Chinese health questions (Qcorp) and make it openly accessible. We developed a two-layered classification schema and corresponding annotation rules on basis of our previous work. Using the schema, we annotated 5000 questions that were randomly selected from 5 Chinese health websites within 6 broad sections. 8 annotators participated in the annotation task, and the inter-annotator agreement was evaluated to ensure the corpus quality. Furthermore, the distribution and relationship of the annotated tags were measured by descriptive statistics and social network map. The questions were annotated using 7101 tags that covers 29 topic categories in the two-layered schema. In our released corpus, the distribution of questions on the top-layered categories was treatment of 64.22%, diagnosis of 37.14%, epidemiology of 14.96%, healthy lifestyle of 10.38%, and health provider choice of 4.54% respectively. Both the annotated health questions and annotation schema were openly accessible on the Qcorp website. Users can download the annotated Chinese questions in CSV, XML, and HTML format. We developed a Chinese health question corpus including 5000 manually annotated questions. It is openly accessible and would contribute to the intelligent health QA system development.

Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China

NASA Astrophysics Data System (ADS)

Cheng, Tao; Zhang, Jialong; Zheng, Xinyan; Yuan, Rujin

2018-03-01

The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.

Research Support for the Laboratory for Lightwave Technology

DTIC Science & Technology

1992-12-31

34 .. . ."/ 12a. DISTRIBUTION AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE UNLIMITED 13. ABSTRACT (Mawimum 200words) 4 SEE ATTACHED ABSTRACT DT I 14. SUBJECT...8217TERMS 15. NUMBER OF PAGES 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT...temperature ceramic nano- phase single crystal oxides that may be produced at a high rate . The synthesis of both glasses and ceramics using novel techniques

Solar simulator for concentrator photovoltaic systems.

PubMed

Domínguez, César; Antón, Ignacio; Sala, Gabriel

2008-09-15

A solar simulator for measuring performance of large area concentrator photovoltaic (CPV) modules is presented. Its illumination system is based on a Xenon flash light and a large area collimator mirror, which simulates natural sun light. Quality requirements imposed by the CPV systems have been characterized: irradiance level and uniformity at the receiver, light collimation and spectral distribution. The simulator allows indoor fast and cost-effective performance characterization and classification of CPV systems at the production line as well as module rating carried out by laboratories.

[Analysis of vegetation spatial and temporal variations in Qinghai Province based on remote sensing].

PubMed

Wang, Li-wen; Wei, Ya-xing; Niu, Zheng

2008-06-01

1 km MODIS NDVI time series data combining with decision tree classification, supervised classification and unsupervised classification was used to classify land cover type of Qinghai Province into 14 classes. In our classification system, sparse grassland and sparse shrub were emphasized, and their spatial distribution locations were labeled. From digital elevation model (DEM) of Qinghai Province, five elevation belts were achieved, and we utilized geographic information system (GIS) software to analyze vegetation cover variation on different elevation belts. Our research result shows that vegetation cover in Qinghai Province has been improved in recent five years. Vegetation cover area increases from 370047 km2 in 2001 to 374576 km2 in 2006, and vegetation cover rate increases by 0.63%. Among five grade elevation belts, vegetation cover ratio of high mountain belt is the highest (67.92%). The area of middle density grassland in high mountain belt is the largest, of which area is 94 003 km2. Increased area of dense grassland in high mountain belt is the greatest (1280 km2). During five years, the biggest variation is the conversion from sparse grassland to middle density grassland in high mountain belt, of which area is 15931 km2.

Context-based automated defect classification system using multiple morphological masks

DOEpatents

Gleason, Shaun S.; Hunt, Martin A.; Sari-Sarraf, Hamed

2002-01-01

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

Inequalities in the distribution of pharmacists' wage-and-salary earnings: indicators and their development.

PubMed

Carvajal, Manuel J; Armayor, Graciela M

2013-01-01

Disparities in wages and salaries can be viewed as the dispersion of a statistical distribution that responds to observed and unobserved characteristics, and reflects socioeconomic phenomena such as the interplay of supply and demand, availability of information, and efficiency of markets in their search for equilibrium. The aim of this study was to explore the nature of inequality in the distribution of pharmacists' wage-and-salary earnings and establish the extent to which inequality primarily occurred because of variation between/among groups or within groups of pharmacists in several classifications of human-capital and job-related preference variables. Data were collected through the use of a survey questionnaire mailed to registered pharmacists in South Florida, USA. Five indicators of inequality (the log earnings variance, the coefficient of variation, the lower median share, the 90-10 decile ratio, and the Gini coefficient) were estimated for eight human-capital classifications and eight job-related classifications. A one-way ANOVA model was applied to the groups in each classification to compare variation between/among versus within pharmacy groups. Pharmacists' wage-and-salary earnings were more evenly distributed than most income distributions discussed in the literature. They were more equitably distributed for full-time pharmacists than for all pharmacists in the data set. All five-inequality indicators behaved similarly. Notable differences were observed between/among groups within the gender, age group, marital status, number of children, academic degree, and type of primary pharmacy activity classifications. Inequalities in wages and salaries have been identified both between/among and within pharmacist groups in several classifications using five commonly accepted indicators. Copyright © 2013 Elsevier Inc. All rights reserved.

Classification with asymmetric label noise: Consistency and maximal denoising

DOE PAGES

Blanchard, Gilles; Flaska, Marek; Handy, Gregory; ...

2016-09-20

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that amore » majority of the observed labels are correct and that the true class-conditional distributions are “mutually irreducible,” a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to “mixture proportion estimation,” which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. MSC 2010 subject classifications: Primary 62H30; secondary 68T10. Keywords and phrases: Classification, label noise, mixture proportion estimation, surrogate loss, consistency.« less

Classification with asymmetric label noise: Consistency and maximal denoising

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

Blanchard, Gilles; Flaska, Marek; Handy, Gregory

In many real-world classification problems, the labels of training examples are randomly corrupted. Most previous theoretical work on classification with label noise assumes that the two classes are separable, that the label noise is independent of the true class label, or that the noise proportions for each class are known. In this work, we give conditions that are necessary and sufficient for the true class-conditional distributions to be identifiable. These conditions are weaker than those analyzed previously, and allow for the classes to be nonseparable and the noise levels to be asymmetric and unknown. The conditions essentially state that amore » majority of the observed labels are correct and that the true class-conditional distributions are “mutually irreducible,” a concept we introduce that limits the similarity of the two distributions. For any label noise problem, there is a unique pair of true class-conditional distributions satisfying the proposed conditions, and we argue that this pair corresponds in a certain sense to maximal denoising of the observed distributions. Our results are facilitated by a connection to “mixture proportion estimation,” which is the problem of estimating the maximal proportion of one distribution that is present in another. We establish a novel rate of convergence result for mixture proportion estimation, and apply this to obtain consistency of a discrimination rule based on surrogate loss minimization. Experimental results on benchmark data and a nuclear particle classification problem demonstrate the efficacy of our approach. MSC 2010 subject classifications: Primary 62H30; secondary 68T10. Keywords and phrases: Classification, label noise, mixture proportion estimation, surrogate loss, consistency.« less

Detection of defects on apple using B-spline lighting correction method

NASA Astrophysics Data System (ADS)

Li, Jiangbo; Huang, Wenqian; Guo, Zhiming

To effectively extract defective areas in fruits, the uneven intensity distribution that was produced by the lighting system or by part of the vision system in the image must be corrected. A methodology was used to convert non-uniform intensity distribution on spherical objects into a uniform intensity distribution. A basically plane image with the defective area having a lower gray level than this plane was obtained by using proposed algorithms. Then, the defective areas can be easily extracted by a global threshold value. The experimental results with a 94.0% classification rate based on 100 apple images showed that the proposed algorithm was simple and effective. This proposed method can be applied to other spherical fruits.

An Artificial Neural Network Control System for Spacecraft Attitude Stabilization

DTIC Science & Technology

1990-06-01

NAVAL POSTGRADUATE SCHOOL Monterey, California ’-DTIC 0 ELECT f NMARO 5 191 N S, U, THESIS B . AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR...NO. NO. NO ACCESSION NO 11. TITLE (Include Security Classification) AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR SPACECRAFT ATTITUDE STABILIZATION...obsolete a U.S. G v pi.. iim n P.. oiice! toog-eo.5s43 i Approved for public release; distribution is unlimited. AN ARTIFICIAL NEURAL NETWORK CONTROL

The classification of phobic disorders.

PubMed

Sheehan, D V; Sheehan, K H

The history of classification of phobic disorders is reviewed. Problems in the ability of current classification schemes to predict, control and describe the relationship between the symptoms and other phenomena are outlined. A new classification of phobic disorders is proposed based on the presence or absence of an endogenous anxiety syndrome with the phobias. The two categories of phobic disorder have a different clinical presentation and course, a different mean age of onset, distribution of age of onset, sex distribution, response to treatment modalities, GSR testing and habituation response. Empirical evidence supporting this proposal is cited. This classification has heuristic merit in guiding research efforts and discussions and in directing the clinician to a simple and practical solution of his patient's phobic disorder.

Ontology for Life-Cycle Modeling of Electrical Distribution Systems: Application of Model View Definition Attributes

DTIC Science & Technology

2013-06-01

Building in- formation exchange (COBie), Building Information Modeling ( BIM ) 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...to develop a life-cycle building model have resulted in the definition of a “core” building information model that contains general information de...develop an information -exchange Model View Definition (MVD) for building electrical systems. The objective of the current work was to document the

Species rarity: definition, causes, and classification

Treesearch

Curtis H. Flather; Carolyn Hull Sieg

2007-01-01

In virtually all ecological communities around the world, most species are represented by few individuals, and most individuals come from only a few of the most common species. Why this distribution of species abundances is so regularly observed among different taxonomic sets in geographically diverse systems is a question that has received considerable theoretical and...

Role of Epidermal Growth Factor Receptors and Their Ligands in Normal Mammary Epithelial and Breast Cancer Cells

DTIC Science & Technology

1996-07-01

UNCLASSIFIED AD NUMBER ADB216343 NEW LIMITATION CHANGE TO Approved for public release, distribution unlimited FROM Distribution authorized to U.S...PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF THIS PAGE OF...ABSTRACT ,Unclassified Unclassified Unclassified Limited NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39-1 8 DISCLAIMER

Mated Fingerprint Card Pairs 2 (MFCP2)

National Institute of Standards and Technology Data Gateway

NIST Mated Fingerprint Card Pairs 2 (MFCP2) (Web, free access)   NIST Special Database 14 is being distributed for use in development and testing of automated fingerprint classification and matching systems on a set of images which approximate a natural horizontal distribution of the National Crime Information Center (NCIC) fingerprint classes. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data.

PubMed

Bargi, Ava; Xu, Richard Yi Da; Piccardi, Massimo

2017-09-21

Recent years have witnessed an increasing need for the automated classification of sequential data, such as activities of daily living, social media interactions, financial series, and others. With the continuous flow of new data, it is critical to classify the observations on-the-fly and without being limited by a predetermined number of classes. In addition, a model should be able to update its parameters in response to a possible evolution in the distributions of the classes. This compelling problem, however, does not seem to have been adequately addressed in the literature, since most studies focus on offline classification over predefined class sets. In this paper, we present a principled solution for this problem based on an adaptive online system leveraging Markov switching models and hierarchical Dirichlet process priors. This adaptive online approach is capable of classifying the sequential data over an unlimited number of classes while meeting the memory and delay constraints typical of streaming contexts. In this paper, we introduce an adaptive ''learning rate'' that is responsible for balancing the extent to which the model retains its previous parameters or adapts to new observations. Experimental results on stationary and evolving synthetic data and two video data sets, TUM Assistive Kitchen and collated Weizmann, show a remarkable performance in terms of segmentation and classification, particularly for sequences from evolutionary distributions and/or those containing previously unseen classes.

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

PubMed Central

Alwanni, Hisham; Baslan, Yara; Alnuman, Nasim; Daoud, Mohammad I.

2017-01-01

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The constructed TFR is used to extract five categories of time-frequency features (TFFs). The TFFs are processed using a hierarchical classification model to identify the MI task encapsulated within the EEG signals. To evaluate the performance of the proposed approach, EEG data were recorded for eighteen intact subjects and four amputated subjects while imagining to perform each of the eleven hand MI tasks. Two performance evaluation analyses, namely channel- and TFF-based analyses, are conducted to identify the best subset of EEG channels and the TFFs category, respectively, that enable the highest classification accuracy between the MI tasks. In each evaluation analysis, the hierarchical classification model is trained using two training procedures, namely subject-dependent and subject-independent procedures. These two training procedures quantify the capability of the proposed approach to capture both intra- and inter-personal variations in the EEG signals for different MI tasks within the same hand. The results demonstrate the efficacy of the approach for classifying the MI tasks within the same hand. In particular, the classification accuracies obtained for the intact and amputated subjects are as high as 88.8% and 90.2%, respectively, for the subject-dependent training procedure, and 80.8% and 87.8%, respectively, for the subject-independent training procedure. These results suggest the feasibility of applying the proposed approach to control dexterous prosthetic hands, which can be of great benefit for individuals suffering from hand amputations. PMID:28832513

Particle-size distribution models for the conversion of Chinese data to FAO/USDA system.

PubMed

Shangguan, Wei; Dai, YongJiu; García-Gutiérrez, Carlos; Yuan, Hua

2014-01-01

We investigated eleven particle-size distribution (PSD) models to determine the appropriate models for describing the PSDs of 16349 Chinese soil samples. These data are based on three soil texture classification schemes, including one ISSS (International Society of Soil Science) scheme with four data points and two Katschinski's schemes with five and six data points, respectively. The adjusted coefficient of determination r (2), Akaike's information criterion (AIC), and geometric mean error ratio (GMER) were used to evaluate the model performance. The soil data were converted to the USDA (United States Department of Agriculture) standard using PSD models and the fractal concept. The performance of PSD models was affected by soil texture and classification of fraction schemes. The performance of PSD models also varied with clay content of soils. The Anderson, Fredlund, modified logistic growth, Skaggs, and Weilbull models were the best.

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

PubMed

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

2015-03-01

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

Towards an information geometric characterization/classification of complex systems. I. Use of generalized entropies

NASA Astrophysics Data System (ADS)

Ghikas, Demetris P. K.; Oikonomou, Fotios D.

2018-04-01

Using the generalized entropies which depend on two parameters we propose a set of quantitative characteristics derived from the Information Geometry based on these entropies. Our aim, at this stage, is to construct first some fundamental geometric objects which will be used in the development of our geometrical framework. We first establish the existence of a two-parameter family of probability distributions. Then using this family we derive the associated metric and we state a generalized Cramer-Rao Inequality. This gives a first two-parameter classification of complex systems. Finally computing the scalar curvature of the information manifold we obtain a further discrimination of the corresponding classes. Our analysis is based on the two-parameter family of generalized entropies of Hanel and Thurner (2011).

A coastal and marine digital library at USGS

USGS Publications Warehouse

Lightsom, Fran

2003-01-01

The Marine Realms Information Bank (MRIB) is a distributed geolibrary [NRC, 1999] from the U.S. Geological Survey (USGS) and the Woods Hole Oceanographic Institution (WHOI), whose purpose is to classify, integrate, and facilitate access to Earth systems science information about ocean, lake, and coastal environments. Core MRIB services are: (1) the search and display of information holdings by place and subject, and (2) linking of information assets that exist in remote physical locations. The design of the MRIB features a classification system to integrate information from remotely maintained sources. This centralized catalogue organizes information using 12 criteria: locations, geologic time, physiographic features, biota, disciplines, research methods, hot topics, project names, agency names, authors, content type, and file type. For many of these fields, MRIB has developed classification hierarchies.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, Jin AU; Shin, Robert T.; Nghiem, Son V.; Yueh, Herng-Aung; Han, Hsiu C.; Lim, Harold H.; Arnold, David V.

1990-01-01

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

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

PubMed

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

2018-05-01

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

A theory for classification of health care organizations in the new economy.

PubMed

Vimarlund, Vivian; Sjöberg, Cecilia; Timpka, Toomas

2003-10-01

Most of the available studies into information technology (IT) have been limited to investigating specific issues, such as how IT can support decision makers distributing the information throughout health care organization, or how technology impacts organizational performance. In this study, for use in the planning of information system development projects, a theoretical model for the classification of health care organizations is proposed. We try to reflect the development in the contemporary digital economy by theoretically classifying health care organizations into three types, namely traditional, developing, and flexible. We describe traditional health care organizations as organizations with a centralized system for management and control. In developing health care organizations, IT is spread over the horizontal dimension and is used for coordinating the different parties throughout the organization. Finally, flexible health care organizations are those which work actively with the design of new health care organizational structure while they are designing the information system.

Utility of the PALM-COEIN classification of abnormal uterine bleeding for Indian gynecologists.

PubMed

Bandi, Nirmala D; Arumugam, Chandrasekharan P; Venkata, Meenakumari R N; Nannam, Lahari

2016-05-01

To study the clinical utility of the PALM-COEIN classification for abnormal uterine bleeding in day-to-day practice in India. Between April and November 2014, a cross-sectional survey was undertaken of gynecologists practicing in Chittoor and Nellore. Doctors possessing a postgraduate degree in gynecology and obstetrics, and postgraduate students in the gynecology department of medical colleges were invited to participate. A validated questionnaire containing 15 questions was distributed, the opinions were collated, and the results analyzed. Among 150 invited gynecologists, 120 agreed to participate, and 119 completed the survey fully. Overall, 95 (79.8%) respondents were aware of the classification, and 56 (47.1%) responded that the PALM-COEIN system is very good, 46 (38.7%) that it is average, and 17 (14.3%) that it is poor. By subgroup, 16 of 20 (80.0%) faculty members, 46 of 56 (82.1%) postgraduate students, and 33 of 43 (76.7%) practitioners responded that the system is useful. Indian doctors generally believe that the PALM-COEIN system is clinically useful and a step forward in the management of abnormal uterine bleeding. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Concreteness effects in semantic processing: ERP evidence supporting dual-coding theory.

PubMed

Kounios, J; Holcomb, P J

1994-07-01

Dual-coding theory argues that processing advantages for concrete over abstract (verbal) stimuli result from the operation of 2 systems (i.e., imaginal and verbal) for concrete stimuli, rather than just 1 (for abstract stimuli). These verbal and imaginal systems have been linked with the left and right hemispheres of the brain, respectively. Context-availability theory argues that concreteness effects result from processing differences in a single system. The merits of these theories were investigated by examining the topographic distribution of event-related brain potentials in 2 experiments (lexical decision and concrete-abstract classification). The results were most consistent with dual-coding theory. In particular, different scalp distributions of an N400-like negativity were elicited by concrete and abstract words.

New Forum Addresses Microbiologically Influenced Corrosion

DTIC Science & Technology

2012-06-01

methanogens. 15. SUBJECT TERMS MIC, biofilm Formation , localized corrosion, microoganisms 16. SECURITY CLASSIFICATION OF: a. REPORT Unclassified b... Stainless Steels for Prestressed Concrete" Elisabeth Schwarzenbbck University of Bourgogne Third Place, Mars Fontana Category "Microelectrochemical...Campbell described a monitoring sys- tem for a Type 316L stainless steel (UNS S31603) drinking water distribution system that measured open circuit

Simulating Synchronous Processors

DTIC Science & Technology

1988-06-01

34f Fvtvru m LABORATORY FOR INMASSACHUSETTSFCOMPUTER SCIENCE TECHNOLOGY MIT/LCS/TM-359 SIMULATING SYNCHRONOUS PROCESSORS Jennifer Lundelius Welch...PROJECT TASK WORK UNIT Arlington, VA 22217 ELEMENT NO. NO. NO ACCESSION NO. 11. TITLE Include Security Classification) Simulating Synchronous Processors...necessary and identify by block number) In this paper we show how a distributed system with synchronous processors and asynchro- nous message delays can

Location Management in Distributed Mobile Environments

DTIC Science & Technology

1994-09-01

carried out to evaluate the performanceof di erent static strategies for various communica-tion and mobility patterns. Simulation results indi-cate...results ofsimulations carried out to evaluate the performanceof proposed static location management strategies forvarious call and mobility patterns...Systems, Austin, Sept. 1994. U.S. Government or Federal Rights License 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17

Ontology for Life-Cycle Modeling of Electrical Distribution Systems: Model View Definition

DTIC Science & Technology

2013-06-01

building information models ( BIM ) at the coordinated design stage of building construction. 1.3 Approach To...standard for exchanging Building Information Modeling ( BIM ) data, which defines hundreds of classes for common use in software, currently supported by...specifications, Construction Operations Building in- formation exchange (COBie), Building Information Modeling ( BIM ) 16. SECURITY CLASSIFICATION OF:

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

Shallow-Water Mud Acoustics

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Shallow- Water Mud Acoustics William L. Siegmann...shallow water over mud sediments and of acoustic detection, localization, and classification of objects buried in mud. OBJECTIVES • Develop...including long-range conveyance of information; detection, localization, and classification of objects buried in mud; and improvement of shallow water

Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

PubMed Central

Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

2013-01-01

Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

Acoustic detection of biosonar activity of deep diving odontocetes at Josephine Seamount High Seas Marine Protected Area.

PubMed

Giorli, Giacomo; Au, Whitlow W L; Ou, Hui; Jarvis, Susan; Morrissey, Ronald; Moretti, David

2015-05-01

The temporal occurrence of deep diving cetaceans in the Josephine Seamount High Seas Marine Protected Area (JSHSMPA), south-west Portugal, was monitored using a passive acoustic recorder. The recorder was deployed on 13 May 2010 at a depth of 814 m during the North Atlantic Treaty Organization Centre for Maritime Research and Experimentation cruise "Sirena10" and recovered on 6 June 2010. The recorder was programmed to record 40 s of data every 2 min. Acoustic data analysis, for the detection and classification of echolocation clicks, was performed using automatic detector/classification systems: M3R (Marine Mammal Monitoring on Navy Ranges), a custom matlab program, and an operator-supervised custom matlab program to assess the classification performance of the detector/classification systems. M3R CS-SVM algorithm contains templates to detect beaked whales, sperm whales, blackfish (pilot and false killer whales), and Risso's dolphins. The detections of each group of odontocetes was monitored as a function of time. Blackfish and Risso's dolphins were detected every day, while beaked whales and sperm whales were detected almost every day. The hourly distribution of detections reveals that blackfish and Risso's dolphins were more active at night, while beaked whales and sperm whales were more active during daylight hours.

A Qualitative Description of Chronic Neck Pain has Implications for Outcome Assessment and Classification

PubMed Central

MacDermid, Joy C.; Walton, David M.; Bobos, Pavlos; Lomotan, Margaret; Carlesso, Lisa

2016-01-01

Background: Neck pain is common, but few studies have used qualitative methods to describe it. Purpose: To describe the quality, distribution and behavior of neck pain. Methods: Sixteen people (15 females; mean age = 33 years (range = 20-69)) with neck pain >3 months were interviewed using a semi-structured guide. Interview data were recorded and transcribed verbatim. Descriptive content analysis was performed by two authors. Participants then completed an electronic descriptive pain tool, placing icons (word and icon descriptors to describe quality) on anatomic diagrams to identify location of pain, and intensity ratings at each location. This data was triangulated with interviews. Results: Aching pain and stiffness in the posterior neck and shoulder region were the most common pain complaints. All patients reported more than one pain quality. Associated headache was common (11/16 people); but varied in location and pain quality; 13/16 reported upper extremity symptoms. Neuropathic characteristics (burning) or sensory disturbance (numbness/tingling) occurred in some patients, but were less common. Activities that involved lifting/carrying and psychological stress were factors reported as exacerbating pain. Physical activity was valued as essential to function, but also instigated exacerbations. Concordance between the structured pain tool and interviews enhanced trustworthiness of our results. Integrating qualitative findings with a previous classification system derived a 7-axis neck pain classification: source/context, sample subgroup, distribution, duration, episode pattern, pain/symptom severity, disability/participation restriction. Conclusions: Qualitative assessment and classification should consider the multiple dimensions of neck pain. PMID:28217199

Hybrid Multiagent System for Automatic Object Learning Classification

NASA Astrophysics Data System (ADS)

Gil, Ana; de La Prieta, Fernando; López, Vivian F.

The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives.

BisQue: cloud-based system for management, annotation, visualization, analysis and data mining of underwater and remote sensing imagery

NASA Astrophysics Data System (ADS)

Fedorov, D.; Miller, R. J.; Kvilekval, K. G.; Doheny, B.; Sampson, S.; Manjunath, B. S.

2016-02-01

Logistical and financial limitations of underwater operations are inherent in marine science, including biodiversity observation. Imagery is a promising way to address these challenges, but the diversity of organisms thwarts simple automated analysis. Recent developments in computer vision methods, such as convolutional neural networks (CNN), are promising for automated classification and detection tasks but are typically very computationally expensive and require extensive training on large datasets. Therefore, managing and connecting distributed computation, large storage and human annotations of diverse marine datasets is crucial for effective application of these methods. BisQue is a cloud-based system for management, annotation, visualization, analysis and data mining of underwater and remote sensing imagery and associated data. Designed to hide the complexity of distributed storage, large computational clusters, diversity of data formats and inhomogeneous computational environments behind a user friendly web-based interface, BisQue is built around an idea of flexible and hierarchical annotations defined by the user. Such textual and graphical annotations can describe captured attributes and the relationships between data elements. Annotations are powerful enough to describe cells in fluorescent 4D images, fish species in underwater videos and kelp beds in aerial imagery. Presently we are developing BisQue-based analysis modules for automated identification of benthic marine organisms. Recent experiments with drop-out and CNN based classification of several thousand annotated underwater images demonstrated an overall accuracy above 70% for the 15 best performing species and above 85% for the top 5 species. Based on these promising results, we have extended bisque with a CNN-based classification system allowing continuous training on user-provided data.

Evaluation of scattered light distributions of cw-transillumination for functional diagnostic of rheumatic disorders in interphalangeal joints

NASA Astrophysics Data System (ADS)

Prapavat, Viravuth; Schuetz, Rijk; Runge, Wolfram; Beuthan, Juergen; Mueller, Gerhard J.

1995-12-01

This paper presents in-vitro-studies using the scattered intensity distribution obtained by cw- transillumination to examine the condition of rheumatic disorders of interphalangeal joints. Inflammation of joints, due to rheumatic diseases, leads to changes in the synovial membrane, synovia composition and content, and anatomic geometrical variations. Measurements have shown that these rheumatic induced inflammation processes result in a variation in optical properties of joint systems. With a scanning system the interphalangeal joint is transilluminated with diode lasers (670 nm, 905 nm) perpendicular to the joint cavity. The detection of the entire distribution of the transmitted radiation intensity was performed with a CCD camera. As a function of the structure and optical properties of the transilluminated volume we achieved distributions of scattered radiation which show characteristic variations in intensity and shape. Using signal and image processing procedures we evaluated the measured scattered distributions regarding their information weight, shape and scale features. Mathematical methods were used to find classification criteria to determine variations of the joint condition.

New nonlinear features for inspection, robotics, and face recognition

NASA Astrophysics Data System (ADS)

Casasent, David P.; Talukder, Ashit

1999-10-01

Classification of real-time X-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non- invasive detection of defective product items on a conveyor belt. We discuss the extraction of new features that allow better discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper; our new maximum representation and discriminating feature (MRDF) extraction method computes nonlinear features that are used as inputs to a new modified k nearest neighbor classifier. In this work, the MRDF is applied to standard features (rather than iconic data). The MRDF is robust to various probability distributions of the input class and is shown to provide good classification and new ROC (receiver operating characteristic) data. Other applications of these new feature spaces in robotics and face recognition are also noted.

Understanding similarity of groundwater systems with empirical copulas

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Kumar, Rohini; Samaniego, Luis; Barthel, Roland

2016-04-01

Within the classification framework for groundwater systems that aims for identifying similarity of hydrogeological systems and transferring information from a well-observed to an ungauged system (Haaf and Barthel, 2015; Haaf and Barthel, 2016), we propose a copula-based method for describing groundwater-systems similarity. Copulas are an emerging method in hydrological sciences that make it possible to model the dependence structure of two groundwater level time series, independently of the effects of their marginal distributions. This study is based on Samaniego et al. (2010), which described an approach calculating dissimilarity measures from bivariate empirical copula densities of streamflow time series. Subsequently, streamflow is predicted in ungauged basins by transferring properties from similar catchments. The proposed approach is innovative because copula-based similarity has not yet been applied to groundwater systems. Here we estimate the pairwise dependence structure of 600 wells in Southern Germany using 10 years of weekly groundwater level observations. Based on these empirical copulas, dissimilarity measures are estimated, such as the copula's lower- and upper corner cumulated probability, copula-based Spearman's rank correlation - as proposed by Samaniego et al. (2010). For the characterization of groundwater systems, copula-based metrics are compared with dissimilarities obtained from precipitation signals corresponding to the presumed area of influence of each groundwater well. This promising approach provides a new tool for advancing similarity-based classification of groundwater system dynamics. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs EGU General Assembly 2016, Vienna, Austria. Samaniego, L., Bardossy, A., Kumar, R., 2010. Streamflow prediction in ungauged catchments using copula-based dissimilarity measures. Water Resources Research, 46. DOI:10.1029/2008wr007695

Local Area Network (LAN) Compatibility Issues

DTIC Science & Technology

1991-09-01

September, 1991 Thesis Advisor: Dr. Norman Schneidewind Approved for public release; distribution is unlimited 92 303s246 Unclassified SECURITY ...CLASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE Ia. REPORT SECURITY CLASSIFICATION 1 b. RESTRICTIVE MARKINGS unclassified 2a. SECURITY CLASSIFICATION...Work UiNt ACCeLUOn Number 11. TITLE (Include Security Classification) LOCAL AREA NETWORK (LAN) COMPATIBILITY ISSUES 12. PERSONAL AUTHOR(S) Rita V

Engineering and Design: Rock Mass Classification Data Requirements for Rippability

DTIC Science & Technology

1983-06-30

Engineering and Design ROCK MASS CLASSIFICATION DATA REQUIREMENTS FOR RIPPABILITY Distribution Restriction Statement Approved for public release...and Design: Rock Mass Classification Data Requirements for Rippability Contract Number Grant Number Program Element Number Author(s) Project...Technical Letter 1110-2-282 Engineering and Design ROCK MASS CLASSIFICATION DATA REQUIREMENTS FOR RIPPABILITY 1“ -“ This ETL contains information on data

Glossary: Defense Acquisition Acronyms and Terms. Revision 2

DTIC Science & Technology

1987-07-01

Approved REPORT DOCUMENTATION PAGE OMBNo. 070-O 18 la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS % unclassified 2a. SECURITY CLASSIFICATION ...WORK UNIT Fort Belvoir, VA 22060-5426 ELEMENT NO. NO. NO. ACCESSION NO. 11. TITLE (Include Security Classification ) Glossary Defense Acquisition...DISTRIBUTION/AVAILABILITY OF ABSTRACT 21 ABSTRACT SECURITY CLASSIFICATION [RUNCLASSIFIED/UNLIMITED 0 SAME AS RPT 0 DTIC USERS unclassified 22a. NAME OF

Detection of anomalous events

DOEpatents

Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

2016-06-07

A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

Intra- and interobserver agreement in the classification and treatment of distal third clavicle fractures.

PubMed

Bishop, Julie Y; Jones, Grant L; Lewis, Brian; Pedroza, Angela

2015-04-01

In treatment of distal third clavicle fractures, the Neer classification system, based on the location of the fracture in relation to the coracoclavicular ligaments, has traditionally been used to determine fracture pattern stability. To determine the intra- and interobserver reliability in the classification of distal third clavicle fractures via standard plain radiographs and the intra- and interobserver agreement in the preferred treatment of these fractures. Cohort study (Diagnosis); Level of evidence, 3. Thirty radiographs of distal clavicle fractures were randomly selected from patients treated for distal clavicle fractures between 2006 and 2011. The radiographs were distributed to 22 shoulder/sports medicine fellowship-trained orthopaedic surgeons. Fourteen surgeons responded and took part in the study. The evaluators were asked to measure the size of the distal fragment, classify the fracture pattern as stable or unstable, assign the Neer classification, and recommend operative versus nonoperative treatment. The radiographs were reordered and redistributed 3 months later. Inter- and intrarater agreement was determined for the distal fragment size, stability of the fracture, Neer classification, and decision to operate. Single variable logistic regression was performed to determine what factors could most accurately predict the decision for surgery. Interrater agreement was fair for distal fragment size, moderate for stability, fair for Neer classification, slight for type IIB and III fractures, and moderate for treatment approach. Intrarater agreement was moderate for distal fragment size categories (κ = 0.50, P < .001) and Neer classification (κ = 0.42, P < .001) and substantial for stable fracture (κ = 0.65, P < .001) and decision to operate (κ = 0.65, P < .001). Fracture stability was the best predictor of treatment, with 89% accuracy (P < .001). Fracture stability determination and the decision to operate had the highest interobserver agreement. Fracture stability was the key determinant of treatment, rather than the Neer classification system or the size of the distal fragment. © 2015 The Author(s).

Enhancing navigation in biomedical databases by community voting and database-driven text classification

PubMed Central

Duchrow, Timo; Shtatland, Timur; Guettler, Daniel; Pivovarov, Misha; Kramer, Stefan; Weissleder, Ralph

2009-01-01

Background The breadth of biological databases and their information content continues to increase exponentially. Unfortunately, our ability to query such sources is still often suboptimal. Here, we introduce and apply community voting, database-driven text classification, and visual aids as a means to incorporate distributed expert knowledge, to automatically classify database entries and to efficiently retrieve them. Results Using a previously developed peptide database as an example, we compared several machine learning algorithms in their ability to classify abstracts of published literature results into categories relevant to peptide research, such as related or not related to cancer, angiogenesis, molecular imaging, etc. Ensembles of bagged decision trees met the requirements of our application best. No other algorithm consistently performed better in comparative testing. Moreover, we show that the algorithm produces meaningful class probability estimates, which can be used to visualize the confidence of automatic classification during the retrieval process. To allow viewing long lists of search results enriched by automatic classifications, we added a dynamic heat map to the web interface. We take advantage of community knowledge by enabling users to cast votes in Web 2.0 style in order to correct automated classification errors, which triggers reclassification of all entries. We used a novel framework in which the database "drives" the entire vote aggregation and reclassification process to increase speed while conserving computational resources and keeping the method scalable. In our experiments, we simulate community voting by adding various levels of noise to nearly perfectly labelled instances, and show that, under such conditions, classification can be improved significantly. Conclusion Using PepBank as a model database, we show how to build a classification-aided retrieval system that gathers training data from the community, is completely controlled by the database, scales well with concurrent change events, and can be adapted to add text classification capability to other biomedical databases. The system can be accessed at . PMID:19799796

A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.

PubMed

S K, Somasundaram; P, Alli

2017-11-09

The main complication of diabetes is Diabetic retinopathy (DR), retinal vascular disease and it leads to the blindness. Regular screening for early DR disease detection is considered as an intensive labor and resource oriented task. Therefore, automatic detection of DR diseases is performed only by using the computational technique is the great solution. An automatic method is more reliable to determine the presence of an abnormality in Fundus images (FI) but, the classification process is poorly performed. Recently, few research works have been designed for analyzing texture discrimination capacity in FI to distinguish the healthy images. However, the feature extraction (FE) process was not performed well, due to the high dimensionality. Therefore, to identify retinal features for DR disease diagnosis and early detection using Machine Learning and Ensemble Classification method, called, Machine Learning Bagging Ensemble Classifier (ML-BEC) is designed. The ML-BEC method comprises of two stages. The first stage in ML-BEC method comprises extraction of the candidate objects from Retinal Images (RI). The candidate objects or the features for DR disease diagnosis include blood vessels, optic nerve, neural tissue, neuroretinal rim, optic disc size, thickness and variance. These features are initially extracted by applying Machine Learning technique called, t-distributed Stochastic Neighbor Embedding (t-SNE). Besides, t-SNE generates a probability distribution across high-dimensional images where the images are separated into similar and dissimilar pairs. Then, t-SNE describes a similar probability distribution across the points in the low-dimensional map. This lessens the Kullback-Leibler divergence among two distributions regarding the locations of the points on the map. The second stage comprises of application of ensemble classifiers to the extracted features for providing accurate analysis of digital FI using machine learning. In this stage, an automatic detection of DR screening system using Bagging Ensemble Classifier (BEC) is investigated. With the help of voting the process in ML-BEC, bagging minimizes the error due to variance of the base classifier. With the publicly available retinal image databases, our classifier is trained with 25% of RI. Results show that the ensemble classifier can achieve better classification accuracy (CA) than single classification models. Empirical experiments suggest that the machine learning-based ensemble classifier is efficient for further reducing DR classification time (CT).

ON A POSSIBLE SIZE/COLOR RELATIONSHIP IN THE KUIPER BELT

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

Pike, R. E.; Kavelaars, J. J., E-mail: repike@uvic.ca

2013-10-01

Color measurements and albedo distributions introduce non-intuitive observational biases in size-color relationships among Kuiper Belt Objects (KBOs) that cannot be disentangled without a well characterized sample population with systematic photometry. Peixinho et al. report that the form of the KBO color distribution varies with absolute magnitude, H. However, Tegler et al. find that KBO color distributions are a property of object classification. We construct synthetic models of observed KBO colors based on two B-R color distribution scenarios: color distribution dependent on H magnitude (H-Model) and color distribution based on object classification (Class-Model). These synthetic B-R color distributions were modified tomore » account for observational flux biases. We compare our synthetic B-R distributions to the observed ''Hot'' and ''Cold'' detected objects from the Canada-France Ecliptic Plane Survey and the Meudon Multicolor Survey. For both surveys, the Hot population color distribution rejects the H-Model, but is well described by the Class-Model. The Cold objects reject the H-Model, but the Class-Model (while not statistically rejected) also does not provide a compelling match for data. Although we formally reject models where the structure of the color distribution is a strong function of H magnitude, we also do not find that a simple dependence of color distribution on orbit classification is sufficient to describe the color distribution of classical KBOs.« less

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

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

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

Adaptive Instructional Systems

DTIC Science & Technology

2005-09-01

Research Institute for the Behavior and Social Sciences 20050928 000 Approved for public release; distribution is unlimited. REPORT DOCUMENTATION PAGE...ADDRESS(ES) 10. MONITOR ACRONYM U. S. Army Research Institute for the Behavioral & Social ARI Sciences ATTN Rotary Wing Aviation Research Unit 11...Training Technology SECURITY CLASSIFICATION OF 19. LIMITATION OF 20. NUMBER 21. RESPONSIBLE PERSON ABSTRACT OF PAGES 16. REPORT 17. ABSTRACT 18. THIS

Innovative Acoustic Sensor Technologies for Leak Detection in Challenging Pipe Types

DTIC Science & Technology

2016-12-30

correlation features to detect and pinpoint leaks in challenging pipe types, as well as metallic pipes. 15. SUBJECT TERMS Leak detection; acoustic... correlation ; water distribution systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18.NUMBER OF PAGES 109 19a. NAME OF...6 1.3.2 State Regulations and Voluntary Water Industry Standards .......................... 7 2.0 TECHNOLOGY DESCRIPTION

Different patterns of lateral meniscus root tears in ACL injuries: application of a differentiated classification system.

PubMed

Forkel, Philipp; Reuter, Sven; Sprenker, Frederike; Achtnich, Andrea; Herbst, Elmar; Imhoff, Andreas; Petersen, Wolf

2015-01-01

Posterior lateral meniscus root tears (PLMRTs) affect the intra-articular pressure distribution in the lateral compartment of the knee. The biomechanical consequences of these injuries are significantly influenced by the integrity of the meniscofemoral ligaments (MFLs). A newly introduced arthroscopic classification system for PLMRTs that takes MFL integrity into account has not yet been clinically applied but may be useful in selecting the optimal method of PLMRT repair. Prospective ACL reconstruction data were collected. Concomitant injuries of the lateral meniscus posterior horn were classified according to their shape and MFL status. The classifications were: type 1, avulsion of the root; type 2, radial tear of the lateral meniscus posterior horn close to the root with an intact MFL; and type 3, complete detachment of the posterior meniscus horn. Between January 2011 and May 2012, 228 consecutive ACL reconstructions were included. Lateral and medial meniscus tears were identified in 38.2% (n = 87) and 44.7% (n = 102), respectively. Of the 87 lateral meniscus tears, 32 cases had PLMRTs; the overall prevalence of PLMRTs was 14% (n = 32). Two medial meniscus root tears were detected. All PLMRTs were classified according to the classification system described above, and the fixation procedure was adapted to the type of meniscus tear. The PLMRT tear is a common injury among patients undergoing ACL repair and can be arthroscopically classified into three different types. Medial meniscus root tears are rare in association with ACL tears. The PLMRT classification presented here may help to estimate the injury's impact on the lateral compartment and to identify the optimal treatment. These tears should not be overlooked, and the treatment strategy should be chosen with respect to the type of root tear. IV.

A Functional-Phylogenetic Classification System for Transmembrane Solute Transporters

PubMed Central

Saier, Milton H.

2000-01-01

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

Drinking Water Microbiome as a Screening Tool for ...

EPA Pesticide Factsheets

Many water utilities in the US using chloramine as disinfectant treatment in their distribution systems have experienced nitrification episodes, which detrimentally impact the water quality. A chloraminated drinking water distribution system (DWDS) simulator was operated through four successive operational schemes, including two stable events (SS) and an episode of nitrification (SF), followed by a ‘chlorine burn’ (SR) by switching disinfectant from chloramine to free chlorine. The current research investigated the viability of biological signatures as potential indicators of operational failure and predictors of nitrification in DWDS. For this purpose, we examined the bulk water (BW) bacterial microbiome of a chloraminated DWDS simulator operated through successive operational schemes, including an episode of nitrification. BW data was chosen because sampling of BW in a DWDS by water utility operators is relatively simpler and easier than collecting biofilm samples from underground pipes. The methodology applied a supervised classification machine learning approach (naïve Bayes algorithm) for developing predictive models for nitrification. Classification models were trained with biological datasets (Operational Taxonomic Unit [OTU] and genus-level taxonomic groups) generated using next generation high-throughput technology, and divided into two groups (i.e. binary) of positives and negatives (Failure and Stable, respectively). We also invest

Phylogenetic Inferences Reveal a Large Extent of Novel Biodiversity in Chemically Rich Tropical Marine Cyanobacteria

PubMed Central

Gunasekera, Sarath P.; Gerwick, William H.

2013-01-01

Benthic marine cyanobacteria are known for their prolific biosynthetic capacities to produce structurally diverse secondary metabolites with biomedical application and their ability to form cyanobacterial harmful algal blooms. In an effort to provide taxonomic clarity to better guide future natural product drug discovery investigations and harmful algal bloom monitoring, this study investigated the taxonomy of tropical and subtropical natural product-producing marine cyanobacteria on the basis of their evolutionary relatedness. Our phylogenetic inferences of marine cyanobacterial strains responsible for over 100 bioactive secondary metabolites revealed an uneven taxonomic distribution, with a few groups being responsible for the vast majority of these molecules. Our data also suggest a high degree of novel biodiversity among natural product-producing strains that was previously overlooked by traditional morphology-based taxonomic approaches. This unrecognized biodiversity is primarily due to a lack of proper classification systems since the taxonomy of tropical and subtropical, benthic marine cyanobacteria has only recently been analyzed by phylogenetic methods. This evolutionary study provides a framework for a more robust classification system to better understand the taxonomy of tropical and subtropical marine cyanobacteria and the distribution of natural products in marine cyanobacteria. PMID:23315747

Mapping lava morphology of the Galapagos Spreading Center at 92°W: fuzzy logic provides a classification of high-resolution bathymetry and backscatter

NASA Astrophysics Data System (ADS)

McClinton, J. T.; White, S. M.; Sinton, J. M.; Rubin, K. H.; Bowles, J. A.

2010-12-01

Differences in axial lava morphology along the Galapagos Spreading Center (GSC) can indicate variations in magma supply and emplacement dynamics due to the influence of the adjacent Galapagos hot spot. Unfortunately, the ability to discriminate fine-scale lava morphology has historically been limited to observations of the small coverage areas of towed camera surveys and submersible operations. This research presents a neuro-fuzzy approach to automated seafloor classification using spatially coincident, high-resolution bathymetry and backscatter data. The classification method implements a Sugeno-type fuzzy inference system trained by a multi-layered adaptive neural network and is capable of rapidly classifying seafloor morphology based on attributes of surface geometry and texture. The system has been applied to the 92°W segment of the western GSC in order to quantify coverage areas and distributions of pillow, lobate, and sheet lava morphology. An accuracy assessment has been performed on the classification results. The resulting classified maps provide a high-resolution view of GSC axial morphology and indicate the study area terrain is approximately 40% pillow flows, 40% lobate and sheet flows, and 10% fissured or faulted area, with about 10% of the study area unclassifiable. Fine-scale features such as eruptive fissures, tumuli, and individual pillowed lava flow fronts are also visible. Although this system has been applied to lava morphology, its design and implementation are applicable to other undersea mapping applications.

Seabed deposits classification at the Precious Stone Mountain hydrothermal field using MultiBeam sonar data

NASA Astrophysics Data System (ADS)

Tao, C.; Zhang, G.; Li, H.; Zhou, J.; Liu, W.; Deng, X.; Chen, S.

2013-12-01

The seabed deposits type and distribution are very complex at the hydrothermal field. In this paper, we provided an approach to study the seabed deposits classification at the Precious Stone Mountain hydrothermal field (PSMHF) using MultiBeam sonar data (Figure 1). The PSMHF was found in the Galapogas microplate at the Leg 3 of the Chinese COMRA 21st Cruise. Using this approach, the seabed deposits at the PSMHF are mainly classified into three types, which are rock, breccia and sediment, respectively. We can find the distribution of the three types of seabed deposits according to the sonar back-scattering data. The rocks are mostly distributed around the hydrothermal vent. The breccia are located at the foot of the vent. Most sediments are distributed at the southwest to the vent due to bottom current. Combining with seabed video, TV-Grab sample and the backscatter data, we draw the map of the seabed deposits distribution at the PSMHF (Figure 2). Figure 1 The flow chart of the seabed deposits classification approach Figure 2 The seabed deposits distribution of the PSMHF

A comparison of KABCO and AIS injury severity metrics using CODES linked data.

PubMed

Burch, Cynthia; Cook, Lawrence; Dischinger, Patricia

2014-01-01

The research objective is to compare the consistency of distributions between crash assigned (KABCO) and hospital assigned (Abbreviated Injury Scale, AIS) injury severity scoring systems for 2 states. The hypothesis is that AIS scores will be more consistent between the 2 studied states (Maryland and Utah) than KABCO. The analysis involved Crash Outcome Data Evaluation System (CODES) data from 2 states, Maryland and Utah, for years 2006-2008. Crash report and hospital inpatient data were linked probabilistically and International Classification of Diseases (CMS 2013) codes from hospital records were translated into AIS codes. KABCO scores from police crash reports were compared to those AIS scores within and between the 2 study states. Maryland appears to have the more severe crash report KABCO scoring for injured crash participants, with close to 50 percent of all injured persons being coded as a level B or worse, and Utah observes approximately 40 percent in this group. When analyzing AIS scores, some fluctuation was seen within states over time, but the distribution of MAIS is much more comparable between states. Maryland had approximately 85 percent of hospitalized injured cases coded as MAIS = 1 or minor. In Utah this percentage was close to 80 percent for all 3 years. This is quite different from the KABCO distributions, where Maryland had a smaller percentage of cases in the lowest injury severity category as compared to Utah. This analysis examines the distribution of 2 injury severity metrics different in both design and collection and found that both classifications are consistent within each state from 2006 to 2008. However, the distribution of both KABCO and Maximum Abbreviated Injury Scale (MAIS) varies between the states. MAIS was found to be more consistent between states than KABCO.

A Generalized Mixture Framework for Multi-label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We develop a novel probabilistic ensemble framework for multi-label classification that is based on the mixtures-of-experts architecture. In this framework, we combine multi-label classification models in the classifier chains family that decompose the class posterior distribution P(Y1, …, Yd|X) using a product of posterior distributions over components of the output space. Our approach captures different input–output and output–output relations that tend to change across data. As a result, we can recover a rich set of dependency relations among inputs and outputs that a single multi-label classification model cannot capture due to its modeling simplifications. We develop and present algorithms for learning the mixtures-of-experts models from data and for performing multi-label predictions on unseen data instances. Experiments on multiple benchmark datasets demonstrate that our approach achieves highly competitive results and outperforms the existing state-of-the-art multi-label classification methods. PMID:26613069

Classification of Stellar Spectra with Fuzzy Minimum Within-Class Support Vector Machine

NASA Astrophysics Data System (ADS)

Zhong-bao, Liu; Wen-ai, Song; Jing, Zhang; Wen-juan, Zhao

2017-06-01

Classification is one of the important tasks in astronomy, especially in spectra analysis. Support Vector Machine (SVM) is a typical classification method, which is widely used in spectra classification. Although it performs well in practice, its classification accuracies can not be greatly improved because of two limitations. One is it does not take the distribution of the classes into consideration. The other is it is sensitive to noise. In order to solve the above problems, inspired by the maximization of the Fisher's Discriminant Analysis (FDA) and the SVM separability constraints, fuzzy minimum within-class support vector machine (FMWSVM) is proposed in this paper. In FMWSVM, the distribution of the classes is reflected by the within-class scatter in FDA and the fuzzy membership function is introduced to decrease the influence of the noise. The comparative experiments with SVM on the SDSS datasets verify the effectiveness of the proposed classifier FMWSVM.

Bulk chemical compositions of Antarctic meteorites in the NIPR collection

NASA Astrophysics Data System (ADS)

Kimura, M.; Imae, N.; Yamaguchi, A.; Haramura, H.; Kojima, H.

2018-03-01

Bulk chemical compositions of meteorites were traditionally analyzed by wet chemical analysis, and NIPR has data for 1162 meteorites as of September 2017. We discuss the classification of meteorites on the basis of these data. Chondrite data are distributed in an anomalously wide range of compositions on the Urey-Craig diagram. One of the reasons for such wide distribution is terrestrial weathering producing Fe2O3-bearing phases from Fe-Ni metal and sulfides. Another important factor affecting the bulk compositional data is brecciation. Our observations indicate that many brecciated chondrites contain anomalously abundant opaque minerals, or are depleted in them, resulting in unusual compositions. In case of enstatite and some carbonaceous chondrites, the bulk compositions are distributed in wider ranges than reported before. The bulk compositions of HED meteorites are consistent with their mineralogy and classification. Our study suggests that wet chemical data are still significant for the meteorite classification. However, petrographic observation is indispensable for evaluating the bulk chemistry and classification of meteorites.

Maximum a posteriori classification of multifrequency, multilook, synthetic aperture radar intensity data

NASA Technical Reports Server (NTRS)

Rignot, E.; Chellappa, R.

1993-01-01

We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.

Phenomenology and classification of dystonia: a consensus update

PubMed Central

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

2013-01-01

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 three 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 two 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. PMID:23649720

Inferior turbinate classification system, grades 1 to 4: development and validation study.

PubMed

Camacho, Macario; Zaghi, Soroush; Certal, Victor; Abdullatif, Jose; Means, Casey; Acevedo, Jason; Liu, Stanley; Brietzke, Scott E; Kushida, Clete A; Capasso, Robson

2015-02-01

To develop a validated inferior turbinate grading scale. Development and validation study. Phase 1 development (alpha test) consisted of a proposal of 10 different inferior turbinate grading scales (>1,000 clinic patients). Phase 2 validation (beta test) utilized 10 providers grading 27 standardized endoscopic photos of inferior turbinates using two different classification systems. Phase 3 validation (pilot study) consisted of 100 live consecutive clinic patients (n = 200 inferior turbinates) who were each prospectively graded by 18 different combinations of two independent raters, and grading was repeated by each of the same two raters, two separate times for each patient. In the development phase, 25% (grades 1-4) and 33% (grades 1-4) were the most useful systems. In the validation phase, the 25% classification system was found to be the best balance between potential clinical utility and ability to grade; the photo grading demonstrated a Cohen's kappa (κ) = 0.4671 ± 0.0082 (moderate inter-rater agreement). Live-patient grading with the 25% classification system demonstrated an overall inter-rater reliability of 71.5% (95% confidence interval [CI]: 64.8-77.3), with overall substantial agreement (κ = 0.704 ± 0.028). Intrarater reliability was 91.5% (95% CI: 88.7-94.3). Distribution for the 200 inferior turbinates was as follows: 25% quartile = grade 1, 50% quartile (median) = grade 2, 75% quartile = grade 3, and 90% quartile = grade 4. Mean turbinate size was 2.22 (95% CI: 2.07-2.34; standard deviation 1.02). Categorical κ was as follows: grade 1, 0.8541 ± 0.0289; grade 2, 0.7310 ± 0.0289; grade 3, 0.6997 ± 0.0289, and grade 4, 0.7760 ± 0.0289. The 25% (grades 1-4) inferior turbinate classification system is a validated grading scale with high intrarater and inter-rater reliability. This system can facilitate future research by tracking the effect of interventions on inferior turbinates. 2c. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Colarco, Peter R.; Hlavka, Dennis; Levy, Robert C.; Vaughan, Mark A.; daSilva, Arlindo

2007-01-01

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Proposal of a new radiological classification system for spinal meningiomas as a descriptive tool and surgical guide.

PubMed

Bayoumi, Ahmed B; Laviv, Yosef; Yokus, Burhan; Efe, Ibrahim E; Toktas, Zafer Orkun; Kilic, Turker; Demir, Mustafa K; Konya, Deniz; Kasper, Ekkehard M

2017-11-01

1) To provide neurosurgeons and radiologists with a new quantitative and anatomical method to describe spinal meningiomas (SM) consistently. 2) To provide a guide to the surgical approach needed and amount of bony resection required based on the proposed classification. 3) To report the distribution of our 58 cases of SM over different Stages and Subtypes in correlation to the surgical treatment needed for each case. 4) To briefly review the literature on the rare non-conventional surgical corridors to resect SM. We reviewed the literature to report on previously published cohorts and classifications used to describe the location of the tumor inside the spinal canal. We reviewed the cases that were published prior showing non-conventional surgical approaches to resect spinal meningiomas. We proposed our classification system composed of Staging based on maximal cross-sectional surface area of tumor inside canal, Typing based on number of quadrants occupied by tumor and Subtyping based on location of the tumor bulk to spinal cord. Extradural and extra-spinal growth were also covered by our classification. We then applied it retrospectively on our 58 cases. 12 articles were published illustrating overlapping terms to describe spinal meningiomas. Another 7 articles were published reporting on 23 cases of anteriorly located spinal meningiomas treated with approaches other than laminectomies/laminoplasties. 4 Types, 9 Subtypes and 4 Stages were described in our Classification System. In our series of 58 patients, no midline anterior type was represented. Therefore, all our cases were treated by laminectomies or laminoplasties (with/without facetectomies) except a case with a paraspinal component where a costotransversectomy was needed. Spinal meningiomas can be radiologically described in a precise fashion. Selection of surgical corridor depends mainly on location of tumor bulk inside canal. Copyright © 2017 Elsevier B.V. All rights reserved.

The Novel Quantitative Technique for Assessment of Gait Symmetry Using Advanced Statistical Learning Algorithm

PubMed Central

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis. PMID:25705672

The novel quantitative technique for assessment of gait symmetry using advanced statistical learning algorithm.

PubMed

Wu, Jianning; Wu, Bin

2015-01-01

The accurate identification of gait asymmetry is very beneficial to the assessment of at-risk gait in the clinical applications. This paper investigated the application of classification method based on statistical learning algorithm to quantify gait symmetry based on the assumption that the degree of intrinsic change in dynamical system of gait is associated with the different statistical distributions between gait variables from left-right side of lower limbs; that is, the discrimination of small difference of similarity between lower limbs is considered the reorganization of their different probability distribution. The kinetic gait data of 60 participants were recorded using a strain gauge force platform during normal walking. The classification method is designed based on advanced statistical learning algorithm such as support vector machine algorithm for binary classification and is adopted to quantitatively evaluate gait symmetry. The experiment results showed that the proposed method could capture more intrinsic dynamic information hidden in gait variables and recognize the right-left gait patterns with superior generalization performance. Moreover, our proposed techniques could identify the small significant difference between lower limbs when compared to the traditional symmetry index method for gait. The proposed algorithm would become an effective tool for early identification of the elderly gait asymmetry in the clinical diagnosis.

Comparison of Program Effects: The Use of Mastery Scores.

ERIC Educational Resources Information Center

Yeh, Jennie P.; Moy, Raymond

The setting of a cut-off score on a mastery test usually involves a consideration of one or more of the following elements: (1) the distribution of observed test scores; (2) the type of mastery criterion used; (3) the level of acceptable risks of mis-classification; (4) the loss of functions of mis-classifications; and (5) the distribution of true…

Autoradiographic Distribution and Applied Pharmacological Characteristics of Dextromethorphan and Related Antitissue/Anticonvulsant Drugs and Novel Analogs

DTIC Science & Technology

1993-10-01

AD-A273 247 AD____ CONTRACT NO: DAMD17-90-C-0124 TITLE: AUTORADIOGRAPHIC DISTRIBUTION AND APPLIED PHARMACOLOGICAL CHARACTERISTICS OF DEXTROMETHORPHAN ...Anticonvulsants, Antitissue, Dextromethorphan , Autoradiography, Pharmacokinetics 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION...middle cerebral artery occlusion model with dextromethorphan , carbetapentane and three of the carbetapentane analogues, 11, B and D, which were

Mapping, classification, and spatial variation of hardbottom habitats in the northeastern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Kingon, Kelly

This dissertation starts by evaluating the applicability of using a commercially available, cost-effective, sidescan sonar system to detect benthic habitats, in particular hardbottom habitats, in the nearshore northeastern Gulf of Mexico. To illustrate the capability of low-cost devices in mapping benthic habitats, I tested the Humminbird 997c SI unit marketed to fishermen at a cost of approximately 2,000. Methodological approaches to effectively capture and process the Humminbird sidescan imagery were developed. Humminbird sidescan data from three sites were compared to overlapping sidescan imagery acquired by the National Marine Fisheries Service using a standard, much more expensive (˜20,000) Marine Sonic system. This analysis verified that the classification results of sand and hardbottom habitats based on data collected using the Humminbird sidescan system were similar to those produced using the traditional and more expensive Marine Sonic sidescan equipment. Thirty-three sites in total were then mapped with the Humminbird system and sampled using dive surveys. Seascape pattern metrics were calculated from the classified Humminbird sidescan maps. The dive survey data included measurements of the geomorphology, physical attributes of the water column (e.g. temperature, depth, and visibility), and coverage and heights of the benthic biota. The coverage and heights of the biota were compared to the geomorphology, seascape, and water column variables to identify patterns in the distribution and community composition of the sessile organisms. Within the study area, visibility was found to vary with longitude. Sites in the east showed higher visibility than sites in the west and this may be driving the community patterns that were identified. Relationships were identified between the four most abundant taxa (sponges, hard corals, brown algae, and red algae) and the geomorphology, physical, and seascape variables. However, the relationships were often complicated and the biota did not strictly follow gradients or boundaries in substrate or geoform (physical feature or landform), even though these features are often used to classify habitats and biotopes. The percent cover of rock was a significant geomorphology variable for red algae and hard coral coverage while geoforms were related to the heights of sponges and brown algae. Seascape metrics also had significant effects on the sessile biota particularly related to patch edges, heterogeneity, core areas, nearest neighbor distances, and the percent cover of hardbottom. Despite the fact that sessile organisms do not move much, if at all following their planktonic larval stage, the surrounding seascape contributes to the patterns we see in their distribution, coverage, and heights. The third chapter focuses on applying a new classification standard to the benthic habitats in the nearshore northeastern Gulf of Mexico. The United States Geological Survey (USGS) has a standardized system for classifying terrestrial and aquatic habitats found across the U.S. which has been in place for almost 40 years. This classification standard does not include marine and most coastal habitats. Therefore, marine researchers developed a number of classification systems for coastal and marine habitats relevant to their local or regional studies in U.S. waters. A national standardized method for classifying marine and coastal habitats was not adopted until recently. The Coastal and Marine Ecological Classification Standard (CMECS) developed by the Federal Geographic Data Committee was approved last year and is intended to fill the gap in U.S. marine habitat classification standards. Since the classification standard is in its infancy, it has not been applied in many geographic areas. My third chapter is the first study to apply the CMECS to the benthic habitats in the nearshore northeastern Gulf of Mexico off the coast of northwest Florida. Hardbottom and sand habitats are characteristic of this area. In the previous chapter, the underwater surveys revealed that the dominant taxa at the sites within the study area were hard corals, sponges, and macroalgae. I used CMECS to broadly classify the sites where the surveys were completed. I found that habitat heterogeneity and a wide variety of environmental characteristics influenced the distribution of taxa at the local scale. This made applying CMECS at scales finer than the composite study area unfeasible without major modifications. CMECS worked well for classifying the broad scale in this region but was not appropriate for classifying complex fine-scale biotopes. (Abstract shortened by UMI.)

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Using beta binomials to estimate classification uncertainty for ensemble models.

PubMed

Clark, Robert D; Liang, Wenkel; Lee, Adam C; Lawless, Michael S; Fraczkiewicz, Robert; Waldman, Marvin

2014-01-01

Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions. Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions. For artificial neural network ensembles (ANNEs) using two different methods for determining ensemble classification - one using vote tallies and the other averaging individual network outputs - we have found that the distribution of predictions across positive vote tallies can be reasonably well-modeled as a beta binomial distribution, as can the distribution of errors. Together, these two distributions can be used to estimate the probability that a given predictive classification will be in error. Large data sets comprised of logP, Ames mutagenicity, and CYP2D6 inhibition data are used to illustrate and validate the method. The distributions of predictions and errors for the training pool accurately predicted the distribution of predictions and errors for large external validation sets, even when the number of positive and negative examples in the training pool were not balanced. Moreover, the likelihood of a given compound being prospectively misclassified as a function of the degree of consensus between networks in the ensemble could in most cases be estimated accurately from the fitted beta binomial distributions for the training pool. Confidence in an individual predictive classification by an ensemble model can be accurately assessed by examining the distributions of predictions and errors as a function of the degree of agreement among the constituent submodels. Further, ensemble uncertainty estimation can often be improved by adjusting the voting or classification threshold based on the parameters of the error distribution. Finally, the profiles for models whose predictive uncertainty estimates are not reliable provide clues to that effect without the need for comparison to an external test set.

Synthesis and size classification of metal oxide nanoparticles for biomedical applications

NASA Astrophysics Data System (ADS)

Atsumi, Takashi; Jeyadevan, Balachandran; Sato, Yoshinori; Tamura, Kazuchika; Aiba, Setsuya; Tohji, Kazuyuki

2004-12-01

Magnetic nanoparticles are considered for biomedical applications, such as the medium in magnetic resonance imaging, hyperthermia, drug delivery, and for the purification or classification of DNA or virus. The performance of magnetic nanoparticles in biomedical application such as hyperthermia depends very much on the magnetic properties, size and size distribution. We briefly described the basic idea behind their use in drug delivery, magnetic separation and hyperthermia and discussed the prerequisite properties magnetic particles for biomedical applications. Finally reported the synthesis and classification scheme to prepare magnetite (Fe3O4) nanoparticles with narrow size distribution for magnetic fluid hyperthermia.

Empirically Estimable Classification Bounds Based on a Nonparametric Divergence Measure

PubMed Central

Berisha, Visar; Wisler, Alan; Hero, Alfred O.; Spanias, Andreas

2015-01-01

Information divergence functions play a critical role in statistics and information theory. In this paper we show that a non-parametric f-divergence measure can be used to provide improved bounds on the minimum binary classification probability of error for the case when the training and test data are drawn from the same distribution and for the case where there exists some mismatch between training and test distributions. We confirm the theoretical results by designing feature selection algorithms using the criteria from these bounds and by evaluating the algorithms on a series of pathological speech classification tasks. PMID:26807014

Real-time interactive 3D computer stereography for recreational applications

NASA Astrophysics Data System (ADS)

Miyazawa, Atsushi; Ishii, Motonaga; Okuzawa, Kazunori; Sakamoto, Ryuuichi

2008-02-01

With the increasing calculation costs of 3D computer stereography, low-cost, high-speed implementation of the latter requires effective distribution of computing resources. In this paper, we attempt to re-classify 3D display technologies on the basis of humans' 3D perception, in order to determine what level of presence or reality is required in recreational video game systems. We then discuss the design and implementation of stereography systems in two categories of the new classification.

Monte Carlo Bayesian System Reliability and MTBF-Confidence Assessment, II. Volume 2. SPARCS-2 Users Manual

DTIC Science & Technology

1978-03-01

1977 Approved for public release; distribution unlimited. AIR FORCE FLIGHT DYNAMICS LABORATORY AIR FORCE WRIGHT AERONAUTICAL LABORATORIES AIR FORCE...SYSTEMS COMMAND WRIGHT-PATTERSON AIR FORCE BASE, OHIO 45433 NOTI CE When Gove~inme~nt d’tawi~ngz, .6pe~c4Lcatiton, ct o-theAi da~ta cute -6e~d Joit any... AIR FORCE/56780/6 June 1978 -450 Unclassified SECURITY CLASSIFICATION OF THIS PAGE ("hen Date ýntered) READ INSTRUCTIONSREPORT DOCUMENTATION PAGE

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis.

PubMed

Sripada, Chandra Sekhar; Kessler, Daniel; Welsh, Robert; Angstadt, Michael; Liberzon, Israel; Phan, K Luan; Scott, Clayton

2013-11-01

Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks are potentially involved in the mechanisms by which methylphenidate improves attention functioning. Copyright © 2013 Elsevier Inc. All rights reserved.

Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

NASA Astrophysics Data System (ADS)

Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

2017-05-01

Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

The Distributed Wind Cost Taxonomy

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

Forsyth, Trudy; Jimenez, Tony; Preus, Robert

To date, there has been no standard method or tool to analyze the installed and operational costs for distributed wind turbine systems. This report describes the development of a classification system, or taxonomy, for distributed wind turbine project costs. The taxonomy establishes a framework to help collect, sort, and compare distributed wind cost data that mirrors how the industry categorizes information. The taxonomy organizes costs so they can be aggregated from installers, developers, vendors, and other sources without losing cost details. Developing a peer-reviewed taxonomy is valuable to industry stakeholders because a common understanding the details of distributed wind turbinemore » costs and balance of station costs is a first step to identifying potential high-value cost reduction opportunities. Addressing cost reduction potential can help increase distributed wind's competitiveness and propel the U.S. distributed wind industry forward. The taxonomy can also be used to perform cost comparisons between technologies and track trends for distributed wind industry costs in the future. As an initial application and piloting of the taxonomy, preliminary cost data were collected for projects of different sizes and from different regions across the contiguous United States. Following the methods described in this report, these data are placed into the established cost categories.« less

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

PubMed

Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

2018-04-18

There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

Vegetation classification, mapping, and monitoring at Voyageurs National Park, Minnesota: An application of the U.S. National Vegetation Classification

USGS Publications Warehouse

Faber-Langendoen, D.; Aaseng, N.; Hop, K.; Lew-Smith, M.; Drake, J.

2007-01-01

Question: How can the U.S. National Vegetation Classification (USNVC) serve as an effective tool for classifying and mapping vegetation, and inform assessments and monitoring? Location: Voyageurs National Park, northern Minnesota, U.S.A and environs. The park contains 54 243 ha of terrestrial habitat in the sub-boreal region of North America. Methods: We classified and mapped the natural vegetation using the USNVC, with 'alliance' and 'association' as base units. We compiled 259 classification plots and 1251 accuracy assessment test plots. Both plot and type ordinations were used to analyse vegetation and environmental patterns. Color infrared aerial photography (1:15840 scale) was used for mapping. Polygons were manually drawn, then transferred into digital form. Classification and mapping products are stored in publicly available databases. Past fire and logging events were used to assess distribution of forest types. Results and Discussion: Ordination and cluster analyses confirmed 49 associations and 42 alliances, with three associations ranked as globally vulnerable to extirpation. Ordination provided a useful summary of vegetation and ecological gradients. Overall map accuracy was 82.4%. Pinus banksiana - Picea mariana forests were less frequent in areas unburned since the 1930s. Conclusion: The USNVC provides a consistent ecological tool for summarizing and mapping vegetation. The products provide a baseline for assessing forests and wetlands, including fire management. The standardized classification and map units provide local to continental perspectives on park resources through linkages to state, provincial, and national classifications in the U.S. and Canada, and to NatureServe's Ecological Systems classification. ?? IAVS; Opulus Press.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders.

PubMed

Subasi, Abdulhamit

2013-06-01

Support vector machine (SVM) is an extensively used machine learning method with many biomedical signal classification applications. In this study, a novel PSO-SVM model has been proposed that hybridized the particle swarm optimization (PSO) and SVM to improve the EMG signal classification accuracy. This optimization mechanism involves kernel parameter setting in the SVM training procedure, which significantly influences the classification accuracy. The experiments were conducted on the basis of EMG signal to classify into normal, neurogenic or myopathic. In the proposed method the EMG signals were decomposed into the frequency sub-bands using discrete wavelet transform (DWT) and a set of statistical features were extracted from these sub-bands to represent the distribution of wavelet coefficients. The obtained results obviously validate the superiority of the SVM method compared to conventional machine learning methods, and suggest that further significant enhancements in terms of classification accuracy can be achieved by the proposed PSO-SVM classification system. The PSO-SVM yielded an overall accuracy of 97.41% on 1200 EMG signals selected from 27 subject records against 96.75%, 95.17% and 94.08% for the SVM, the k-NN and the RBF classifiers, respectively. PSO-SVM is developed as an efficient tool so that various SVMs can be used conveniently as the core of PSO-SVM for diagnosis of neuromuscular disorders. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Juniati, E.; Arrofiqoh, E. N.

2017-09-01

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

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

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

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

Effective classification of the prevalence of Schistosoma mansoni.

PubMed

Mitchell, Shira A; Pagano, Marcello

2012-12-01

To present an effective classification method based on the prevalence of Schistosoma mansoni in the community. We created decision rules (defined by cut-offs for number of positive slides), which account for imperfect sensitivity, both with a simple adjustment of fixed sensitivity and with a more complex adjustment of changing sensitivity with prevalence. To reduce screening costs while maintaining accuracy, we propose a pooled classification method. To estimate sensitivity, we use the De Vlas model for worm and egg distributions. We compare the proposed method with the standard method to investigate differences in efficiency, measured by number of slides read, and accuracy, measured by probability of correct classification. Modelling varying sensitivity lowers the lower cut-off more significantly than the upper cut-off, correctly classifying regions as moderate rather than lower, thus receiving life-saving treatment. The classification method goes directly to classification on the basis of positive pools, avoiding having to know sensitivity to estimate prevalence. For model parameter values describing worm and egg distributions among children, the pooled method with 25 slides achieves an expected 89.9% probability of correct classification, whereas the standard method with 50 slides achieves 88.7%. Among children, it is more efficient and more accurate to use the pooled method for classification of S. mansoni prevalence than the current standard method. © 2012 Blackwell Publishing Ltd.

Design and update of a classification system: the UCSD map of science.

PubMed

Börner, Katy; Klavans, Richard; Patek, Michael; Zoss, Angela M; Biberstine, Joseph R; Light, Robert P; Larivière, Vincent; Boyack, Kevin W

2012-01-01

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier's Scopus (about 15,000 source titles, 2001-2005) and Thomson Reuters' Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001-2004)-about 16,000 unique source titles. The updated map and classification adds six years (2005-2010) of WoS data and three years (2006-2008) from Scopus to the existing category structure-increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others.

Design and Update of a Classification System: The UCSD Map of Science

PubMed Central

Börner, Katy; Klavans, Richard; Patek, Michael; Zoss, Angela M.; Biberstine, Joseph R.; Light, Robert P.; Larivière, Vincent; Boyack, Kevin W.

2012-01-01

Global maps of science can be used as a reference system to chart career trajectories, the location of emerging research frontiers, or the expertise profiles of institutes or nations. This paper details data preparation, analysis, and layout performed when designing and subsequently updating the UCSD map of science and classification system. The original classification and map use 7.2 million papers and their references from Elsevier’s Scopus (about 15,000 source titles, 2001–2005) and Thomson Reuters’ Web of Science (WoS) Science, Social Science, Arts & Humanities Citation Indexes (about 9,000 source titles, 2001–2004)–about 16,000 unique source titles. The updated map and classification adds six years (2005–2010) of WoS data and three years (2006–2008) from Scopus to the existing category structure–increasing the number of source titles to about 25,000. To our knowledge, this is the first time that a widely used map of science was updated. A comparison of the original 5-year and the new 10-year maps and classification system show (i) an increase in the total number of journals that can be mapped by 9,409 journals (social sciences had a 80% increase, humanities a 119% increase, medical (32%) and natural science (74%)), (ii) a simplification of the map by assigning all but five highly interdisciplinary journals to exactly one discipline, (iii) a more even distribution of journals over the 554 subdisciplines and 13 disciplines when calculating the coefficient of variation, and (iv) a better reflection of journal clusters when compared with paper-level citation data. When evaluating the map with a listing of desirable features for maps of science, the updated map is shown to have higher mapping accuracy, easier understandability as fewer journals are multiply classified, and higher usability for the generation of data overlays, among others. PMID:22808037

The anti-hepatitis drug use effect and inventory management optimization from the perspective of hospital drug supply chain.

PubMed

Liu, Zhanyu

2017-09-01

By analyzing the current hospital anti hepatitis drug use, dosage, indications and drug resistance, this article studied the drug inventory management and cost optimization. The author used drug utilization evaluation method, analyzed the amount and kind distribution of anti hepatitis drugs and made dynamic monitoring of inventory. At the same time, the author puts forward an effective scheme of drug classification management, uses the ABC classification method to classify the drugs according to the average daily dose of drugs, and implements the automatic replenishment plan. The design of pharmaceutical services supply chain includes drug procurement platform, warehouse management system and connect to the hospital system through data exchange. Through the statistical analysis of drug inventory, we put forward the countermeasures of drug logistics optimization. The results showed that drug replenishment plan can effectively improve drugs inventory efficiency.

Prediction of bioavailability of selected bisphosphonates using in silico methods towards categorization into a biopharmaceutical classification system.

PubMed

Biernacka, Joanna; Betlejewska-Kielak, Katarzyna; Kłosińska-Szmurło, Ewa; Pluciński, Franciszek A; Mazurek, Aleksander P

2013-01-01

The physicochemical properties relevant to biological activity of selected bisphosphonates such as clodronate disodium salt, etidronate disodium salt, pamidronate disodium salt, alendronate sodium salt, ibandronate sodium salt, risedronate sodium salt and zoledronate disodium salt were determined using in silico methods. The main aim of our research was to investigate and propose molecular determinants thataffect bioavailability of above mentioned compounds. These determinants are: stabilization energy (deltaE), free energy of solvation (deltaG(solv)), electrostatic potential, dipole moment, as well as partition and distribution coefficients estimated by the log P and log D values. Presented values indicate that selected bisphosphonates a recharacterized by high solubility and low permeability. The calculated parameters describing both solubility and permeability through biological membranes seem to be a good bioavailability indicators of bisphosphonates examined and can be a useful tool to include into Biopharmaceutical Classification System (BCS) development.

Heterogeneity of road traffic accident rate in the Russian cities and the need of usage various methods of transport safety management

NASA Astrophysics Data System (ADS)

Petrov, A. I.; Petrova, D. A.

2017-10-01

The article considers one of the topical problems of road safety management at the federal level - the problem of the heterogeneity of road traffic accident rate in Russian cities. The article analyzes actual statistical data on road traffic accident rate in the administrative centers of Russia. The histograms of the distribution of the values of two most important road accidents characteristics - Social Risk HR and Severity Rate of Road Accidents - formed in 2016 in administrative centers of Russia are presented. On the basis of the regression model of the statistical connection between Severity Rate of Road Accidents and Social Risk HR, a classification of the Russian cities based on the level of actual road traffic accident rate was developed. On the basis of this classification a differentiated system of priority methods for organizing the safe functioning of transport systems in the cities of Russia is proposed.

The use of computer-assisted image analysis in the evaluation of the effect of management systems on changes in the color, chemical composition and texture of m. longissimus dorsi in pigs.

PubMed

Zapotoczny, Piotr; Kozera, Wojciech; Karpiesiuk, Krzysztof; Pawłowski, Rodian

2014-08-01

The effect of management systems on selected physical properties and chemical composition of m. longissimus dorsi was studied in pigs. Muscle texture parameters were determined by computer-assisted image analysis, and the color of muscle samples was evaluated using a spectrophotometer. Highly significant correlations were observed between chemical composition and selected texture variables in the analyzed images. Chemical composition was not correlated with color or spectral distribution. Subject to the applied classification methods and groups of variables included in the classification model, the experimental groups were identified correctly in 35-95%. No significant differences in the chemical composition of m. longissimus dorsi were observed between experimental groups. Significant differences were noted in color lightness (L*) and redness (a*). Copyright © 2014 Elsevier Ltd. All rights reserved.

3D shape representation with spatial probabilistic distribution of intrinsic shape keypoints

NASA Astrophysics Data System (ADS)

Ghorpade, Vijaya K.; Checchin, Paul; Malaterre, Laurent; Trassoudaine, Laurent

2017-12-01

The accelerated advancement in modeling, digitizing, and visualizing techniques for 3D shapes has led to an increasing amount of 3D models creation and usage, thanks to the 3D sensors which are readily available and easy to utilize. As a result, determining the similarity between 3D shapes has become consequential and is a fundamental task in shape-based recognition, retrieval, clustering, and classification. Several decades of research in Content-Based Information Retrieval (CBIR) has resulted in diverse techniques for 2D and 3D shape or object classification/retrieval and many benchmark data sets. In this article, a novel technique for 3D shape representation and object classification has been proposed based on analyses of spatial, geometric distributions of 3D keypoints. These distributions capture the intrinsic geometric structure of 3D objects. The result of the approach is a probability distribution function (PDF) produced from spatial disposition of 3D keypoints, keypoints which are stable on object surface and invariant to pose changes. Each class/instance of an object can be uniquely represented by a PDF. This shape representation is robust yet with a simple idea, easy to implement but fast enough to compute. Both Euclidean and topological space on object's surface are considered to build the PDFs. Topology-based geodesic distances between keypoints exploit the non-planar surface properties of the object. The performance of the novel shape signature is tested with object classification accuracy. The classification efficacy of the new shape analysis method is evaluated on a new dataset acquired with a Time-of-Flight camera, and also, a comparative evaluation on a standard benchmark dataset with state-of-the-art methods is performed. Experimental results demonstrate superior classification performance of the new approach on RGB-D dataset and depth data.

A new map of standardized terrestrial ecosystems of Africa

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Hak, Jon; Josse, Carmen; Bow, Jacquie; Warner, Harumi; Larwanou, Mahamane; Kelbessa, Ensermu; Bekele, Tamrat; Kehl, Harald; Amena, Ruba; Andriamasimanana, Rado; Ba, Taibou; Benson, Laurence; Boucher, Timothy; Brown, Matthew; Cress, Jill J.; Dassering, Oueddo; Friesen, Beverly A.; Gachathi, Francis; Houcine, Sebei; Keita, Mahamadou; Khamala, Erick; Marangu, Dan; Mokua, Fredrick; Morou, Boube; Mucina, Ladislav; Mugisha, Samuel; Mwavu, Edward; Rutherford, Michael; Sanou, Patrice; Syampungani, Stephen; Tomor, Bojoi; Vall, Abdallahi Ould Mohamed; Vande Weghe, Jean Pierre; Wangui, Eunice; Waruingi, Lucy

2013-01-01

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

Distributed Fusion in Sensor Networks with Information Genealogy

DTIC Science & Technology

2011-06-28

image processing [2], acoustic and speech recognition [3], multitarget tracking [4], distributed fusion [5], and Bayesian inference [6-7]. For...Adaptation for Distant-Talking Speech Recognition." in Proc Acoustics. Speech , and Signal Processing, 2004 |4| Y Bar-Shalom and T 1-. Fortmann...used in speech recognition and other classification applications [8]. But their use in underwater mine classification is limited. In this paper, we

An Overview of Production Systems

DTIC Science & Technology

1975-10-01

DISTRIBUTED BY: Matonal Tochnica! Infonu srice U. S. DEPARTMENT OF COMMERCE 028143 Stanford Artificil Inteligence Laboratory October 1975 Memo AIM-271...ORGANIZATION NAMEL AND ADDRESS 18. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AE OKUI UBR Stanford University ARPA Order 249...014-64011I j SEC-jRITY CLASSIFICATION OF THIS PAGE (When, Data bHISP011 A Stanford Artificial ktteligncs Laboratory October 1975 Memo AIM-271 Computer

Scattering from Rock and Rock Outcrops

DTIC Science & Technology

2018-01-23

scattering and rough areas as seen on the rock outcrop in Fig. 1, display high variability which could pose difficulty for target detection and...classification systems. The primary long-term goal of this research project is to increase understanding and modeling capabilities for high -frequency acoustic...Arlington, VA 22203-1995 10. SPONSOR/MONITOR’S ACRONYM(S) BD025 11. SPONSORING/MONITORING AGENCY REPORT NUMBER 12. DISTRIBUTION AVAILABILITY

Review of the temporal and geographical distribution of measles virus genotypes in the prevaccine and postvaccine eras

PubMed Central

Riddell, Michaela A; Rota, Jennifer S; Rota, Paul A

2005-01-01

Molecular epidemiological investigation of measles outbreaks can document the interruption of endemic measles transmission and is useful for establishing and clarifying epidemiological links between cases in geographically distinct clusters. To determine the distribution of measles virus genotypes in the prevaccine and postvaccine eras, a literature search of biomedical databases, measles surveillance websites and other electronic sources was conducted for English language reports of measles outbreaks or genetic characterization of measles virus isolates. Genotype assignments based on classification systems other than the currently accepted WHO nomenclature were reassigned using the current criteria. This review gives a comprehensive overview of the distribution of MV genotypes in the prevaccine and postvaccine eras and describes the geographically diverse distribution of some measles virus genotypes and the localized distributions of other genotypes. PMID:16303052

Evaluation of Barrier Cable Impact Pad Materials

DTIC Science & Technology

1988-03-01

INFORMATION CENTER CAMERON STATION ALEXANDRIA, VIRGINIA 22314 Unclassified SECURITY CLASSIFICATION OF THIS PAGE Form Approved REPORT DOCUMENTATION PAGE OMB...No. 0704-0188 _____________________________________________Exp. Date: Jun 30, 1986 la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS...Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAILABILITY OF REPORT 2b. DECLASSIFICATION/DOWNGRADING SCHEDULE Approved for public

Automatic Classification of Medical Text: The Influence of Publication Form1

PubMed Central

Cole, William G.; Michael, Patricia A.; Stewart, James G.; Blois, Marsden S.

1988-01-01

Previous research has shown that within the domain of medical journal abstracts the statistical distribution of words is neither random nor uniform, but is highly characteristic. Many words are used mainly or solely by one medical specialty or when writing about one particular level of description. Due to this regularity of usage, automatic classification within journal abstracts has proved quite successful. The present research asks two further questions. It investigates whether this statistical regularity and automatic classification success can also be achieved in medical textbook chapters. It then goes on to see whether the statistical distribution found in textbooks is sufficiently similar to that found in abstracts to permit accurate classification of abstracts based solely on previous knowledge of textbooks. 14 textbook chapters and 45 MEDLINE abstracts were submitted to an automatic classification program that had been trained only on chapters drawn from a standard textbook series. Statistical analysis of the properties of abstracts vs. chapters revealed important differences in word use. Automatic classification performance was good for chapters, but poor for abstracts.

Raster Vs. Point Cloud LiDAR Data Classification

NASA Astrophysics Data System (ADS)

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 classification results can be achieved by using the proposed approach.

The Geogenomic Mutational Atlas of Pathogens (GoMAP) Web System

PubMed Central

Sargeant, David P.; Hedden, Michael W.; Deverasetty, Sandeep; Strong, Christy L.; Alaniz, Izua J.; Bartlett, Alexandria N.; Brandon, Nicholas R.; Brooks, Steven B.; Brown, Frederick A.; Bufi, Flaviona; Chakarova, Monika; David, Roxanne P.; Dobritch, Karlyn M.; Guerra, Horacio P.; Levit, Kelvy S.; Mathew, Kiran R.; Matti, Ray; Maza, Dorothea Q.; Mistry, Sabyasachy; Novakovic, Nemanja; Pomerantz, Austin; Rafalski, Timothy F.; Rathnayake, Viraj; Rezapour, Noura; Ross, Christian A.; Schooler, Steve G.; Songao, Sarah; Tuggle, Sean L.; Wing, Helen J.; Yousif, Sandy; Schiller, Martin R.

2014-01-01

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/ PMID:24675726

The Geogenomic Mutational Atlas of Pathogens (GoMAP) web system.

PubMed

Sargeant, David P; Hedden, Michael W; Deverasetty, Sandeep; Strong, Christy L; Alaniz, Izua J; Bartlett, Alexandria N; Brandon, Nicholas R; Brooks, Steven B; Brown, Frederick A; Bufi, Flaviona; Chakarova, Monika; David, Roxanne P; Dobritch, Karlyn M; Guerra, Horacio P; Levit, Kelvy S; Mathew, Kiran R; Matti, Ray; Maza, Dorothea Q; Mistry, Sabyasachy; Novakovic, Nemanja; Pomerantz, Austin; Rafalski, Timothy F; Rathnayake, Viraj; Rezapour, Noura; Ross, Christian A; Schooler, Steve G; Songao, Sarah; Tuggle, Sean L; Wing, Helen J; Yousif, Sandy; Schiller, Martin R

2014-01-01

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Cloud field classification based on textural features

NASA Technical Reports Server (NTRS)

Sengupta, Sailes Kumar

1989-01-01

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes of features. Preliminary results based on the GLDV textural features alone look promising.

The applicability of new TNM classification for humanpapilloma virus-related oropharyngeal cancer in the 8th edition of the AJCC/UICC TNM staging system in Japan: A single-centre study.

PubMed

Sano, Daisuke; Yabuki, Kenichiro; Arai, Yasuhiro; Tanabe, Teruhiko; Chiba, Yoshihiro; Nishimura, Goshi; Takahashi, Hideaki; Yamanaka, Shoji; Oridate, Nobuhiko

2018-06-01

The purpose of this study is to validate the applicability of new TNM classification for human papillomavirus (HPV)-related oropharyngeal cancer (OPC) in the 8th edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) TNM staging system in Japan. A total of 91 OPC patients treated with radiation-based therapy between November 2001 and July 2015 were analyzed retrospectively in this study. HPV infection status was evaluated using tumor p16 expression. 40 OPC patients (44.0%) had HPV-positive disease in this study. The distribution of disease stage of HPV-positive OPC patients dramatically changed from the 7th edition to the 8th edition of AJCC/UICC TNM classification. However, neither the 8th edition nor the 7th edition of the AJCC/UICC TNM staging system could adequately predict outcomes of HPV-positive OPC patients in our patient series. On the other hand, our multivariate analysis indicated that matted nodes and age ≥63 were independent prognostic factors for progression-free survival. In addition, HPV-positive OPC patients with stage I without matted nodes showed significantly better overall and progression-free survival compared with those with stage I with matted nodes and stages II and III in the 8th edition of the AJCC/UICC TNM staging system (P=0.008, and P=0.043, respectively). Our results suggested that matted nodes of HPV-positive OPC patients might be additionally examined to apply the 8th edition of AJCC/UICC TNM classification for more adequate predicting outcomes of HPV-positive OPC patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Comprehensive AOCMF Classification System: Mandible Fractures- Level 2 Tutorial

PubMed Central

Cornelius, Carl-Peter; Audigé, Laurent; Kunz, Christoph; Rudderman, Randal; Buitrago-Téllez, Carlos H.; Frodel, John; Prein, Joachim

2014-01-01

This tutorial outlines the details of the AOCMF image-based classification system for fractures of the mandible at the precision level 2 allowing description of their topographical distribution. A short introduction about the anatomy is made. Mandibular fractures are classified by the anatomic regions involved. For this purpose, the mandible is delineated into an array of nine regions identified by letters: the symphysis/parasymphysis region anteriorly, two body regions on each lateral side, combined angle and ascending ramus regions, and finally the condylar and coronoid processes. A precise definition of the demarcation lines between these regions is given for the unambiguous allocation of fractures. Four transition zones allow an accurate topographic assignment if fractures end up in or run across the borders of anatomic regions. These zones are defined between angle/ramus and body, and between body and symphysis/parasymphysis. A fracture is classified as “confined” as long as it is located within a region, in contrast to a fracture being “nonconfined” when it extents to an adjoining region. Illustrations and case examples of mandible fractures are presented to become familiar with the classification procedure in daily routine. PMID:25489388

Durability of classification and action learning: differences revealed using ex-Gaussian distribution analysis.

PubMed

Moutsopoulou, Karolina; Waszak, Florian

2013-05-01

It has been shown that in associative learning it is possible to disentangle the effects caused on behaviour by the associations between a stimulus and a classification (S-C) and the associations between a stimulus and the action performed towards it (S-A). Such evidence has been provided using ex-Gaussian distribution analysis to show that different parameters of the reaction time distribution reflect the different processes. Here, using this method, we investigate another difference between these two types of associations: What is the relative durability of these associations across time? Using a task-switching paradigm and by manipulating the lag between the point of the creation of the associations and the test phase, we show that S-A associations have stronger effects on behaviour when the lag between the two repetitions of a stimulus is short. However, classification learning affects behaviour not only in short-term lags but also (and equally so) when the lag between prime and probe is long and the same stimuli are repeatedly presented within a different classification task, demonstrating a remarkable durability of S-C associations.

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

NASA Astrophysics Data System (ADS)

Hu, G. C.; Zhao, Q. H.

2017-09-01

Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

Ecological Land Classification: Applications to Identify the Productive Potential of Southern Forests

Treesearch

Dennis L. Mengel; D. Thompson Tew; [Editors

1991-01-01

Eighteen papers representing four categories-Regional Overviews; Classification System Development; Classification System Interpretation; Mapping/GIS Applications in Classification Systems-present the state of the art in forest-land classification and evaluation in the South. In addition, nine poster papers are presented.

A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment

NASA Astrophysics Data System (ADS)

Gundreddy, Rohith Reddy; Tan, Maxine; Qui, Yuchen; Zheng, Bin

2015-03-01

The purpose of this study is to develop and test a new content-based image retrieval (CBIR) scheme that enables to achieve higher reproducibility when it is implemented in an interactive computer-aided diagnosis (CAD) system without significantly reducing lesion classification performance. This is a new Fourier transform based CBIR algorithm that determines image similarity of two regions of interest (ROI) based on the difference of average regional image pixel value distribution in two Fourier transform mapped images under comparison. A reference image database involving 227 ROIs depicting the verified soft-tissue breast lesions was used. For each testing ROI, the queried lesion center was systematically shifted from 10 to 50 pixels to simulate inter-user variation of querying suspicious lesion center when using an interactive CAD system. The lesion classification performance and reproducibility as the queried lesion center shift were assessed and compared among the three CBIR schemes based on Fourier transform, mutual information and Pearson correlation. Each CBIR scheme retrieved 10 most similar reference ROIs and computed a likelihood score of the queried ROI depicting a malignant lesion. The experimental results shown that three CBIR schemes yielded very comparable lesion classification performance as measured by the areas under ROC curves with the p-value greater than 0.498. However, the CBIR scheme using Fourier transform yielded the highest invariance to both queried lesion center shift and lesion size change. This study demonstrated the feasibility of improving robustness of the interactive CAD systems by adding a new Fourier transform based image feature to CBIR schemes.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

PubMed Central

Ma, Yue; Tuskan, Gerald A.

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. PMID:29686995

Restricted Boltzmann machines based oversampling and semi-supervised learning for false positive reduction in breast CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Bao, Hang; Yang, Jinzhu; Zhao, Dazhe

2015-01-01

The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these challenges, we propose oversampling and semi-supervised learning methods based on the restricted Boltzmann machines (RBMs) to solve the classification of imbalanced data with a few labeled samples. To evaluate the proposed method, we conducted a comprehensive performance study and compared its results with the commonly used techniques. Experiments on benchmark dataset of DDSM demonstrate the effectiveness of the RBMs based oversampling and semi-supervised learning method in terms of geometric mean (G-mean) for false positive reduction in Breast CAD.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

Performance analysis of mineral mapping method to delineate mineralization zones under tropical region

NASA Astrophysics Data System (ADS)

Wakila, M. H.; Saepuloh, A.; Heriawan, M. N.; Susanto, A.

2016-09-01

Geothermal explorations and productions are currently being intensively conducted at certain areas in Indonesia such as Wayang Windu Geothermal Field (WWGF) in West Java, Indonesia. The WWGF is located at wide area covering about 40 km2. An accurate method to map the distribution of heterogeneity minerals is necessary for wide areas such as WWGF. Mineral mapping is an important method in geothermal explorations to determine the distribution of minerals which indicate the surface manifestations of geothermal system. This study is aimed to determine the most precise and accurate methods for minerals mapping at geothermal field. Field measurements were performed to assess the accuracy of three proposed methods: 1) Minimum Noise Fraction (MNF), utilizing the linear transformation method to eliminate the correlation among the spectra bands and to reduce the noise in the data, 2) Pixel Purity Index (PPI), a designed method to find the most extreme spectrum pixels and their characteristics due to end-members mixing, 3) Spectral Angle Mapper (SAM), an image classification technique by measuring the spectral similarity between an unknown object with spectral reference in n- dimension. The output of those methods were mineral distribution occurrence. The performance of each mapping method was analyzed based on the ground truth data. Among the three proposed method, the SAM classification method is the most appropriate and accurate for mineral mapping related to spatial distribution of alteration minerals.

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

Hussain, Hameed; Malik, Saif Ur Rehman; Hameed, Abdul

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement ofmore » all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.« less

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

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

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

Technical support for creating an artificial intelligence system for feature extraction and experimental design

NASA Technical Reports Server (NTRS)

Glick, B. J.

1985-01-01

Techniques for classifying objects into groups or clases go under many different names including, most commonly, cluster analysis. Mathematically, the general problem is to find a best mapping of objects into an index set consisting of class identifiers. When an a priori grouping of objects exists, the process of deriving the classification rules from samples of classified objects is known as discrimination. When such rules are applied to objects of unknown class, the process is denoted classification. The specific problem addressed involves the group classification of a set of objects that are each associated with a series of measurements (ratio, interval, ordinal, or nominal levels of measurement). Each measurement produces one variable in a multidimensional variable space. Cluster analysis techniques are reviewed and methods for incuding geographic location, distance measures, and spatial pattern (distribution) as parameters in clustering are examined. For the case of patterning, measures of spatial autocorrelation are discussed in terms of the kind of data (nominal, ordinal, or interval scaled) to which they may be applied.

Updating Landsat-derived land-cover maps using change detection and masking techniques

NASA Technical Reports Server (NTRS)

Likens, W.; Maw, K.

1982-01-01

The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

Multiresolution texture analysis applied to road surface inspection

NASA Astrophysics Data System (ADS)

Paquis, Stephane; Legeay, Vincent; Konik, Hubert; Charrier, Jean

1999-03-01

Technological advances provide now the opportunity to automate the pavement distress assessment. This paper deals with an approach for achieving an automatic vision system for road surface classification. Road surfaces are composed of aggregates, which have a particular grain size distribution and a mortar matrix. From various physical properties and visual aspects, four road families are generated. We present here a tool using a pyramidal process with the assumption that regions or objects in an image rise up because of their uniform texture. Note that the aim is not to compute another statistical parameter but to include usual criteria in our method. In fact, the road surface classification uses a multiresolution cooccurrence matrix and a hierarchical process through an original intensity pyramid, where a father pixel takes the minimum gray level value of its directly linked children pixels. More precisely, only matrix diagonal is taken into account and analyzed along the pyramidal structure, which allows the classification to be made.

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

PubMed Central

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

2014-01-01

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

Queueing analysis of a canonical model of real-time multiprocessors

NASA Technical Reports Server (NTRS)

Krishna, C. M.; Shin, K. G.

1983-01-01

A logical classification of multiprocessor structures from the point of view of control applications is presented. A computation of the response time distribution for a canonical model of a real time multiprocessor is presented. The multiprocessor is approximated by a blocking model. Two separate models are derived: one created from the system's point of view, and the other from the point of view of an incoming task.

A Critical Review of Options for Tool and Workpiece Sensing

DTIC Science & Technology

1989-06-02

Tool Temperature Control ." International Machine Tool Design Res., Vol. 7, pp. 465-75, 1967. 5. Cook, N. H., Subramanian, K., and Basile, S. A...if necessury and identify by block riumber) FIELD GROUP SUB-GROUP 1. Detectors 3. Control Equipment 1 08 2. Sensor Characteristics 4. Process Control ...will provide conceptual designs and recommend a system (Continued) 20. DISTRIBUTION/AVAILABILITY OF ABSTRACT 21 ABSTRACT SECURITY CLASSIFICATION 0

Study of the Effects of Drugs upon the Cardiovascular and Respiratory Systems

DTIC Science & Technology

1986-06-01

ed. The C.V. Mosby Company, St . Louis, 1971. Spence, 3.T., Underwood, B.3., Duncan, C.P., and Cotton, J.W. Elementary Statistics. Appleton- Century ...I.I)" ,,,- 20. DISTRIBUTION/AVAILABILITY OF ABSTRACT 21 . ABSTRACT SECURITY CLASSIFICATION C3 UNCLASSIFIED/UNLIMITED 0 SAME AS RPT. - OTIC USERS...50, resistance units - -. ° ! U { {{{{{{ {{{{{{{{{{{{{{{ { {{{{ I {{{ {{{{ { {{{{{{ {{{{{{{ {{{{{ 21 3. Calibration of the Buxco Data Logger Model DL

Atropine’s Effects upon the Heart and Its Systemic Output,

DTIC Science & Technology

1986-01-01

CLASSIFICATION AUTHORITY 3 DISTRIBUTION/AVAILABILITY OF REPORT 2b. DECLASSIFICATION /DOWNGRADING SCHEDULE Unlimited 4. PERFORMING ORGANIZATION REPORT...NUMBER(S) S. MONITORING ORGANIZATION REPORT NUMBER(S) WRAIR ET-86-1 6a. NAME OF PERFORMING ORGANIZATION 6b OFFICE SYMBOL 7a NAME OF MONITORING...review of atropine’s effects upon sweat production abatement and the related consequences to exercise performance in humans, horses and dogs appears

Next-Generation Botnet Detection and Response

DTIC Science & Technology

2008-06-24

REPORT Final Report of "Next-Generation Botnet Detection and Response" 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: In this project, we developed...and Wenke Lee. ?In Proceedings of The 13th Annual Network and Distributed System Security Symposium (NDSS 2006), San Diego, CA, February 2006. 2...In Proceedings of The 16th USENIX Security Symposium ( Security 󈧋), Boston, MA, August 2007. 3. A Taxonomy of Botnet Structures. ?David Dagon, Guofei

Session Initiation Protocol Network Encryption Device Plain Text Domain Discovery Service

DTIC Science & Technology

2007-12-07

MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a...such as the TACLANE, have developed unique discovery methods to establish Plain Text Domain (PTD) Security Associations (SA). All of these techniques...can include network and host Internet Protocol (IP) addresses, Information System Security Office (ISSO) point of contact information and PTD status

Algorithms and Results of Eye Tissues Differentiation Based on RF Ultrasound

PubMed Central

Jurkonis, R.; Janušauskas, A.; Marozas, V.; Jegelevičius, D.; Daukantas, S.; Patašius, M.; Paunksnis, A.; Lukoševičius, A.

2012-01-01

Algorithms and software were developed for analysis of B-scan ultrasonic signals acquired from commercial diagnostic ultrasound system. The algorithms process raw ultrasonic signals in backscattered spectrum domain, which is obtained using two time-frequency methods: short-time Fourier and Hilbert-Huang transformations. The signals from selected regions of eye tissues are characterized by parameters: B-scan envelope amplitude, approximated spectral slope, approximated spectral intercept, mean instantaneous frequency, mean instantaneous bandwidth, and parameters of Nakagami distribution characterizing Hilbert-Huang transformation output. The backscattered ultrasound signal parameters characterizing intraocular and orbit tissues were processed by decision tree data mining algorithm. The pilot trial proved that applied methods are able to correctly classify signals from corpus vitreum blood, extraocular muscle, and orbit tissues. In 26 cases of ocular tissues classification, one error occurred, when tissues were classified into classes of corpus vitreum blood, extraocular muscle, and orbit tissue. In this pilot classification parameters of spectral intercept and Nakagami parameter for instantaneous frequencies distribution of the 1st intrinsic mode function were found specific for corpus vitreum blood, orbit and extraocular muscle tissues. We conclude that ultrasound data should be further collected in clinical database to establish background for decision support system for ocular tissue noninvasive differentiation. PMID:22654643

[The questionnaire survey on glaucoma diagnosis and treatment in China (2016)].

PubMed

Zhang, Q; Cao, K; Kang, M T; Sun, Y X; Gan, J H; Tian, J X; Ran, A R; Zhang, X; Su, Y D; Li, S N

2017-02-11

Objective: To investigate the present situation of diagnosis and treatment for primary angle-closure glaucoma (PACG) and primary open-angle glaucoma (POAG) and awareness of the relevant progress among Chinese ophthalmologists. Methods: This study was a cross-sectional, non-randomized sampling survey. Participants were ophthalmologists who attended the 11st Chinese Glaucoma Society Congress during November 11 to 12, 2016. They were invited to fill out a questionnaire. The questionnaire included participants' basic information and their knowledge about glaucoma diagnosis and treatment. The data collected through questionnaire were analyzed with SAS9.4. Results: A total of 450 questionnaires were distributed and 372 valid questionnaires were retrieved, with a response rate of 82. 7%(372/450). ISGEO classification system was adopted by 58.9% (219/372) of the participants as the diagnostic criteria for PACG. Of the respondents, 48.1% (179/372) of the participants believed that "anterior chamber angle closure mechanism-based PACG classification system" was more instructive for treatment, the percentage was higher than ISGEO classification system (42.2%, 157/372). Most (72.3%, 269/372) of the participants knew the 3-minute dark room prone test, but only 27.7%(103/372) of them applied it in clinical practice. A total of 83.4%(310/372) of the participants believed that low cerebrospinal fluid pressure is a risk factor for POAG. In all, 71.8% (267/372) of the participants reported that their institutes had applied compound trabeculectomy with adjustable suture, with 76.9%(286/372) of the participants agreeing that the adjustable suture reduced the rate of complications after trabeculectomy. Conclusions: Currently, both ISGEO classification system and anterior chamber angle closure mechanism-based PACG classification system were adopted in the diagnosis and treatment of glaucoma. Low cerebrospinal fluid pressure as new risk factors for POAG has been widely acknowledged and given attentions by Chinese ophthalmologists. The 3-minute darkroom prone test and compound trabeculectomy with adjustable suture still need to be promoted. (Chin J Ophthalmol, 2017, 53: 115-120) .

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

Mainzer, A.; Masiero, J.; Bauer, J.

We have combined the NEOWISE and Sloan Digital Sky Survey data to study the albedos of 24,353 asteroids with candidate taxonomic classifications derived using Sloan photometry. We find a wide range of moderate to high albedos for candidate S-type asteroids that are analogous to the S complex defined by previous spectrophotometrically based taxonomic systems. The candidate C-type asteroids, while generally very dark, have a tail of higher albedos that overlaps the S types. The albedo distribution for asteroids with a photometrically derived Q classification is extremely similar to those of the S types. Asteroids with similar colors to (4) Vestamore » have higher albedos than the S types, and most have orbital elements similar to known Vesta family members. Finally, we show that the relative reflectance at 3.4 and 4.6 {mu}m is higher for D-type asteroids and suggest that their red visible and near-infrared spectral slope extends out to these wavelengths. Understanding the relationship between size, albedo, and taxonomic classification is complicated by the fact that the objects with classifications were selected from the visible/near-infrared Sloan Moving Object Catalog, which is biased against fainter asteroids, including those with lower albedos.« less

Phenomenology and classification of dystonia: a consensus update.

PubMed

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.

Texture and color features for tile classification

NASA Astrophysics Data System (ADS)

Baldrich, Ramon; Vanrell, Maria; Villanueva, Juan J.

1999-09-01

In this paper we present the results of a preliminary computer vision system to classify the production of a ceramic tile industry. We focus on the classification of a specific type of tiles whose production can be affected by external factors, such as humidity, temperature, origin of clays and pigments. Variations on these uncontrolled factors provoke small differences in the color and the texture of the tiles that force to classify all the production. A constant and non- subjective classification would allow avoiding devolution from customers and unnecessary stock fragmentation. The aim of this work is to simulate the human behavior on this classification task by extracting a set of features from tile images. These features are induced by definitions from experts. To compute them we need to mix color and texture information and to define global and local measures. In this work, we do not seek a general texture-color representation, we only deal with textures formed by non-oriented colored-blobs randomly distributed. New samples are classified using Discriminant Analysis functions derived from known class tile samples. The last part of the paper is devoted to explain the correction of acquired images in order to avoid time and geometry illumination changes.

Ice Water Classification Using Statistical Distribution Based Conditional Random Fields in RADARSAT-2 Dual Polarization Imagery

NASA Astrophysics Data System (ADS)

Zhang, Y.; Li, F.; Zhang, S.; Hao, W.; Zhu, T.; Yuan, L.; Xiao, F.

2017-09-01

In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.

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

PubMed

Waring, R; Knight, R

2013-01-01

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

Comparison of Rai and Binet Classifications in Chronic Lymphocytic Leukemia.

PubMed

Zengin, N; Kars, A; Kansu, E; Özdemir, O; Barişta, İ; Güllü, İ; Güler, N; Özişik, Y; Dündar, S; Firat, D

1997-01-01

Staging systems are essential for understanding disease, in predicting the outcome, and therapeutic decision making in any tumor as well as chronic lymphocytic leukemia (CLL). In this study, we compared the clinical correlation of the Rai and Binet classification systems in 133 CLL patients. The distribution of 133 patients according to the Rai system was as follows, stage 0:17, I:13, II:45, III:30, IV:28, and in the Binet system stage A:35, B:40, C:58 patients. Median survival of patients according to the Rai staging system was >67.0, >91.0, 63.8, 20.9 and 9.8 months, and >91.0, 63.4, 16.0 months according to Binet, respectively. Although no difference was found between Rai stages 0, I, II (p > 0.05) in terms of median survival, the difference between these stages and stages III and IV was statistically significant (p < 0.05). In the Binet staging system statistically significant survival difference was found between all stages (p < 0.05). We concluded that although both systems are comparable in terms of staging and predicting the outcome of patients with CLL, the Rai staging system appears to have an advantage over the Binet system by defining a subset of patients with excellent prognosis (stage 0) which is included within stage A of the latter.

GPCALMA: A Tool For Mammography With A GRID-Connected Distributed Database

NASA Astrophysics Data System (ADS)

Bottigli, U.; Cerello, P.; Cheran, S.; Delogu, P.; Fantacci, M. E.; Fauci, F.; Golosio, B.; Lauria, A.; Lopez Torres, E.; Magro, R.; Masala, G. L.; Oliva, P.; Palmiero, R.; Raso, G.; Retico, A.; Stumbo, S.; Tangaro, S.

2003-09-01

The GPCALMA (Grid Platform for Computer Assisted Library for MAmmography) collaboration involves several departments of physics, INFN (National Institute of Nuclear Physics) sections, and italian hospitals. The aim of this collaboration is developing a tool that can help radiologists in early detection of breast cancer. GPCALMA has built a large distributed database of digitised mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) software which is integrated in a station that can also be used to acquire new images, as archive and to perform statistical analysis. The images (18×24 cm2, digitised by a CCD linear scanner with a 85 μm pitch and 4096 gray levels) are completely described: pathological ones have a consistent characterization with radiologist's diagnosis and histological data, non pathological ones correspond to patients with a follow up at least three years. The distributed database is realized throught the connection of all the hospitals and research centers in GRID tecnology. In each hospital local patients digital images are stored in the local database. Using GRID connection, GPCALMA will allow each node to work on distributed database data as well as local database data. Using its database the GPCALMA tools perform several analysis. A texture analysis, i.e. an automated classification on adipose, dense or glandular texture, can be provided by the system. GPCALMA software also allows classification of pathological features, in particular massive lesions (both opacities and spiculated lesions) analysis and microcalcification clusters analysis. The detection of pathological features is made using neural network software that provides a selection of areas showing a given "suspicion level" of lesion occurrence. The performance of the GPCALMA system will be presented in terms of the ROC (Receiver Operating Characteristic) curves. The results of GPCALMA system as "second reader" will also be presented.

Future production of hydrogen from solar energy and water - A summary and assessment of U.S. developments

NASA Technical Reports Server (NTRS)

Hanson, J. A.; Escher, W. J. D.

1979-01-01

The paper examines technologies of hydrogen production. Its delivery, distribution, and end-use systems are reviewed, and a classification of solar energy and hydrogen production methods is suggested. The operation of photoelectric processes, biophotolysis, photocatalysis, photoelectrolysis, and of photovoltaic systems are reviewed, with comments on their possible hydrogen production potential. It is concluded that solar hydrogen derived from wind energy, photovoltaic technology, solar thermal electric technology, and hydropower could supply some of the hydrogen for air transport by the middle of the next century.

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

Code of Federal Regulations, 2011 CFR

2011-01-01

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

Logistics Composite Model (LCOM) Workbook

DTIC Science & Technology

1976-06-01

nc;-J to e UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (When Dots Ew.ervol. REPORT DOCUMENTATION PAGE READ INSTRUCTIONS BEFORE COMPLETING FORM I...Controlling Office) 15. SECURITY CLASS. (of this report) Unclassified 158. DECLASSIFICATIONDOWNGRADING SCHEDULE 16. DISTRIBUTION STATEMENT (of this Report...ID SECURITY CLASSIFICATION OF THIS PAGE (When Des Entered) K7 UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE(Whon Dal Entore o l Logic networks

The Blurred Line between Form and Process: A Comparison of Stream Channel Classification Frameworks

PubMed Central

Kasprak, Alan; Hough-Snee, Nate

2016-01-01

Stream classification provides a means to understand the diversity and distribution of channels and floodplains that occur across a landscape while identifying links between geomorphic form and process. Accordingly, stream classification is frequently employed as a watershed planning, management, and restoration tool. At the same time, there has been intense debate and criticism of particular frameworks, on the grounds that these frameworks classify stream reaches based largely on their physical form, rather than direct measurements of their component hydrogeomorphic processes. Despite this debate surrounding stream classifications, and their ongoing use in watershed management, direct comparisons of channel classification frameworks are rare. Here we implement four stream classification frameworks and explore the degree to which each make inferences about hydrogeomorphic process from channel form within the Middle Fork John Day Basin, a watershed of high conservation interest within the Columbia River Basin, U.S.A. We compare the results of the River Styles Framework, Natural Channel Classification, Rosgen Classification System, and a channel form-based statistical classification at 33 field-monitored sites. We found that the four frameworks consistently classified reach types into similar groups based on each reach or segment’s dominant hydrogeomorphic elements. Where classified channel types diverged, differences could be attributed to the (a) spatial scale of input data used, (b) the requisite metrics and their order in completing a framework’s decision tree and/or, (c) whether the framework attempts to classify current or historic channel form. Divergence in framework agreement was also observed at reaches where channel planform was decoupled from valley setting. Overall, the relative agreement between frameworks indicates that criticism of individual classifications for their use of form in grouping stream channels may be overstated. These form-based criticisms may also ignore the geomorphic tenet that channel form reflects formative hydrogeomorphic processes across a given landscape. PMID:26982076

Object-Based Classification and Change Detection of Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Park, J. G.; Harada, I.; Kwak, Y.

2016-06-01

Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

Impervious surface mapping with Quickbird imagery

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio

2010-01-01

This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance. PMID:21643434

Classification of Acousto-Optic Correlation Signatures of Spread Spectrum Signals Using Artificial Neural Networks

DTIC Science & Technology

1989-12-01

Ohio ’aPw iorlipuab muo i 0I2, AFIT/GE/ENG/89D-10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION SIGNATURES OF SPREAD SPECTRUM SIGNALS USING ARTIFICIAL...ENG/89D- 10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION SIGNATURES OF SPREAD SPECTRUM SIGNALS USING ARTIFICIAL NEURAL NETWORKS THESIS John W. DeBerry...Captain, USAF AFIT/GE/ENG/89D- 10 Approved for public release; distribution unlimited. AFIT/GE/ENG/89D-10 CLASSIFICATION OF ACOUSTO - OPTIC CORRELATION

J-Plus: Morphological Classification Of Compact And Extended Sources By Pdf Analysis

NASA Astrophysics Data System (ADS)

López-Sanjuan, C.; Vázquez-Ramió, H.; Varela, J.; Spinoso, D.; Cristóbal-Hornillos, D.; Viironen, K.; Muniesa, D.; J-PLUS Collaboration

2017-10-01

We present a morphological classification of J-PLUS EDR sources into compact (i.e. stars) and extended (i.e. galaxies). Such classification is based on the Bayesian modelling of the concentration distribution, including observational errors and magnitude + sky position priors. We provide the star / galaxy probability of each source computed from the gri images. The comparison with the SDSS number counts support our classification up to r 21. The 31.7 deg² analised comprises 150k stars and 101k galaxies.

Pedestrian recognition using automotive radar sensors

NASA Astrophysics Data System (ADS)

Bartsch, A.; Fitzek, F.; Rasshofer, R. H.

2012-09-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

Modality-Driven Classification and Visualization of Ensemble Variance

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

Bensema, Kevin; Gosink, Luke; Obermaier, Harald

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no informationmore » about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.« less

Hierarchy concepts: classification and preparation strategies for zeolite containing materials with hierarchical porosity.

PubMed

Schwieger, Wilhelm; Machoke, Albert Gonche; Weissenberger, Tobias; Inayat, Amer; Selvam, Thangaraj; Klumpp, Michael; Inayat, Alexandra

2016-06-13

'Hierarchy' is a property which can be attributed to a manifold of different immaterial systems, such as ideas, items and organisations or material ones like biological systems within living organisms or artificial, man-made constructions. The property 'hierarchy' is mainly characterised by a certain ordering of individual elements relative to each other, often in combination with a certain degree of branching. Especially mass-flow related systems in the natural environment feature special hierarchically branched patterns. This review is a survey into the world of hierarchical systems with special focus on hierarchically porous zeolite materials. A classification of hierarchical porosity is proposed based on the flow distribution pattern within the respective pore systems. In addition, this review might serve as a toolbox providing several synthetic and post-synthetic strategies to prepare zeolitic or zeolite containing material with tailored hierarchical porosity. Very often, such strategies with their underlying principles were developed for improving the performance of the final materials in different technical applications like adsorptive or catalytic processes. In the present review, besides on the hierarchically porous all-zeolite material, special focus is laid on the preparation of zeolitic composite materials with hierarchical porosity capable to face the demands of industrial application.

A Hybrid Semi-supervised Classification Scheme for Mining Multisource Geospatial Data

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

Vatsavai, Raju; Bhaduri, Budhendra L

2011-01-01

Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of large number of accurate training samples (10 to 30 |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, itmore » is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately there is no convenient multivariate statistical model that can be employed for mulitsource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on real datasets, and our new hybrid approach shows over 25 to 35% improvement in overall classification accuracy over conventional classification schemes.« less

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

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

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

A new precipitation and meteorological drought climatology based on weather patterns

NASA Astrophysics Data System (ADS)

Richardson, D.; Fowler, H. J.; Kilsby, C. G.; Neal, R.

2017-12-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterise the broad-scale atmospheric circulation over a given region. An analysis of regional UK precipitation and meteorological drought climatology with respect to a set of objectively defined weather patterns is presented. This classification system, introduced last year, is currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. The classification consists of 30 daily patterns derived from North Atlantic Ocean and European mean sea level pressure data. Clustering these 30 patterns yields another set of eight patterns that are intended for use in longer-range applications. Weather pattern definitions and daily occurrences are mapped to the commonly-used Lamb Weather Types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Drought index series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for different drought index thresholds, representing dry, wet and drought conditions. The set of 30 weather patterns is shown to be adequate for precipitation-based analyses in the UK, although the smaller set of clustered patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in the context of precipitation studies. Weather patterns associated with drought over the different UK regions are identified. This has potential forecasting application - if a model (e.g. a global seasonal forecast model) can predict weather pattern occurrences then regional drought outlooks may be derived from the forecasted weather patterns.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE PAGES

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; ...

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

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

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Approximation in Optimal Control and Identification of Large Space Structures.

DTIC Science & Technology

1985-01-01

I ease I Cr ’. ’. -4 . r*_...1- UN(D aSIFIED SECURITY CLAS.’ICATION OF fHIS P^.GE REPORT DOCUMENTATION PAGE 1 REPORT SECURITY CLASSIFICATION 1...RESTRICTIVE MARKINGS UNCLASSIFIED 2 SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION/AVAILABILITY OF REPORT Approved for public release; distribution 2b...NOS. PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. NO Bolling AFB DC 20332-6448 61102F 2304 Al 11. TITLE IlnRCiude Security Claas.ifcation

A Framework for Inferring Taxonomic Class of Asteroids.

NASA Technical Reports Server (NTRS)

Dotson, J. L.; Mathias, D. L.

2017-01-01

Introduction: Taxonomic classification of asteroids based on their visible / near-infrared spectra or multi band photometry has proven to be a useful tool to infer other properties about asteroids. Meteorite analogs have been identified for several taxonomic classes, permitting detailed inference about asteroid composition. Trends have been identified between taxonomy and measured asteroid density. Thanks to NEOWise (Near-Earth-Object Wide-field Infrared Survey Explorer) and Spitzer (Spitzer Space Telescope), approximately twice as many asteroids have measured albedos than the number with taxonomic classifications. (If one only considers spectroscopically determined classifications, the ratio is greater than 40.) We present a Bayesian framework that provides probabilistic estimates of the taxonomic class of an asteroid based on its albedo. Although probabilistic estimates of taxonomic classes are not a replacement for spectroscopic or photometric determinations, they can be a useful tool for identifying objects for further study or for asteroid threat assessment models. Inputs and Framework: The framework relies upon two inputs: the expected fraction of each taxonomic class in the population and the albedo distribution of each class. Luckily, numerous authors have addressed both of these questions. For example, the taxonomic distribution by number, surface area and mass of the main belt has been estimated and a diameter limited estimate of fractional abundances of the near earth asteroid population was made. Similarly, the albedo distributions for taxonomic classes have been estimated for the combined main belt and NEA (Near Earth Asteroid) populations in different taxonomic systems and for the NEA population specifically. The framework utilizes a Bayesian inference appropriate for categorical data. The population fractions provide the prior while the albedo distributions allow calculation of the likelihood an albedo measurement is consistent with a given taxonomic class. These inputs allows calculation of the probability an asteroid with a specified albedo belongs to any given taxonomic class.

The PLATINO study: description of the distribution, stability, and mortality according to the Global Initiative for Chronic Obstructive Lung Disease classification from 2007 to 2017.

PubMed

Menezes, Ana M; Wehrmeister, Fernando C; Perez-Padilla, Rogelio; Viana, Karynna P; Soares, Claudia; Müllerova, Hana; Valdivia, Gonzalo; Jardim, José R; Montes de Oca, Maria

2017-01-01

The Global Initiative for Chronic Obstructive Lung Disease (GOLD) report provides a framework for classifying COPD reflecting the impacts of disease on patients and for targeting treatment recommendations. The GOLD 2017 introduced a new classification with 16 subgroups based on a composite of spirometry and symptoms/exacerbations. Data from the population-based PLATINO study, collected at baseline and at follow-up, in three sites in Latin America were analyzed to compare the following: 1) the distribution of COPD patients according to GOLD 2007, 2013, and 2017; 2) the stability of the 2007 and 2013 classifications; and 3) the mortality rate over time stratified by GOLD 2007, 2013, and 2017. Of the 524 COPD patients evaluated, most of them were classified as Grade I or II (GOLD 2007) and Group A or B (GOLD 2013), with ≈70% of those classified as Group A in GOLD 2013 also classified as Grade I in GOLD 2007 and the highest percentage (41%) in Group D (2013) classified as Grade III (2007). According to GOLD 2017, among patients with Grade I airflow limitation, 69% of them were categorized into Group A, whereas Grade IV patients were more evenly distributed among Groups A-D. Most of the patients classified by GOLD 2007 remained in the same airflow limitation group at the follow-up; a greater temporal variability was observed with GOLD 2013 classification. Incidence-mortality rate in patients classified by GOLD 2007 was positively associated with increasing severity of airflow obstruction; for GOLD 2013 and GOLD 2017 (Groups A-D), highest mortality rates were observed in Groups C and D. No clear pattern was observed for mortality across the GOLD 2017 subgroups. The PLATINO study data suggest that GOLD 2007 classification shows more stability over time compared with GOLD 2013. No clear patterns with respect to the distribution of patients or incidence-mortality rates were observed according to GOLD 2013/2017 classification.

Considering the Spatial Layout Information of Bag of Features (BoF) Framework for Image Classification.

PubMed

Mu, Guangyu; Liu, Ying; Wang, Limin

2015-01-01

The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.

Autonomous Non-Linear Classification of LPI Radar Signal Modulations

DTIC Science & Technology

2007-09-01

Wigner - Ville distribution ( WVD ), the Choi-Williams distribution (CWD) and a Quadrature...accomplished using the images from the Wigner - Ville distribution and the Choi-Williams distribution for polyphase modulations. For the WVD images, radon...this work. Four detection techniques including the Wigner - Ville distribution ( WVD ), the Choi-Williams distribution (CWD), Quadrature Mirror

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

PubMed

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

2015-12-01

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

Contextual convolutional neural networks for lung nodule classification using Gaussian-weighted average image patches

NASA Astrophysics Data System (ADS)

Lee, Haeil; Lee, Hansang; Park, Minseok; Kim, Junmo

2017-03-01

Lung cancer is the most common cause of cancer-related death. To diagnose lung cancers in early stages, numerous studies and approaches have been developed for cancer screening with computed tomography (CT) imaging. In recent years, convolutional neural networks (CNN) have become one of the most common and reliable techniques in computer aided detection (CADe) and diagnosis (CADx) by achieving state-of-the-art-level performances for various tasks. In this study, we propose a CNN classification system for false positive reduction of initially detected lung nodule candidates. First, image patches of lung nodule candidates are extracted from CT scans to train a CNN classifier. To reflect the volumetric contextual information of lung nodules to 2D image patch, we propose a weighted average image patch (WAIP) generation by averaging multiple slice images of lung nodule candidates. Moreover, to emphasize central slices of lung nodules, slice images are locally weighted according to Gaussian distribution and averaged to generate the 2D WAIP. With these extracted patches, 2D CNN is trained to achieve the classification of WAIPs of lung nodule candidates into positive and negative labels. We used LUNA 2016 public challenge database to validate the performance of our approach for false positive reduction in lung CT nodule classification. Experiments show our approach improves the classification accuracy of lung nodules compared to the baseline 2D CNN with patches from single slice image.

Opto-EM and Devices Investigation

DTIC Science & Technology

1989-06-01

value of bandwidth is used the signal to noise ratio of the UAM system becomes ( SNP )u z exp ’cr. 2P,\\ 3 .V N._ W/ 3.3 GAUSSIAN SHAPED MESSAGE SPECTRA...Unclassified N/A 2a. SECURITY CLASSIFICATION AUTHORITY 3 . DISTRIBUTION/AVAILABILITY OF REPORT N/A Approved for public release; 2b. DECLASSIFICATION...Synthesis, Single Crystal Growth, Purification and Characterization of Indium Phosphide 2. Deposition of Select Silicides Under High Vacuum Conditions 3 . Use

Application of the Recreation Opportunity Spectrum for Outdoor Recreation Planning on Army Installations.

DTIC Science & Technology

1982-03-01

to preference types, and uses capacity estimation; therefore, it is basically a good system for recreation and resource inventory and classification...quan- tity, and distribution of recreational resources. Its basic unit of inventory is landform, or the homogeneity of physical features used to...by Clark and Stankey, "the basic assumption underlying the ROS is that quality recreational experiences are best assured by providing a diverse set of

Webcam classification using simple features

NASA Astrophysics Data System (ADS)

Pramoun, Thitiporn; Choe, Jeehyun; Li, He; Chen, Qingshuang; Amornraksa, Thumrongrat; Lu, Yung-Hsiang; Delp, Edward J.

2015-03-01

Thousands of sensors are connected to the Internet and many of these sensors are cameras. The "Internet of Things" will contain many "things" that are image sensors. This vast network of distributed cameras (i.e. web cams) will continue to exponentially grow. In this paper we examine simple methods to classify an image from a web cam as "indoor/outdoor" and having "people/no people" based on simple features. We use four types of image features to classify an image as indoor/outdoor: color, edge, line, and text. To classify an image as having people/no people we use HOG and texture features. The features are weighted based on their significance and combined. A support vector machine is used for classification. Our system with feature weighting and feature combination yields 95.5% accuracy.

Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

PubMed

Siuly; Li, Yan; Paul Wen, Peng

2014-03-01

Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

Video sensor architecture for surveillance applications.

PubMed

Sánchez, Jordi; Benet, Ginés; Simó, José E

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

Video Sensor Architecture for Surveillance Applications

PubMed Central

Sánchez, Jordi; Benet, Ginés; Simó, José E.

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%. PMID:22438723

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

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

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

Inter-Relationships of Functional Status in Cerebral Palsy: Analyzing Gross Motor Function, Manual Ability, and Communication Function Classification Systems in Children

ERIC Educational Resources Information Center

Hidecker, Mary Jo Cooley; Ho, Nhan Thi; Dodge, Nancy; Hurvitz, Edward A.; Slaughter, Jaime; Workinger, Marilyn Seif; Kent, Ray D.; Rosenbaum, Peter; Lenski, Madeleine; Messaros, Bridget M.; Vanderbeek, Suzette B.; Deroos, Steven; Paneth, Nigel

2012-01-01

Aim: To investigate the relationships among the Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) in children with cerebral palsy (CP). Method: Using questionnaires describing each scale, mothers reported GMFCS, MACS, and CFCS levels in 222…

Web-Enabled Distributed Health-Care Framework for Automated Malaria Parasite Classification: an E-Health Approach.

PubMed

Maity, Maitreya; Dhane, Dhiraj; Mungle, Tushar; Maiti, A K; Chakraborty, Chandan

2017-10-26

Web-enabled e-healthcare system or computer assisted disease diagnosis has a potential to improve the quality and service of conventional healthcare delivery approach. The article describes the design and development of a web-based distributed healthcare management system for medical information and quantitative evaluation of microscopic images using machine learning approach for malaria. In the proposed study, all the health-care centres are connected in a distributed computer network. Each peripheral centre manages its' own health-care service independently and communicates with the central server for remote assistance. The proposed methodology for automated evaluation of parasites includes pre-processing of blood smear microscopic images followed by erythrocytes segmentation. To differentiate between different parasites; a total of 138 quantitative features characterising colour, morphology, and texture are extracted from segmented erythrocytes. An integrated pattern classification framework is designed where four feature selection methods viz. Correlation-based Feature Selection (CFS), Chi-square, Information Gain, and RELIEF are employed with three different classifiers i.e. Naive Bayes', C4.5, and Instance-Based Learning (IB1) individually. Optimal features subset with the best classifier is selected for achieving maximum diagnostic precision. It is seen that the proposed method achieved with 99.2% sensitivity and 99.6% specificity by combining CFS and C4.5 in comparison with other methods. Moreover, the web-based tool is entirely designed using open standards like Java for a web application, ImageJ for image processing, and WEKA for data mining considering its feasibility in rural places with minimal health care facilities.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

PubMed

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

2015-07-01

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

Stroke subtyping for genetic association studies? A comparison of the CCS and TOAST classifications.

PubMed

Lanfranconi, Silvia; Markus, Hugh S

2013-12-01

A reliable and reproducible classification system of stroke subtype is essential for epidemiological and genetic studies. The Causative Classification of Stroke system is an evidence-based computerized algorithm with excellent inter-rater reliability. It has been suggested that, compared to the Trial of ORG 10172 in Acute Stroke Treatment classification, it increases the proportion of cases with defined subtype that may increase power in genetic association studies. We compared Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications in a large cohort of well-phenotyped stroke patients. Six hundred ninety consecutively recruited patients with first-ever ischemic stroke were classified, using review of clinical data and original imaging, according to the Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications. There was excellent agreement subtype assigned by between Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system (kappa = 0·85). The agreement was excellent for the major individual subtypes: large artery atherosclerosis kappa = 0·888, small-artery occlusion kappa = 0·869, cardiac embolism kappa = 0·89, and undetermined category kappa = 0·884. There was only moderate agreement (kappa = 0·41) for the subjects with at least two competing underlying mechanism. Thirty-five (5·8%) patients classified as undetermined by Trial of ORG 10172 in Acute Stroke Treatment were assigned to a definite subtype by Causative Classification of Stroke system. Thirty-two subjects assigned to a definite subtype by Trial of ORG 10172 in Acute Stroke Treatment were classified as undetermined by Causative Classification of Stroke system. There is excellent agreement between classification using Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke systems but no evidence that Causative Classification of Stroke system reduced the proportion of patients classified to undetermined subtypes. The excellent inter-rater reproducibility and web-based semiautomated nature make Causative Classification of Stroke system suitable for multicenter studies, but the benefit of reclassifying cases already classified using the Trial of ORG 10172 in Acute Stroke Treatment system on existing databases is likely to be small. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.

Morphometric comparison by the ISAS® CASA-DNAf system of two techniques for the evaluation of DNA fragmentation in human spermatozoa

PubMed Central

Sadeghi, Sara; García-Molina, Almudena; Celma, Ferran; Valverde, Anthony; Fereidounfar, Sogol; Soler, Carles

2016-01-01

DNA fragmentation has been shown to be one of the causes of male infertility, particularly related to repeated abortions, and different methods have been developed to analyze it. In the present study, two commercial kits based on the SCD technique (Halosperm® and SDFA) were evaluated by the use of the DNA fragmentation module of the ISAS® v1 CASA system. Seven semen samples from volunteers were analyzed. To compare the results between techniques, the Kruskal–Wallis test was used. Data were used for calculation of Principal Components (two PCs were obtained), and subsequent subpopulations were identified using the Halo, Halo/Core Ratio, and PC data. Results from both kits were significantly different (P < 0.001). In each case, four subpopulations were obtained, independently of the classification method used. The distribution of subpopulations differed depending on the kit used. From the PC data, a discriminant analysis matrix was obtained and a good a posteriori classification was obtained (97.1% for Halosperm and 96.6% for SDFA). The present results are the first approach on morphometric evaluation of DNA fragmentation from the SCD technique. This approach could be used for the future definition of a classification matrix surpassing the current subjective evaluation of this important sperm factor. PMID:27678463

Morphometric comparison by the ISAS® CASA-DNAf system of two techniques for the evaluation of DNA fragmentation in human spermatozoa.

PubMed

Sadeghi, Sara; García-Molina, Almudena; Celma, Ferran; Valverde, Anthony; Fereidounfar, Sogol; Soler, Carles

2016-01-01

DNA fragmentation has been shown to be one of the causes of male infertility, particularly related to repeated abortions, and different methods have been developed to analyze it. In the present study, two commercial kits based on the SCD technique (Halosperm ® and SDFA) were evaluated by the use of the DNA fragmentation module of the ISAS ® v1 CASA system. Seven semen samples from volunteers were analyzed. To compare the results between techniques, the Kruskal-Wallis test was used. Data were used for calculation of Principal Components (two PCs were obtained), and subsequent subpopulations were identified using the Halo, Halo/Core Ratio, and PC data. Results from both kits were significantly different (P < 0.001). In each case, four subpopulations were obtained, independently of the classification method used. The distribution of subpopulations differed depending on the kit used. From the PC data, a discriminant analysis matrix was obtained and a good a posteriori classification was obtained (97.1% for Halosperm and 96.6% for SDFA). The present results are the first approach on morphometric evaluation of DNA fragmentation from the SCD technique. This approach could be used for the future definition of a classification matrix surpassing the current subjective evaluation of this important sperm factor.

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

NASA Technical Reports Server (NTRS)

Slater, P. N. (Principal Investigator)

1980-01-01

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

Impact of using the new GOLD classification on the distribution of COPD severity in clinical practice.

PubMed

Hernández, Marcos; García, Gabriel; Falco, Jimena; García, Agustín R; Martín, Vanina; Ibarrola, Manuel; Quadrelli, Silvia

2018-01-01

The objective of this study was to examine how COPD patients were classified by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometry-based severity system and the distribution of COPD severity using the new GOLD 2011 assessment framework. This was an observational, retrospective cohort study conducted in a single tertiary center on a prospective database, which aimed to evaluate the prevalence, incidence, severity, and comorbidities of COPD. Inclusion criteria were age ≥40 years and COPD diagnosis according to GOLD 2007 classification. Clinical factors were compared between the categories in GOLD 2007 and 2011 groups by using the χ 2 test for categorical data and the analysis of variance for continuous data. In total, 420 COPD patients were included in the analysis. The distribution of patients into GOLD 2007 categories was as follows: 6.4% (n=27) of them were classified into subgroup I, 42.1% (n=177) into subgroup II, 37.9% (n=159) into subgroup III, and 13.6% (n=57) into subgroup IV. The distribution of patients into GOLD 2011 categories was as follows: 16.4% (n=69) of them were classified into subgroup A (low risk and fewer symptoms), 32.1% (n=135) into subgroup B (low risk and more symptoms), 21.6% (n=91) into subgroup C (high risk and fewer symptoms), and 29.7% (n=125) into subgroup D (high risk and more symptoms). After the application of the new GOLD 2011 (modified Medical Research Council [mMRC] system), 22% (n=94) of patients were upgraded to a higher level than their spirometry level, and 16.2% (n=68) of them were downgraded in their severity category, meaning that almost 40% of patients changed their severity assessment category. In total, 22% of patients in stage I were allocated to group B, and 35% of patients in stage IV were allocated to group C. Patients in stage III were the most frequently upgraded to a higher risk group (D), taking into account mMRC and exacerbation history. Classifying patients using the new GOLD 2011 criteria reallocated a relevant proportion of patients to a different risk category and identified larger proportions of patients in the mildest and more severe groups compared with GOLD 2007 classification.

A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals

PubMed Central

2014-01-01

Background The inter-patient classification schema and the Association for the Advancement of Medical Instrumentation (AAMI) standards are important to the construction and evaluation of automated heartbeat classification systems. The majority of previously proposed methods that take the above two aspects into consideration use the same features and classification method to classify different classes of heartbeats. The performance of the classification system is often unsatisfactory with respect to the ventricular ectopic beat (VEB) and supraventricular ectopic beat (SVEB). Methods Based on the different characteristics of VEB and SVEB, a novel hierarchical heartbeat classification system was constructed. This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods. First, random projection and support vector machine (SVM) ensemble were used to detect VEB. Then, the ratio of the RR interval was compared to a predetermined threshold to detect SVEB. The optimal parameters for the classification models were selected on the training set and used in the independent testing set to assess the final performance of the classification system. Meanwhile, the effect of different lead configurations on the classification results was evaluated. Results Results showed that the performance of this classification system was notably superior to that of other methods. The VEB detection sensitivity was 93.9% with a positive predictive value of 90.9%, and the SVEB detection sensitivity was 91.1% with a positive predictive value of 42.2%. In addition, this classification process was relatively fast. Conclusions A hierarchical heartbeat classification system was proposed based on the inter-patient data division to detect VEB and SVEB. It demonstrated better classification performance than existing methods. It can be regarded as a promising system for detecting VEB and SVEB of unknown patients in clinical practice. PMID:24981916

Modeling of air pollutant removal by dry deposition to urban trees using a WRF/CMAQ/i-Tree Eco coupled system.

PubMed

Cabaraban, Maria Theresa I; Kroll, Charles N; Hirabayashi, Satoshi; Nowak, David J

2013-05-01

A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature and LAI fields, and CMAQ provided NO2 concentrations. A base case simulation was conducted using built-in distributed i-Tree Eco tools, and simulations using different inputs were compared against this base case. Differences in land cover classification and tree cover between the distributed i-Tree Eco and WRF resulted in changes in estimated LAI, which in turn resulted in variations in simulated NO2 dry deposition. Estimated NO2 removal decreased when CMAQ-derived concentration was applied to the distributed i-Tree Eco simulation. Discrepancies in temperature inputs did little to affect estimates of NO2 removal by dry deposition to trees in Baltimore. Copyright © 2013 Elsevier Ltd. All rights reserved.

Extensions to the Speech Disorders Classification System (SDCS)

ERIC Educational Resources Information Center

Shriberg, Lawrence D.; Fourakis, Marios; Hall, Sheryl D.; Karlsson, Heather B.; Lohmeier, Heather L.; McSweeny, Jane L.; Potter, Nancy L.; Scheer-Cohen, Alison R.; Strand, Edythe A.; Tilkens, Christie M.; Wilson, David L.

2010-01-01

This report describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). Part I describes a classification extension to the SDCS to differentiate motor speech disorders from speech delay and to differentiate among three sub-types of motor speech disorders.…

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed

O'Neill, M A; Hilgetag, C C

2001-08-29

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement.

The portable UNIX programming system (PUPS) and CANTOR: a computational environment for dynamical representation and analysis of complex neurobiological data.

PubMed Central

O'Neill, M A; Hilgetag, C C

2001-01-01

Many problems in analytical biology, such as the classification of organisms, the modelling of macromolecules, or the structural analysis of metabolic or neural networks, involve complex relational data. Here, we describe a software environment, the portable UNIX programming system (PUPS), which has been developed to allow efficient computational representation and analysis of such data. The system can also be used as a general development tool for database and classification applications. As the complexity of analytical biology problems may lead to computation times of several days or weeks even on powerful computer hardware, the PUPS environment gives support for persistent computations by providing mechanisms for dynamic interaction and homeostatic protection of processes. Biological objects and their interrelations are also represented in a homeostatic way in PUPS. Object relationships are maintained and updated by the objects themselves, thus providing a flexible, scalable and current data representation. Based on the PUPS environment, we have developed an optimization package, CANTOR, which can be applied to a wide range of relational data and which has been employed in different analyses of neuroanatomical connectivity. The CANTOR package makes use of the PUPS system features by modifying candidate arrangements of objects within the system's database. This restructuring is carried out via optimization algorithms that are based on user-defined cost functions, thus providing flexible and powerful tools for the structural analysis of the database content. The use of stochastic optimization also enables the CANTOR system to deal effectively with incomplete and inconsistent data. Prototypical forms of PUPS and CANTOR have been coded and used successfully in the analysis of anatomical and functional mammalian brain connectivity, involving complex and inconsistent experimental data. In addition, PUPS has been used for solving multivariate engineering optimization problems and to implement the digital identification system (DAISY), a system for the automated classification of biological objects. PUPS is implemented in ANSI-C under the POSIX.1 standard and is to a great extent architecture- and operating-system independent. The software is supported by systems libraries that allow multi-threading (the concurrent processing of several database operations), as well as the distribution of the dynamic data objects and library operations over clusters of computers. These attributes make the system easily scalable, and in principle allow the representation and analysis of arbitrarily large sets of relational data. PUPS and CANTOR are freely distributed (http://www.pups.org.uk) as open-source software under the GNU license agreement. PMID:11545702

Exploring diversity in ensemble classification: Applications in large area land cover mapping

NASA Astrophysics Data System (ADS)

Mellor, Andrew; Boukir, Samia

2017-07-01

Ensemble classifiers, such as random forests, are now commonly applied in the field of remote sensing, and have been shown to perform better than single classifier systems, resulting in reduced generalisation error. Diversity across the members of ensemble classifiers is known to have a strong influence on classification performance - whereby classifier errors are uncorrelated and more uniformly distributed across ensemble members. The relationship between ensemble diversity and classification performance has not yet been fully explored in the fields of information science and machine learning and has never been examined in the field of remote sensing. This study is a novel exploration of ensemble diversity and its link to classification performance, applied to a multi-class canopy cover classification problem using random forests and multisource remote sensing and ancillary GIS data, across seven million hectares of diverse dry-sclerophyll dominated public forests in Victoria Australia. A particular emphasis is placed on analysing the relationship between ensemble diversity and ensemble margin - two key concepts in ensemble learning. The main novelty of our work is on boosting diversity by emphasizing the contribution of lower margin instances used in the learning process. Exploring the influence of tree pruning on diversity is also a new empirical analysis that contributes to a better understanding of ensemble performance. Results reveal insights into the trade-off between ensemble classification accuracy and diversity, and through the ensemble margin, demonstrate how inducing diversity by targeting lower margin training samples is a means of achieving better classifier performance for more difficult or rarer classes and reducing information redundancy in classification problems. Our findings inform strategies for collecting training data and designing and parameterising ensemble classifiers, such as random forests. This is particularly important in large area remote sensing applications, for which training data is costly and resource intensive to collect.

Is the maturity of hospitals' quality improvement systems associated with measures of quality and patient safety?

PubMed Central

2011-01-01

Background Previous research addressed the development of a classification scheme for quality improvement systems in European hospitals. In this study we explore associations between the 'maturity' of the hospitals' quality improvement system and clinical outcomes. Methods The maturity classification scheme was developed based on survey results from 389 hospitals in eight European countries. We matched the hospitals from the Spanish sample (113 hospitals) with those hospitals participating in a nation-wide, voluntary hospital performance initiative. We then compared sample distributions and explored associations between the 'maturity' of the hospitals' quality improvement system and a range of composite outcomes measures, such as adjusted hospital-wide mortality, -readmission, -complication and -length of stay indices. Statistical analysis includes bivariate correlations for parametrically and non-parametrically distributed data, multiple robust regression models and bootstrapping techniques to obtain confidence-intervals for the correlation and regression estimates. Results Overall, 43 hospitals were included. Compared to the original sample of 113, this sample was characterized by a higher representation of university hospitals. Maturity of the quality improvement system was similar, although the matched sample showed less variability. Analysis of associations between the quality improvement system and hospital-wide outcomes suggests significant correlations for the indicator adjusted hospital complications, borderline significance for adjusted hospital readmissions and non-significance for the adjusted hospital mortality and length of stay indicators. These results are confirmed by the bootstrap estimates of the robust regression model after adjusting for hospital characteristics. Conclusions We assessed associations between hospitals' quality improvement systems and clinical outcomes. From this data it seems that having a more developed quality improvement system is associated with lower rates of adjusted hospital complications. A number of methodological and logistic hurdles remain to link hospital quality improvement systems to outcomes. Further research should aim at identifying the latent dimensions of quality improvement systems that predict quality and safety outcomes. Such research would add pertinent knowledge regarding the implementation of organizational strategies related with quality of care outcomes. PMID:22185479

Comparison of Danish dichotomous and BI-RADS classifications of mammographic density.

PubMed

Hodge, Rebecca; Hellmann, Sophie Sell; von Euler-Chelpin, My; Vejborg, Ilse; Andersen, Zorana Jovanovic

2014-06-01

In the Copenhagen mammography screening program from 1991 to 2001, mammographic density was classified either as fatty or mixed/dense. This dichotomous mammographic density classification system is unique internationally, and has not been validated before. To compare the Danish dichotomous mammographic density classification system from 1991 to 2001 with the density BI-RADS classifications, in an attempt to validate the Danish classification system. The study sample consisted of 120 mammograms taken in Copenhagen in 1991-2001, which tested false positive, and which were in 2012 re-assessed and classified according to the BI-RADS classification system. We calculated inter-rater agreement between the Danish dichotomous mammographic classification as fatty or mixed/dense and the four-level BI-RADS classification by the linear weighted Kappa statistic. Of the 120 women, 32 (26.7%) were classified as having fatty and 88 (73.3%) as mixed/dense mammographic density, according to Danish dichotomous classification. According to BI-RADS density classification, 12 (10.0%) women were classified as having predominantly fatty (BI-RADS code 1), 46 (38.3%) as having scattered fibroglandular (BI-RADS code 2), 57 (47.5%) as having heterogeneously dense (BI-RADS 3), and five (4.2%) as having extremely dense (BI-RADS code 4) mammographic density. The inter-rater variability assessed by weighted kappa statistic showed a substantial agreement (0.75). The dichotomous mammographic density classification system utilized in early years of Copenhagen's mammographic screening program (1991-2001) agreed well with the BI-RADS density classification system.

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

PubMed

Acién, Pedro; Acién, Maribel I

2011-01-01

A correct classification of malformations of the female genital tract is essential to prevent unnecessary and inadequate surgical operations and to compare reproductive results. An ideal classification system should be based on aetiopathogenesis and should suggest the appropriate therapeutic strategy. We conducted a systematic review of relevant articles found in PubMed, Scopus, Scirus and ISI webknowledge, and analysis of historical collections of 'female genital malformations' and 'classifications'. Of 124 full-text articles assessed for eligibility, 64 were included because they contained original general, partial or modified classifications. All the existing classifications were analysed and grouped. The unification of terms and concepts was also analysed. Traditionally, malformations of the female genital tract have been catalogued and classified as Müllerian malformations due to agenesis, lack of fusion, the absence of resorption and lack of posterior development of the Müllerian ducts. The American Fertility Society classification of the late 1980s included seven basic groups of malformations also considering the Müllerian development and the relationship of the malformations to fertility. Other classifications are based on different aspects: functional, defects in vertical fusion, embryological or anatomical (Vagina, Cervix, Uterus, Adnex and Associated Malformation: VCUAM classification). However, an embryological-clinical classification system seems to be the most appropriate. Accepting the need for a new classification system of genitourinary malformations that considers the experience gained from the application of the current classification systems, the aetiopathogenesis and that also suggests the appropriate treatment, we proposed an update of our embryological-clinical classification as a new system with six groups of female genitourinary anomalies.

14 CFR § 1203.303 - Distribution controls.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Distribution controls. § 1203.303 Section... PROGRAM Classification Principles and Considerations § 1203.303 Distribution controls. NASA shall establish controls over the distribution of classified information to ensure that it is dispersed only to...

Detection And Classification Of Web Robots With Honeypots

DTIC Science & Technology

2016-03-01

CLASSIFICATION OF WEB ROBOTS WITH HONEYPOTS by Sean F. McKenna March 2016 Thesis Advisor: Neil Rowe Second Reader: Justin P. Rohrer THIS...Master’s thesis 4. TITLE AND SUBTITLE DETECTION AND CLASSIFICATION OF WEB ROBOTS WITH HONEYPOTS 5. FUNDING NUMBERS 6. AUTHOR(S) Sean F. McKenna 7...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Web robots are automated programs that systematically browse the Web , collecting information. Although

Digitally Controlled ’Programmable’ Active Filters.

DTIC Science & Technology

1985-12-01

Advisor: Sherif Michael Approved for public release; distribution is unlimited. U - ~ .%~ ~ % %’.4 ~ -. 4-. " %’ -. .4. z. . 4, ,4°*-4° -o - ’ SECURITY ...CLASSIFICATION O THI PAGE ff ,’- -""" REPORT DOCUMENTATION PAGE Ia REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS 2a SECURITY CLASSIFICATION...ELEMENT NO. NO NO. ACCESSION NO. S 11 TITLE (Include Security ClassWfication) , DIGITALLY CONTROLLED "PROGRAMMABLE" ACTIVE FILTERS 1 PERSONAL AUTHOR

ELINT Signal Processing Using Choi-Williams Distribution on Reconfigurable Computers for Detection and Classification of LPI Emitters

DTIC Science & Technology

2008-03-01

WVD Wigner - Ville Distribution xiv THIS PAGE INTENTIONALLY LEFT BLANK xv ACKNOWLEDGMENTS Many thanks to David Caliga of SRC Computer for his...11 2. Wigner - Ville Distribution .................................................................11 3. Choi-Williams... Ville Distribution ...................................12 Table 3. C Code Output for Wigner - Ville Distribution

Automated classification of mouse pup isolation syllables: from cluster analysis to an Excel-based "mouse pup syllable classification calculator".

PubMed

Grimsley, Jasmine M S; Gadziola, Marie A; Wenstrup, Jeffrey J

2012-01-01

Mouse pups vocalize at high rates when they are cold or isolated from the nest. The proportions of each syllable type produced carry information about disease state and are being used as behavioral markers for the internal state of animals. Manual classifications of these vocalizations identified 10 syllable types based on their spectro-temporal features. However, manual classification of mouse syllables is time consuming and vulnerable to experimenter bias. This study uses an automated cluster analysis to identify acoustically distinct syllable types produced by CBA/CaJ mouse pups, and then compares the results to prior manual classification methods. The cluster analysis identified two syllable types, based on their frequency bands, that have continuous frequency-time structure, and two syllable types featuring abrupt frequency transitions. Although cluster analysis computed fewer syllable types than manual classification, the clusters represented well the probability distributions of the acoustic features within syllables. These probability distributions indicate that some of the manually classified syllable types are not statistically distinct. The characteristics of the four classified clusters were used to generate a Microsoft Excel-based mouse syllable classifier that rapidly categorizes syllables, with over a 90% match, into the syllable types determined by cluster analysis.

Application of Neural Networks for classification of Patau, Edwards, Down, Turner and Klinefelter Syndrome based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics.

PubMed

Catic, Aida; Gurbeta, Lejla; Kurtovic-Kozaric, Amina; Mehmedbasic, Senad; Badnjevic, Almir

2018-02-13

The usage of Artificial Neural Networks (ANNs) for genome-enabled classifications and establishing genome-phenotype correlations have been investigated more extensively over the past few years. The reason for this is that ANNs are good approximates of complex functions, so classification can be performed without the need for explicitly defined input-output model. This engineering tool can be applied for optimization of existing methods for disease/syndrome classification. Cytogenetic and molecular analyses are the most frequent tests used in prenatal diagnostic for the early detection of Turner, Klinefelter, Patau, Edwards and Down syndrome. These procedures can be lengthy, repetitive; and often employ invasive techniques so a robust automated method for classifying and reporting prenatal diagnostics would greatly help the clinicians with their routine work. The database consisted of data collected from 2500 pregnant woman that came to the Institute of Gynecology, Infertility and Perinatology "Mehmedbasic" for routine antenatal care between January 2000 and December 2016. During first trimester all women were subject to screening test where values of maternal serum pregnancy-associated plasma protein A (PAPP-A) and free beta human chorionic gonadotropin (β-hCG) were measured. Also, fetal nuchal translucency thickness and the presence or absence of the nasal bone was observed using ultrasound. The architectures of linear feedforward and feedback neural networks were investigated for various training data distributions and number of neurons in hidden layer. Feedback neural network architecture out performed feedforward neural network architecture in predictive ability for all five aneuploidy prenatal syndrome classes. Feedforward neural network with 15 neurons in hidden layer achieved classification sensitivity of 92.00%. Classification sensitivity of feedback (Elman's) neural network was 99.00%. Average accuracy of feedforward neural network was 89.6% and for feedback was 98.8%. The results presented in this paper prove that an expert diagnostic system based on neural networks can be efficiently used for classification of five aneuploidy syndromes, covered with this study, based on first trimester maternal serum screening data, ultrasonographic findings and patient demographics. Developed Expert System proved to be simple, robust, and powerful in properly classifying prenatal aneuploidy syndromes.

Prototype Expert System for Climate Classification.

ERIC Educational Resources Information Center

Harris, Clay

Many students find climate classification laborious and time-consuming, and through their lack of repetition fail to grasp the details of classification. This paper describes an expert system for climate classification that is being developed at Middle Tennessee State University. Topics include: (1) an introduction to the nature of classification,…

Palomar 60-inch SEDM classification of optical transients

NASA Astrophysics Data System (ADS)

Fremling, Christoffer; Blagorodnova, Nadejda; Neill, James D.; Walters, Richard; Cannella, Christopher B.; Kulkarni, Shrinivas R.

2018-03-01

We report the classification of the following bright transients. The spectra have been obtained with the Spectral Energy Distribution Machine (SEDM) (range 350-950nm, spectral resolution R 100) mounted on the Palomar 60-inch (P60) telescope (Blagorodnova et. al. 2018).

Recipe creation for automated defect classification with a 450mm surface scanning inspection system based on the bidirectional reflectance distribution function of native defects

NASA Astrophysics Data System (ADS)

Yathapu, Nithin; McGarvey, Steve; Brown, Justin; Zhivotovsky, Alexander

2016-03-01

This study explores the feasibility of Automated Defect Classification (ADC) with a Surface Scanning Inspection System (SSIS). The defect classification was based upon scattering sensitivity sizing curves created via modeling of the Bidirectional Reflectance Distribution Function (BRDF). The BRDF allowed for the creation of SSIS sensitivity/sizing curves based upon the optical properties of both the filmed wafer samples and the optical architecture of the SSIS. The elimination of Polystyrene Latex Sphere (PSL) and Silica deposition on both filmed and bare Silicon wafers prior to SSIS recipe creation and ADC creates a challenge for light scattering surface intensity based defect binning. This study explored the theoretical maximal SSIS sensitivity based on native defect recipe creation in conjunction with the maximal sensitivity derived from BRDF modeling recipe creation. Single film and film stack wafers were inspected with recipes based upon BRDF modeling. Following SSIS recipe creation, initially targeting maximal sensitivity, selected recipes were optimized to classify defects commonly found on non-patterned wafers. The results were utilized to determine the ADC binning accuracy of the native defects and evaluate the SSIS recipe creation methodology. A statistically valid sample of defects from the final inspection results of each SSIS recipe and filmed substrate were reviewed post SSIS ADC processing on a Defect Review Scanning Electron Microscope (SEM). Native defect images were collected from each statistically valid defect bin category/size for SEM Review. The data collected from the Defect Review SEM was utilized to determine the statistical purity and accuracy of each SSIS defect classification bin. This paper explores both, commercial and technical, considerations of the elimination of PSL and Silica deposition as a precursor to SSIS recipe creation targeted towards ADC. Successful integration of SSIS ADC in conjunction with recipes created via BRDF modeling has the potential to dramatically reduce the workload requirements of a Defect Review SEM and save a significant amount of capital expenditure for 450mm SSIS recipe creation.

Email recruitment to use web decision support tools for pneumonia.

PubMed

Flanagan, James R; Peterson, Michael; Dayton, Charles; Strommer Pace, Lori; Plank, Andrew; Walker, Kristy; Carlson, William S

2002-01-01

Application of guidelines to improve clinical decisions for Community Acquired Pneumonia (CAP) patients depends on accurate information about specific facts of each case and on presenting guideline support at the time decisions are being made. We report here on a system designed to solicit information from physicians about their CAP patients in order to classify CAP and present appropriate guidelines for type of care, length of stay, and use of antibiotics. We used elements of three existing information systems to create a achieve these goals: professionals coding diagnoses captured by the existing clinical information system (CIS), email, and web-based decision support tools including a pneumonia severity evaluation tool (SET). The non-secure IS components (email and web) were able to link to information in the CIS using tokens that do not reveal confidential patient-identifiable information. We examined their response to this strategy and the accuracy of pneumonia classification using this approach compared to chart review as a gold standard. On average physicians responded to email solicitations 50% of the time over the 14 month study. Also using this standard, we examined various information triggers for case finding. Professional coding of the primary reason for admission as pneumonia was fairly sensitive as an indicator of CAP. Physician use of the web SET was insensitive but fairly specific. Pneumonia classification using the SET was very reliable compared to experts' chart review using the same algorithm. We examined the distribution of severity of pneumonia for cases of pneumonia found by the various information triggers and for each severity the average length of stay. The distribution found by both chart review and by SET has demonstrated a shift toward more severe cases being admitted compared to only 3 years ago. The length of stay for level of severity is above expectations published by guidelines even for cases of true CAP by chart review. We suggest that the Fine classification system may not adequately describe patients in this setting. Physicians frequently responded that the guidelines presented did not fit their patients.

5 CFR 9901.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9901.221 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

Anticipating the Chaotic Behaviour of Industrial Systems Based on Stochastic, Event-Driven Simulations

NASA Astrophysics Data System (ADS)

Bruzzone, Agostino G.; Revetria, Roberto; Simeoni, Simone; Viazzo, Simone; Orsoni, Alessandra

2004-08-01

In logistics and industrial production managers must deal with the impact of stochastic events to improve performances and reduce costs. In fact, production and logistics systems are generally designed considering some parameters as deterministically distributed. While this assumption is mostly used for preliminary prototyping, it is sometimes also retained during the final design stage, and especially for estimated parameters (i.e. Market Request). The proposed methodology can determine the impact of stochastic events in the system by evaluating the chaotic threshold level. Such an approach, based on the application of a new and innovative methodology, can be implemented to find the condition under which chaos makes the system become uncontrollable. Starting from problem identification and risk assessment, several classification techniques are used to carry out an effect analysis and contingency plan estimation. In this paper the authors illustrate the methodology with respect to a real industrial case: a production problem related to the logistics of distributed chemical processing.

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

PubMed

Mrabet, Yassine; Semmar, Nabil

2010-05-01

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

Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification

PubMed Central

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-01-01

Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. PMID:25277605

New tools for evaluating LQAS survey designs

PubMed Central

2014-01-01

Lot Quality Assurance Sampling (LQAS) surveys have become increasingly popular in global health care applications. Incorporating Bayesian ideas into LQAS survey design, such as using reasonable prior beliefs about the distribution of an indicator, can improve the selection of design parameters and decision rules. In this paper, a joint frequentist and Bayesian framework is proposed for evaluating LQAS classification accuracy and informing survey design parameters. Simple software tools are provided for calculating the positive and negative predictive value of a design with respect to an underlying coverage distribution and the selected design parameters. These tools are illustrated using a data example from two consecutive LQAS surveys measuring Oral Rehydration Solution (ORS) preparation. Using the survey tools, the dependence of classification accuracy on benchmark selection and the width of the ‘grey region’ are clarified in the context of ORS preparation across seven supervision areas. Following the completion of an LQAS survey, estimation of the distribution of coverage across areas facilitates quantifying classification accuracy and can help guide intervention decisions. PMID:24528928

New tools for evaluating LQAS survey designs.

PubMed

Hund, Lauren

2014-02-15

Lot Quality Assurance Sampling (LQAS) surveys have become increasingly popular in global health care applications. Incorporating Bayesian ideas into LQAS survey design, such as using reasonable prior beliefs about the distribution of an indicator, can improve the selection of design parameters and decision rules. In this paper, a joint frequentist and Bayesian framework is proposed for evaluating LQAS classification accuracy and informing survey design parameters. Simple software tools are provided for calculating the positive and negative predictive value of a design with respect to an underlying coverage distribution and the selected design parameters. These tools are illustrated using a data example from two consecutive LQAS surveys measuring Oral Rehydration Solution (ORS) preparation. Using the survey tools, the dependence of classification accuracy on benchmark selection and the width of the 'grey region' are clarified in the context of ORS preparation across seven supervision areas. Following the completion of an LQAS survey, estimation of the distribution of coverage across areas facilitates quantifying classification accuracy and can help guide intervention decisions.

The Bellevue Classification System: nursing's voice upon the library shelves*†

PubMed Central

Mages, Keith C

2011-01-01

This article examines the inspiration, construction, and meaning of the Bellevue Classification System (BCS), created during the 1930s for use in the Bellevue School of Nursing Library. Nursing instructor Ann Doyle, with assistance from librarian Mary Casamajor, designed the BCS after consulting with library leaders and examining leading contemporary classification systems, including the Dewey Decimal Classification and Library of Congress, Ballard, and National Health Library classification systems. A close textual reading of the classes, subclasses, and subdivisions of these classification systems against those of the resulting BCS, reveals Doyle's belief that the BCS was created not only to organize the literature, but also to promote the burgeoning intellectualism and professionalism of early twentieth-century American nursing. PMID:21243054

Coordination of Local Road Classification with the State Highway System Classification: Impact and Clarification of Related Language in the LVR Manual

DOT National Transportation Integrated Search

1996-02-01

This study reviewed the low volume road (LVR) classifications in Kansas in conjunction with the State A, B, C, D, E road classification system and addressed alignment of these differences. As an extension to the State system, an F, G, H classificatio...

Non-Gaussian Distributions Affect Identification of Expression Patterns, Functional Annotation, and Prospective Classification in Human Cancer Genomes

PubMed Central

Marko, Nicholas F.; Weil, Robert J.

2012-01-01

Introduction Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. Methods We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. Results Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. Conclusions Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that “small” departures from normality in the expression data distributions are analytically-insignificant and that “robust” gene-calling algorithms can fully compensate for these effects. PMID:23118863

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Marine habitat mapping, classification and monitoring in the coastal North Sea: Scientific vs. stakeholder interests

NASA Astrophysics Data System (ADS)

Hass, H. Christian; Mielck, Finn; Papenmeier, Svenja; Fiorentino, Dario

2016-04-01

Producing detailed maps of the seafloor that include both, water depth and simple textural characteristics has always been a challenge to scientists. In this context, marine habitat maps are an essential tool to comprehend the complexity, the spatial distribution and the ecological status of different seafloor types. The increasing need for more detail demands additional information on the texture of the sediment, bedforms and information on benthic sessile life. For long time, taking samples and videos/photographs followed by interpolation over larger distances was the only feasible way to gain information about sedimentary features such as grain-size distribution and bedforms. While ground truthing is still necessary, swath systems such as multibeam echo sounders (MBES) and sidescan sonars (SSS), as well as single beam acoustic ground discrimination systems (AGDS) became available to map the seafloor area-wide (MBES, SSS), fast and in great detail. Where area-wide measurements are impossible or unavailable point measurements are interpolated, classified and modeled. To keep pace with environmental change in the highly dynamic coastal areas of the North Sea (here: German Bight) monitoring that utilizes all of the mentioned techniques is a necessity. Since monitoring of larger areas is quite expensive, concepts for monitoring strategies were developed in scientific projects such as "WIMO" ("Scientific monitoring concepts for the German Bight, SE North Sea"). While instrumentation becomes better and better and interdisciplinary methods are being developed, the gap between basic scientific interests and stakeholder needs often seem to move in opposite directions. There are two main tendencies: the need to better understand nature systems (for theoretical purposes) and the one to simplify nature (for applied purposes). Science trends to resolve the most detail in highest precision employing soft gradients and/or fuzzy borders instead of crisp demarcations and classifications of habitats wherever this is suitable. At the same time e.g. the European authorities put much effort into the standardization of habitat classifications (e.g. EUNIS) which is essentially a massive reduction of the information content. While standardization is a necessary and important task aiming at aiding e.g. the public authorities in protecting and managing marine habitats, much information is lost on the way without actually knowing its role in explaining the natural system. In this study we show examples from various coastal areas of the North Sea concerning raw data, processed data, interpolated, modeled and classified data. We compare classifications and evaluate the information contents as well as the entropy change across the data processing stages.

Remote Sensing Systems to Detect and Analyze Oil Spills on the U.S. Outer Continental Shelf - A State of the Art Assessment

DTIC Science & Technology

2016-08-18

multi- sensor remote sensing approach to describe the distribution of oil from the DWH spill. They used airborne and satellite , multi- and hyperspectral...Experimental Sensors e.g., Acoustic and Nuclear Magnetic Resonance (NMR) (Fingas and Brown, 2012; Puestow et al., 2013). These are further...ship, aerial - aircraft, aerostat or UAV, or satellite ), among other classification criteria. A comprehensive review of sensor categories employed

Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection

NASA Astrophysics Data System (ADS)

Sakuma, Jun; Wright, Rebecca N.

Privacy-preserving classification is the task of learning or training a classifier on the union of privately distributed datasets without sharing the datasets. The emphasis of existing studies in privacy-preserving classification has primarily been put on the design of privacy-preserving versions of particular data mining algorithms, However, in classification problems, preprocessing and postprocessing— such as model selection or attribute selection—play a prominent role in achieving higher classification accuracy. In this paper, we show generalization error of classifiers in privacy-preserving classification can be securely evaluated without sharing prediction results. Our main technical contribution is a new generalized Hamming distance protocol that is universally applicable to preprocessing and postprocessing of various privacy-preserving classification problems, such as model selection in support vector machine and attribute selection in naive Bayes classification.

Classifying Measures of Biological Variation

PubMed Central

Gregorius, Hans-Rolf; Gillet, Elizabeth M.

2015-01-01

Biological variation is commonly measured at two basic levels: variation within individual communities, and the distribution of variation over communities or within a metacommunity. We develop a classification for the measurement of biological variation on both levels: Within communities into the categories of dispersion and diversity, and within metacommunities into the categories of compositional differentiation and partitioning of variation. There are essentially two approaches to characterizing the distribution of trait variation over communities in that individuals with the same trait state or type tend to occur in the same community (describes differentiation tendencies), and individuals with different types tend to occur in different communities (describes apportionment tendencies). Both approaches can be viewed from the dual perspectives of trait variation distributed over communities (CT perspective) and community membership distributed over trait states (TC perspective). This classification covers most of the relevant descriptors (qualified measures) of biological variation, as is demonstrated with the help of major families of descriptors. Moreover, the classification is shown to open ways to develop new descriptors that meet current needs. Yet the classification also reveals the misclassification of some prominent and widely applied descriptors: Dispersion is often misclassified as diversity, particularly in cases where dispersion descriptor allow for the computation of effective numbers; the descriptor GST of population genetics is commonly misclassified as compositional differentiation and confused with partitioning-oriented differentiation, whereas it actually measures partitioning-oriented apportionment; descriptors of β-diversity are ambiguous about the differentiation effects they are supposed to represent and therefore require conceptual reconsideration. PMID:25807558

Palomar 60-inch SEDM classification of optical transients

NASA Astrophysics Data System (ADS)

Fremling, Christoffer; Blagorodnova, Nadejda; Kupfer, Thomas; Neill, James D.; Walters, Richard; Cannella, Christopher B.; Kulkarni, Shrinivas R.

2018-04-01

We report the classification of the following bright transients. The spectra have been obtained with the Spectral Energy Distribution Machine (SEDM) (range 350-950nm, spectral resolution R 100) mounted on the Palomar 60-inch (P60) telescope (Blagorodnova et. al. 2018, PASP, 130, 5003).

Palomar 60-inch SEDM classification of optical transients

NASA Astrophysics Data System (ADS)

Blagorodnova, Nadejda; Fremling, Christoffer; Neill, James D.; Walters, Richard; Cannella, Christopher B.; Kulkarni, Shrinivas R.

2018-03-01

We report the classification of the following bright transients. The spectra have been obtained with the Spectral Energy Distribution Machine (SEDM) (range 350-950nm, spectral resolution R 100) mounted on the Palomar 60-inch (P60) telescope (Blagorodnova et. al. 2018, PASP, 130, 5003).

Classification of JET Neutron and Gamma Emissivity Profiles

NASA Astrophysics Data System (ADS)

Craciunescu, T.; Murari, A.; Kiptily, V.; Vega, J.; Contributors, JET

2016-05-01

In thermonuclear plasmas, emission tomography uses integrated measurements along lines of sight (LOS) to determine the two-dimensional (2-D) spatial distribution of the volume emission intensity. Due to the availability of only a limited number views and to the coarse sampling of the LOS, the tomographic inversion is a limited data set problem. Several techniques have been developed for tomographic reconstruction of the 2-D gamma and neutron emissivity on JET. In specific experimental conditions the availability of LOSs is restricted to a single view. In this case an explicit reconstruction of the emissivity profile is no longer possible. However, machine learning classification methods can be used in order to derive the type of the distribution. In the present approach the classification is developed using the theory of belief functions which provide the support to fuse the results of independent clustering and supervised classification. The method allows to represent the uncertainty of the results provided by different independent techniques, to combine them and to manage possible conflicts.

Classification Algorithms for Big Data Analysis, a Map Reduce Approach

NASA Astrophysics Data System (ADS)

Ayma, V. A.; Ferreira, R. S.; Happ, P.; Oliveira, D.; Feitosa, R.; Costa, G.; Plaza, A.; Gamba, P.

2015-03-01

Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), which is an open-source, distributed framework for automatic image interpretation, is presented. The tool, named ICP: Data Mining Package, is able to perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed infrastructure using Hadoop MapReduce. The tool has four classification algorithms implemented, taken from WEKA's machine learning library, namely: Decision Trees, Naïve Bayes, Random Forest and Support Vector Machines (SVM). The results of an experimental analysis using a SVM classifier on data sets of different sizes for different cluster configurations demonstrates the potential of the tool, as well as aspects that affect its performance.

SkICAT: A cataloging and analysis tool for wide field imaging surveys

NASA Technical Reports Server (NTRS)

Weir, N.; Fayyad, U. M.; Djorgovski, S. G.; Roden, J.

1992-01-01

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging.

PubMed

Ravi, Daniele; Fabelo, Himar; Callic, Gustavo Marrero; Yang, Guang-Zhong

2017-09-01

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.

Improving imbalanced scientific text classification using sampling strategies and dictionaries.

PubMed

Borrajo, L; Romero, R; Iglesias, E L; Redondo Marey, C M

2011-09-15

Many real applications have the imbalanced class distribution problem, where one of the classes is represented by a very small number of cases compared to the other classes. One of the systems affected are those related to the recovery and classification of scientific documentation. Sampling strategies such as Oversampling and Subsampling are popular in tackling the problem of class imbalance. In this work, we study their effects on three types of classifiers (Knn, SVM and Naive-Bayes) when they are applied to search on the PubMed scientific database. Another purpose of this paper is to study the use of dictionaries in the classification of biomedical texts. Experiments are conducted with three different dictionaries (BioCreative, NLPBA, and an ad-hoc subset of the UniProt database named Protein) using the mentioned classifiers and sampling strategies. Best results were obtained with NLPBA and Protein dictionaries and the SVM classifier using the Subsampling balancing technique. These results were compared with those obtained by other authors using the TREC Genomics 2005 public corpus. Copyright 2011 The Author(s). Published by Journal of Integrative Bioinformatics.

Classification of close binary systems by Svechnikov

NASA Astrophysics Data System (ADS)

Dryomova, G. N.

The paper presents the historical overview of classification schemes of eclipsing variable stars with the foreground of advantages of the classification scheme by Svechnikov being widely appreciated for Close Binary Systems due to simplicity of classification criteria and brevity.

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

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

Examining the Effect of Transverse Motion on Retinal Biometric Identifiers Relating to Shipboard Security Mechanisms

DTIC Science & Technology

1986-03-01

CLASSIFICATION OF THIS PAGEZ-~-ft! -q 1 REPORT DOCUMENTATION PAGE a REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS . UNCLASSIFIED """ a. SECURITY...CLASSIFICATION AUTHORITY 3 DISTRiBUTION(/AVAILABILITY OF REPORT Approved for public release; 2b. DECLASSIFICATION/ DOWNGRADING SCHEDULE distribution...is un 1 im i ted 4 PERFORMING ORGANIZATION REPORT NUMBER(S) S. MONITORING ORGANIZATION REPOR•r NUMBER(S) j a.NAME OF PERFORMING ORGANIZATION 16b

State-to-State Thermal/Hyperthermal Collision Dynamics of Atmospheric Species

DTIC Science & Technology

2012-02-28

kinetics 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT 18 . SECURITY CLASSIFICATION OF THIS PAGE 19. SECURITY CLASSIFICATION...OF ABSTRACT 20. LIMITATION OF ABSTRACT NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39- 18 298-102 AFRL...populations, though colder, are also highly excited in a non-Boltzmann distribution, [ Erot  =1.0(1) kcal/mol], which indicates that a substantial fraction

Nonlinear Interactions between Laser Radiation and Spin-Aligned Carriers in Semiconductors.

DTIC Science & Technology

1980-11-25

Massachusetts 02154 AIR FORCE OFFICEK OF SCIWMTIFIC RESWACHi (AISC) NOTICE OF TRJAZSMITTAL TO DDC This techniical raouti has been reviewed an I approved...f’or PuAli release JAN A.FR 190-12 (7b). Distribution is wilimited. &. D. BLOSA Technical Inorwatiom Oftlee UNCLASSIFIED SECURITY CLASSIFICATION OF...well. The material of choice D I 1473 UNCLASSIFIED.6- SECURITY CLASSIFICATION OF THIS PAGE (mien Deta Entered) UNCLASSIFIED SECURITY CLASSIFICATION OF

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

PubMed

Dijemeni, Esuabom; D'Amone, Gabriele; Gbati, Israel

2017-12-01

Drug-induced sedation endoscopy (DISE) classification systems have been used to assess anatomical findings on upper airway obstruction, and decide and plan surgical treatments and act as a predictor for surgical treatment outcome for obstructive sleep apnoea management. The first objective is to identify if there is a universally accepted DISE grading and classification system for analysing DISE findings. The second objective is to identify if there is one DISE grading and classification treatment planning framework for deciding appropriate surgical treatment for obstructive sleep apnoea (OSA). The third objective is to identify if there is one DISE grading and classification treatment outcome framework for determining the likelihood of success for a given OSA surgical intervention. A systematic review was performed to identify new and significantly modified DISE classification systems: concept, advantages and disadvantages. Fourteen studies proposing a new DISE classification system and three studies proposing a significantly modified DISE classification were identified. None of the studies were based on randomised control trials. DISE is an objective method for visualising upper airway obstruction. The classification and assessment of clinical findings based on DISE is highly subjective due to the increasing number of DISE classification systems. Hence, this creates a growing divergence in surgical treatment planning and treatment outcome. Further research on a universally accepted objective DISE assessment is critically needed.

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

PubMed

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

Classification of Anticipatory Signals for Grasp and Release from Surface Electromyography.

PubMed

Siu, Ho Chit; Shah, Julie A; Stirling, Leia A

2016-10-25

Surface electromyography (sEMG) is a technique for recording natural muscle activation signals, which can serve as control inputs for exoskeletons and prosthetic devices. Previous experiments have incorporated these signals using both classical and pattern-recognition control methods in order to actuate such devices. We used the results of an experiment incorporating grasp and release actions with object contact to develop an intent-recognition system based on Gaussian mixture models (GMM) and continuous-emission hidden Markov models (HMM) of sEMG data. We tested this system with data collected from 16 individuals using a forearm band with distributed sEMG sensors. The data contain trials with shifted band alignments to assess robustness to sensor placement. This study evaluated and found that pattern-recognition-based methods could classify transient anticipatory sEMG signals in the presence of shifted sensor placement and object contact. With the best-performing classifier, the effect of label lengths in the training data was also examined. A mean classification accuracy of 75.96% was achieved through a unigram HMM method with five mixture components. Classification accuracy on different sub-movements was found to be limited by the length of the shortest sub-movement, which means that shorter sub-movements within dynamic sequences require larger training sets to be classified correctly. This classification of user intent is a potential control mechanism for a dynamic grasping task involving user contact with external objects and noise. Further work is required to test its performance as part of an exoskeleton controller, which involves contact with actuated external surfaces.

Comparative analysis of distribution and abundance of West Nile and Eastern Equine Encephalomyelitis virus vectors in Suffolk County, New York, using human population density and land use/cover data

USGS Publications Warehouse

Rochlin, I.; Harding, K.; Ginsberg, H.S.; Campbell, S.R.

2008-01-01

Five years of CDC light trap data from Suffolk County, NY, were analyzed to compare the applicability of human population density (HPD) and land use/cover (LUC) classification systems to describe mosquito abundance and to determine whether certain mosquito species of medical importance tend to be more common in urban (defined by HPD) or residential (defined by LUC) areas. Eleven study sites were categorized as urban or rural using U.S. Census Bureau data and by LUC types using geographic information systems (GISs). Abundance and percent composition of nine mosquito taxa, all known or potential vectors of arboviruses, were analyzed to determine spatial patterns. By HPD definitions, three mosquito species, Aedes canadensis (Theobald), Coquillettidia perturbans (Walker), and Culiseta melanura (Coquillett), differed significantly between habitat types, with higher abundance and percent composition in rural areas. Abundance and percent composition of these three species also increased with freshwater wetland, natural vegetation areas, or a combination when using LUC definitions. Additionally, two species, Ae. canadensis and Cs. melanura, were negatively affected by increased residential area. One species, Aedes vexans (Meigen), had higher percent composition in urban areas. Two medically important taxa, Culex spp. and Aedes triseriatus (Say), were proportionally more prevalent in residential areas by LUC classification, as was Aedes trivittatus (Coquillett). Although HPD classification was readily available and had some predictive value, LUC classification resulted in higher spatial resolution and better ability to develop location specific predictive models.

Classification of Anticipatory Signals for Grasp and Release from Surface Electromyography

PubMed Central

Siu, Ho Chit; Shah, Julie A.; Stirling, Leia A.

2016-01-01

Surface electromyography (sEMG) is a technique for recording natural muscle activation signals, which can serve as control inputs for exoskeletons and prosthetic devices. Previous experiments have incorporated these signals using both classical and pattern-recognition control methods in order to actuate such devices. We used the results of an experiment incorporating grasp and release actions with object contact to develop an intent-recognition system based on Gaussian mixture models (GMM) and continuous-emission hidden Markov models (HMM) of sEMG data. We tested this system with data collected from 16 individuals using a forearm band with distributed sEMG sensors. The data contain trials with shifted band alignments to assess robustness to sensor placement. This study evaluated and found that pattern-recognition-based methods could classify transient anticipatory sEMG signals in the presence of shifted sensor placement and object contact. With the best-performing classifier, the effect of label lengths in the training data was also examined. A mean classification accuracy of 75.96% was achieved through a unigram HMM method with five mixture components. Classification accuracy on different sub-movements was found to be limited by the length of the shortest sub-movement, which means that shorter sub-movements within dynamic sequences require larger training sets to be classified correctly. This classification of user intent is a potential control mechanism for a dynamic grasping task involving user contact with external objects and noise. Further work is required to test its performance as part of an exoskeleton controller, which involves contact with actuated external surfaces. PMID:27792155

The postoperative COFAS end-stage ankle arthritis classification system: interobserver and intraobserver reliability.

PubMed

Krause, Fabian G; Di Silvestro, Matthew; Penner, Murray J; Wing, Kevin J; Glazebrook, Mark A; Daniels, Timothy R; Lau, Johnny T C; Younger, Alastair S E

2012-02-01

End-stage ankle arthritis is operatively treated with numerous designs of total ankle replacement and different techniques for ankle fusion. For superior comparison of these procedures, outcome research requires a classification system to stratify patients appropriately. A postoperative 4-type classification system was designed by 6 fellowship-trained foot and ankle surgeons. Four surgeons reviewed blinded patient profiles and radiographs on 2 occasions to determine the interobserver and intraobserver reliability of the classification. Excellent interobserver reliability (κ = .89) and intraobserver reproducibility (κ = .87) were demonstrated for the postoperative classification system. In conclusion, the postoperative Canadian Orthopaedic Foot and Ankle Society (COFAS) end-stage ankle arthritis classification system appears to be a valid tool to evaluate the outcome of patients operated for end-stage ankle arthritis.

Classification of stellar spectra with SVM based on within-class scatter and between-class scatter

NASA Astrophysics Data System (ADS)

Liu, Zhong-bao; Zhou, Fang-xiao; Qin, Zhen-tao; Luo, Xue-gang; Zhang, Jing

2018-07-01

Support Vector Machine (SVM) is a popular data mining technique, and it has been widely applied in astronomical tasks, especially in stellar spectra classification. Since SVM doesn't take the data distribution into consideration, and therefore, its classification efficiencies can't be greatly improved. Meanwhile, SVM ignores the internal information of the training dataset, such as the within-class structure and between-class structure. In view of this, we propose a new classification algorithm-SVM based on Within-Class Scatter and Between-Class Scatter (WBS-SVM) in this paper. WBS-SVM tries to find an optimal hyperplane to separate two classes. The difference is that it incorporates minimum within-class scatter and maximum between-class scatter in Linear Discriminant Analysis (LDA) into SVM. These two scatters represent the distributions of the training dataset, and the optimization of WBS-SVM ensures the samples in the same class are as close as possible and the samples in different classes are as far as possible. Experiments on the K-, F-, G-type stellar spectra from Sloan Digital Sky Survey (SDSS), Data Release 8 show that our proposed WBS-SVM can greatly improve the classification accuracies.

DREAM: Classification scheme for dialog acts in clinical research query mediation.

PubMed

Hoxha, Julia; Chandar, Praveen; He, Zhe; Cimino, James; Hanauer, David; Weng, Chunhua

2016-02-01

Clinical data access involves complex but opaque communication between medical researchers and query analysts. Understanding such communication is indispensable for designing intelligent human-machine dialog systems that automate query formulation. This study investigates email communication and proposes a novel scheme for classifying dialog acts in clinical research query mediation. We analyzed 315 email messages exchanged in the communication for 20 data requests obtained from three institutions. The messages were segmented into 1333 utterance units. Through a rigorous process, we developed a classification scheme and applied it for dialog act annotation of the extracted utterances. Evaluation results with high inter-annotator agreement demonstrate the reliability of this scheme. This dataset is used to contribute preliminary understanding of dialog acts distribution and conversation flow in this dialog space. Copyright © 2015 Elsevier Inc. All rights reserved.

A Visual Basic program to classify sediments based on gravel-sand-silt-clay ratios

USGS Publications Warehouse

Poppe, L.J.; Eliason, A.H.; Hastings, M.E.

2003-01-01

Nomenclature describing size distributions is important to geologists because grain size is the most basic attribute of sediments. Traditionally, geologists have divided sediments into four size fractions that include gravel, sand, silt, and clay, and classified these sediments based on ratios of the various proportions of the fractions. Definitions of these fractions have long been standardized to the grade scale described by Wentworth (1922), and two main classification schemes have been adopted to describe the approximate relationship between the size fractions.Specifically, according to the Wentworth grade scale gravel-sized particles have a nominal diameter of ⩾2.0 mm; sand-sized particles have nominal diameters from <2.0 mm to ⩾62.5 μm; silt-sized particles have nominal diameters from <62.5 to ⩾4.0 μm; and clay is <4.0 μm. As for sediment classification, most sedimentologists use one of the systems described either by Shepard (1954) or Folk (1954, 1974). The original scheme devised by Shepard (1954) utilized a single ternary diagram with sand, silt, and clay in the corners to graphically show the relative proportions among these three grades within a sample. This scheme, however, does not allow for sediments with significant amounts of gravel. Therefore, Shepard's classification scheme (Fig. 1) was subsequently modified by the addition of a second ternary diagram to account for the gravel fraction (Schlee, 1973). The system devised by Folk (1954, 1974) is also based on two triangular diagrams (Fig. 2), but it has 23 major categories, and uses the term mud (defined as silt plus clay). The patterns within the triangles of both systems differ, as does the emphasis placed on gravel. For example, in the system described by Shepard, gravelly sediments have more than 10% gravel; in Folk's system, slightly gravelly sediments have as little as 0.01% gravel. Folk's classification scheme stresses gravel because its concentration is a function of the highest current velocity at the time of deposition, together with the maximum grain size of the detritus that is available; Shepard's classification scheme emphasizes the ratios of sand, silt, and clay because they reflect sorting and reworking (Poppe et al., 2000).

Railroad Classification Yard Technology Manual: Volume II : Yard Computer Systems

DOT National Transportation Integrated Search

1981-08-01

This volume (Volume II) of the Railroad Classification Yard Technology Manual documents the railroad classification yard computer systems methodology. The subjects covered are: functional description of process control and inventory computer systems,...

Jobs in Marketing and Distribution. Job Family Series.

ERIC Educational Resources Information Center

Science Research Associates, Inc., Chicago, IL.

The booklet describes jobs in marketing and distribution in the following chapter classifications: product development, marketing products and property, salesworkers unlimited, selling intangibles (ideas and services), purchasing and distribution, and management and marketing services. For each occupation duties are outlined and working conditions…

Filtering big data from social media--Building an early warning system for adverse drug reactions.

PubMed

Yang, Ming; Kiang, Melody; Shang, Wei

2015-04-01

Adverse drug reactions (ADRs) are believed to be a leading cause of death in the world. Pharmacovigilance systems are aimed at early detection of ADRs. With the popularity of social media, Web forums and discussion boards become important sources of data for consumers to share their drug use experience, as a result may provide useful information on drugs and their adverse reactions. In this study, we propose an automated ADR related posts filtering mechanism using text classification methods. In real-life settings, ADR related messages are highly distributed in social media, while non-ADR related messages are unspecific and topically diverse. It is expensive to manually label a large amount of ADR related messages (positive examples) and non-ADR related messages (negative examples) to train classification systems. To mitigate this challenge, we examine the use of a partially supervised learning classification method to automate the process. We propose a novel pharmacovigilance system leveraging a Latent Dirichlet Allocation modeling module and a partially supervised classification approach. We select drugs with more than 500 threads of discussion, and collect all the original posts and comments of these drugs using an automatic Web spidering program as the text corpus. Various classifiers were trained by varying the number of positive examples and the number of topics. The trained classifiers were applied to 3000 posts published over 60 days. Top-ranked posts from each classifier were pooled and the resulting set of 300 posts was reviewed by a domain expert to evaluate the classifiers. Compare to the alternative approaches using supervised learning methods and three general purpose partially supervised learning methods, our approach performs significantly better in terms of precision, recall, and the F measure (the harmonic mean of precision and recall), based on a computational experiment using online discussion threads from Medhelp. Our design provides satisfactory performance in identifying ADR related posts for post-marketing drug surveillance. The overall design of our system also points out a potentially fruitful direction for building other early warning systems that need to filter big data from social media networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Cause of and factors associated with stillbirth: a systematic review of classification systems.

PubMed

Aminu, Mamuda; Bar-Zeev, Sarah; van den Broek, Nynke

2017-05-01

An estimated 2.6 million stillbirths occur worldwide each year. A standardized classification system setting out possible cause of death and contributing factors is useful to help obtain comparative data across different settings. We undertook a systematic review of stillbirth classification systems to highlight their strengths and weaknesses for practitioners and policymakers. We conducted a systematic search and review of the literature to identify the classification systems used to aggregate information for stillbirth and perinatal deaths. Narrative synthesis was used to compare the range and depth of information required to apply the systems, and the different categories provided for cause of and factors contributing to stillbirth. A total of 118 documents were screened; 31 classification systems were included, of which six were designed specifically for stillbirth, 14 for perinatal death, three systems included neonatal deaths and two included infant deaths. Most (27/31) were developed in and first tested using data obtained from high-income settings. All systems required information from clinical records. One-third of the classification systems (11/31) included information obtained from histology or autopsy. The percentage where cause of death remained unknown ranged from 0.39% using the Nordic-Baltic classification to 46.4% using the Keeling system. Over time, classification systems have become more complex. The success of application is dependent on the availability of detailed clinical information and laboratory investigations. Systems that adopt a layered approach allow for classification of cause of death to a broad as well as to a more detailed level. © 2017 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Method for secure electronic voting system: face recognition based approach

NASA Astrophysics Data System (ADS)

Alim, M. Affan; Baig, Misbah M.; Mehboob, Shahzain; Naseem, Imran

2017-06-01

In this paper, we propose a framework for low cost secure electronic voting system based on face recognition. Essentially Local Binary Pattern (LBP) is used for face feature characterization in texture format followed by chi-square distribution is used for image classification. Two parallel systems are developed based on smart phone and web applications for face learning and verification modules. The proposed system has two tire security levels by using person ID followed by face verification. Essentially class specific threshold is associated for controlling the security level of face verification. Our system is evaluated three standard databases and one real home based database and achieve the satisfactory recognition accuracies. Consequently our propose system provides secure, hassle free voting system and less intrusive compare with other biometrics.

Spectroscopic classification of SN2018afm and SN2018aik

NASA Astrophysics Data System (ADS)

Blagorodnova, Nadejda; Fremling, Christoffer; Neill, James D.; Walters, Richard; Cannella, Christopher B.; Kulkarni, Shrinivas R.

2018-03-01

We report the classification of the following bright transients. The spectra have been obtained with the Spectral Energy Distribution Machine (SEDM) (range 350-950nm, spectral resolution R 100) mounted on the Palomar 60-inch (P60) telescope (Blagorodnova et. al. 2018, PASP, 130, 5003).

7 CFR 28.904 - Market news.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Market news. 28.904 Section 28.904 Agriculture..., TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.904 Market news. The Director shall cause to be distributed to producers of...

7 CFR 28.904 - Market news.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Market news. 28.904 Section 28.904 Agriculture..., TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.904 Market news. The Director shall cause to be distributed to producers of...

7 CFR 28.904 - Market news.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Market news. 28.904 Section 28.904 Agriculture..., TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.904 Market news. The Director shall cause to be distributed to producers of...

7 CFR 28.904 - Market news.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Market news. 28.904 Section 28.904 Agriculture..., TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.904 Market news. The Director shall cause to be distributed to producers of...

7 CFR 28.904 - Market news.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Market news. 28.904 Section 28.904 Agriculture..., TESTING, AND STANDARDS Cotton Classification and Market News Service for Producers Classification and Market News Services § 28.904 Market news. The Director shall cause to be distributed to producers of...

Estimating the Classification Efficiency of a Test Battery.

ERIC Educational Resources Information Center

De Corte, Wilfried

2000-01-01

Shows how a theorem proven by H. Brogden (1951, 1959) can be used to estimate the allocation average (a predictor based classification of a test battery) assuming that the predictor intercorrelations and validities are known and that the predictor variables have a joint multivariate normal distribution. (SLD)

Zn/Cd ratios and cadmium isotope evidence for the classification of lead-zinc deposits

PubMed Central

Wen, Hanjie; Zhu, Chuanwei; Zhang, Yuxu; Cloquet, Christophe; Fan, Haifeng; Fu, Shaohong

2016-01-01

Lead-zinc deposits are often difficult to classify because clear criteria are lacking. In recent years, new tools, such as Cd and Zn isotopes, have been used to better understand the ore-formation processes and to classify Pb-Zn deposits. Herein, we investigate Cd concentrations, Cd isotope systematics and Zn/Cd ratios in sphalerite from nine Pb-Zn deposits divided into high-temperature systems (e.g., porphyry), low-temperature systems (e.g., Mississippi Valley type [MVT]) and exhalative systems (e.g., sedimentary exhalative [SEDEX]). Our results showed little evidence of fractionation in the high-temperature systems. In the low-temperature systems, Cd concentrations were the highest, but were also highly variable, a result consistent with the higher fractionation of Cd at low temperatures. The δ114/110Cd values in low-temperature systems were enriched in heavier isotopes (mean of 0.32 ± 0.31‰). Exhalative systems had the lowest Cd concentrations, with a mean δ114/110Cd value of 0.12 ± 0.50‰. We thus conclude that different ore-formation systems result in different characteristic Cd concentrations and fraction levels and that low-temperature processes lead to the most significant fractionation of Cd. Therefore, Cd distribution and isotopic studies can support better understanding of the geochemistry of ore-formation processes and the classification of Pb-Zn deposits. PMID:27121538

Distributed multimodal data fusion for large scale wireless sensor networks

NASA Astrophysics Data System (ADS)

Ertin, Emre

2006-05-01

Sensor network technology has enabled new surveillance systems where sensor nodes equipped with processing and communication capabilities can collaboratively detect, classify and track targets of interest over a large surveillance area. In this paper we study distributed fusion of multimodal sensor data for extracting target information from a large scale sensor network. Optimal tracking, classification, and reporting of threat events require joint consideration of multiple sensor modalities. Multiple sensor modalities improve tracking by reducing the uncertainty in the track estimates as well as resolving track-sensor data association problems. Our approach to solving the fusion problem with large number of multimodal sensors is construction of likelihood maps. The likelihood maps provide a summary data for the solution of the detection, tracking and classification problem. The likelihood map presents the sensory information in an easy format for the decision makers to interpret and is suitable with fusion of spatial prior information such as maps, imaging data from stand-off imaging sensors. We follow a statistical approach to combine sensor data at different levels of uncertainty and resolution. The likelihood map transforms each sensor data stream to a spatio-temporal likelihood map ideally suitable for fusion with imaging sensor outputs and prior geographic information about the scene. We also discuss distributed computation of the likelihood map using a gossip based algorithm and present simulation results.

The Role and Function of the Navy Office of Legislative Affairs in the Congressional Program Authorization and Budget Process

DTIC Science & Technology

1990-12-01

SECURITY CLASSIfICATON AUTHORITY I OSTRilJ-ON AVALAIILiTY OF REPORT Approved for public release; 20 DECLASSIFIA71ON/OOWNGRADiNG SCxIEDULI distribution is...8217; administrative budget formulation at the headquarters level throu oh connressional action in budget enactment, (2) the role and mission of the Office of the Navy...are nobsolete S .URITYY CLASSIFICATION O0 ’HIS PACE S/N 0102-LF-014-6603 Unclassified Approved for public release; distribution is unlimited. The Role

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

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

Remote Sensing and GIS for Landuse/Landcover Classification and Water Quality in the Northern Ireland

NASA Astrophysics Data System (ADS)

Amer, R.; Ofterdinger, U.; Ruffell, A.; Donald, A.

2012-04-01

This study presents landuse/landcover (LULC) classifications of Northern Ireland in order to quantify land-use types driving chemical loading in the surface water bodies. The major LULC classes are agricultural land, bare land (mountainous areas), forest, urban areas, and water bodies. Three ENVISAT ASAR multi-look precision images acquired in 2011 and two Enhanced Thematic Mapper Plus (ETM+) acquired in 2003 were used for classification. The ASAR digital numbers were converted to backscattering coefficient (sigma nought) and enhanced using adaptive Gamma filter and Gaussian stretch. Supervised classifications of Maximum Likelihood, Mahalanobils Distance, Minimum Distance, Spectral Angel Mapper, Parallelepiped, and Winner Tercat were applied on ETM+ and ASAR images. A confusion matrix was used to evaluate the classification accuracy; the best results of ETM+ and ASAR were given by the winner classification (82.9 and 73.6 %), and maximum likelihood (81.7 and 72.5 %), respectively. Change detection was applied to identify the areas of significant changes in landuse/landcover over the last eight years. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems and watersheds. Water quality data of the first and second order streams were extracted from 2005 survey by Geological Survey of Northern Ireland. GIS spatially distributed modelling generated maps showing the distribution of phosphorus (P), nitrate (NO3), dissolved organic carbon (DOC), and some of the trace elements including fluoride (F), calcium (Ca), aluminium (Al), iron (Fe), copper (Cu), lead (Pb), zinc (Zn), and arsenic (As) across the watersheds of the Northern Ireland were generated. The distribution of these elements was evaluated against the LULC classes and bed rock geology. Concentration of these elements was classified into normal (safe level), moderate, high, and very high based on the World Health Organization (WHO, 2011) water quality standards. The results show that P concentration is generally high across all the watersheds. NO3 is within normal range in all watersheds. DOC is within normal range in urban areas, moderate to high in agricultural lands, and high in the forest areas and bare lands. F and Fe are within safe level in all watersheds. Al, Cu, and As are high in all watersheds around the bare land LULC class which are underlain by psammite and semipelite metamorphic rocks. Ca is within normal range in most of watersheds but it is high in the south western part of the study area because of the presence of limestone bedrock. Pb and Zn are within normal range in the urban and most of the agricultural land, and high in the mountainous areas underlain by psammite and semipelite metamorphic bed rock.

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

PubMed

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

2017-12-01

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

Chemical Preparation Laboratory for IND Candidate Compounds

DTIC Science & Technology

1990-02-08

CLASSIFICATION lb. RESTRICTIVE MARKINGS Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3 . DISTRIBUTION /AVAILABILITY OF REPORT 2b. DECLASSIFICATION... 3 III. Cumulative list of Compounds Delivered to U.S. Army Medical Research and Development (USAMRIID) from January 17, 1989 to...AVS 52) ............................................ 7 2. Selenazole (AVS 253) ............................................... 9 3 . Methyl-l,2,4

ZTF Bright Transient Survey classifications

NASA Astrophysics Data System (ADS)

Fremling, C.; Sharma, Y.; Skulkarni, S. R.; Walters, R.; Blagorodnova, N.; Neill, J. D.; Miller, A. A.; Taggart, K.; Perley, D. A.; Goobar, A.; Graham, M. L.

2018-06-01

The Zwicky Transient Facility (ZTF; ATel #11266) Bright Transient Survey (BTS; ATel #11688) reports classifications of the following targets. Spectra have been obtained with the Spectral Energy Distribution Machine (SEDM) (range 350-950nm, spectral resolution R 100) mounted on the Palomar 60-inch (P60) telescope (Blagorodnova et. al. 2018, PASP, 130, 5003).

THE EFFECTS OF HABITAT RESOLUTION ON MODELS OF AVIAN DIVERSITY AND DISTRIBUTIONS: A COMPARISON OF TWO LAND-COVER CLASSIFICATIONS

EPA Science Inventory

The quantification of pattern is a key element of landscape analyses. One aspect of this quantification of particular importance to landscape ecologists regards the classification of continuous variables to produce categorical variables such as land-cover type or elevation strat...

[Considerations about the epidemiologic surveillance system on mesothelioma in Tuscany (Italy) after 25 years of activity].

PubMed

Chellini, Elisabetta; Martini, Andrea; Cacciarini, Valentina; Badiali, Anna Maria

2013-01-01

To present problems and opportunities related to the operating procedures developed by the Tuscan epidemiological surveillance system on mesothelioma during its 25 years of activity. All 1,224 mesotheliomas, registered up to 31.12. 2011, diagnosed in Tuscan residents during 1988-2009 by the Tuscan Operating Centre of the Italian registry, have been considered. In order to evaluate accuracy and completeness of cases, the following indicators by period are used for pleural mesotheliomas diagnosed during 1988-2009: the distribution of the sources of cases' diagnosis and report to the regional registry, the latency time between diagnosis and report, the age and sex specific rates, the ratio between standardized mortality and incidence rates. The distribution of type of interview and exposure classification by period for all cases were used to evaluate the collected and classified exposure information. Histology with immunohistochemistry became the chosen method (97.4% of histological cases in 2005- 2009). Since the second half of the Nineties, other Italian regional Operating Centres and, more recently, the Workers Compensation Authority (INAIL) became new important sources of case report. Nowadays, the mortality/incidence ratio is closer to 1. The latency time between diagnosis and case report have been reducing with a consequent increase in direct interviews to cases (from 20.3% in 1988-1993 to 71.4% in 2005-2009) and in exposure information and classification quality. The regional network with the effective cooperation of the Local Health Authorities produced relevant improvements in the quality of the epidemiological surveillance system. It is hoped that the new revision of the national Guidelines will succeed in taking into consideration all the improvements made by the surveillance system in order to get over the difficulties observed in defining and classifying cases and their asbestos exposure.

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

PubMed

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

2015-01-01

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

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery. Caribbean Journal of Science. 44(2):175-198.

Treesearch

E.H. Helmer; T.A. Kennaway; D.H. Pedreros; M.L. Clark; H. Marcano-Vega; L.L. Tieszen; S.R. Schill; C.M.S. Carrington

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

A Crosswalk of Mineral Commodity End Uses and North American Industry Classification System (NAICS) codes

USGS Publications Warehouse

Barry, James J.; Matos, Grecia R.; Menzie, W. David

2015-09-14

The links between the end uses of mineral commodities and the NAICS codes provide an instrument for analyzing the use of mineral commodities in the economy. The crosswalk is also a guide, highlighting those industrial sectors in the economy that rely heavily on mineral commodities. The distribution of mineral commodities across the economy is dynamic and does differ from year to year. This report reflects a snapshot of the state of the economy and mineral commodities in 2010.

Applications of remote sensing in resource management in Nebraska

NASA Technical Reports Server (NTRS)

Drew, J. V.

1975-01-01

A computer-generated graphic display of land use data was developed. The level II inventory data for Sarpy County, Nebraska, was placed on magnetic tape. This data could then be displayed in a map format for comparative analysis of amount and distribution of the various categories of land use. The presentation scale can be varied and thus utilized as a direct guide for cartographic purposes during preparation for publication. In addition, the inventory and classification system was further refined.

Performance Evaluation of Distributed Systems with Unbalanced Flows: An Analysis of the INFOPLEX Data Storage Hierarchy.

DTIC Science & Technology

1984-07-01

34. - . . ’-... " " " ". ’ UNCLASSIFIED SECURITY CLASSIFICATION OF T0IS PAGE (lhen Det £ntered) REPORT DOCUMENTATION PAGE READ INSTRUCTIONS...RUMERODF PAGES 267 14 MONITORING AGENCY NAME & ADDRESS(II dillerent from Controllind Office) IS. SECURITY CLASS. (o this report) UNCLASSIFIED ISa...lower storage level. This is the basis for the mapping of the PIL3 read operation and workloads into a queueing netowrk model. S PAGE 135 REFERENCE

Risk-informed radioactive waste classification and reclassification.

PubMed

Croff, Allen G

2006-11-01

Radioactive waste classification systems have been developed to allow wastes having similar hazards to be grouped for purposes of storage, treatment, packaging, transportation, and/or disposal. As recommended in the National Council on Radiation Protection and Measurements' Report No. 139, Risk-Based Classification of Radioactive and Hazardous Chemical Wastes, a preferred classification system would be based primarily on the health risks to the public that arise from waste disposal and secondarily on other attributes such as the near-term practicalities of managing a waste, i.e., the waste classification system would be risk informed. The current U.S. radioactive waste classification system is not risk informed because key definitions--especially that of high-level waste--are based on the source of the waste instead of its inherent characteristics related to risk. A second important reason for concluding the existing U.S. radioactive waste classification system is not risk informed is there are no general principles or provisions for exempting materials from being classified as radioactive waste which would then allow management without regard to its radioactivity. This paper elaborates the current system for classifying and reclassifying radioactive wastes in the United States, analyzes the extent to which the system is risk informed and the ramifications of its not being so, and provides observations on potential future direction of efforts to address shortcomings in the U.S. radioactive waste classification system as of 2004.

Autonomous power management and distribution

NASA Technical Reports Server (NTRS)

Dolce, Jim; Kish, Jim

1990-01-01

The goal of the Autonomous Power System program is to develop and apply intelligent problem solving and control to the Space Station Freedom's electric power testbed being developed at NASA's Lewis Research Center. Objectives are to establish artificial intelligence technology paths, craft knowledge-based tools and products for power systems, and integrate knowledge-based and conventional controllers. This program represents a joint effort between the Space Station and Office of Aeronautics and Space Technology to develop and demonstrate space electric power automation technology capable of: (1) detection and classification of system operating status, (2) diagnosis of failure causes, and (3) cooperative problem solving for power scheduling and failure recovery. Program details, status, and plans will be presented.

Standardized Semantic Markup for Reference Terminologies, Thesauri and Coding Systems: Benefits for distributed E-Health Applications.

PubMed

Hoelzer, Simon; Schweiger, Ralf K; Liu, Raymond; Rudolf, Dirk; Rieger, Joerg; Dudeck, Joachim

2005-01-01

With the introduction of the ICD-10 as the standard for diagnosis, the development of an electronic representation of its complete content, inherent semantics and coding rules is necessary. Our concept refers to current efforts of the CEN/TC 251 to establish a European standard for hierarchical classification systems in healthcare. We have developed an electronic representation of the ICD-10 with the extensible Markup Language (XML) that facilitates the integration in current information systems or coding software taking into account different languages and versions. In this context, XML offers a complete framework of related technologies and standard tools for processing that helps to develop interoperable applications.

Multidimensional classification of magma types for altered igneous rocks and application to their tectonomagmatic discrimination and igneous provenance of siliciclastic sediments

NASA Astrophysics Data System (ADS)

Verma, Surendra P.; Rivera-Gómez, M. Abdelaly; Díaz-González, Lorena; Pandarinath, Kailasa; Amezcua-Valdez, Alejandra; Rosales-Rivera, Mauricio; Verma, Sanjeet K.; Quiroz-Ruiz, Alfredo; Armstrong-Altrin, John S.

2017-05-01

A new multidimensional scheme consistent with the International Union of Geological Sciences (IUGS) is proposed for the classification of igneous rocks in terms of four magma types: ultrabasic, basic, intermediate, and acid. Our procedure is based on an extensive database of major element composition of a total of 33,868 relatively fresh rock samples having a multinormal distribution (initial database with 37,215 samples). Multinormally distributed database in terms of log-ratios of samples was ascertained by a new computer program DOMuDaF, in which the discordancy test was applied at the 99.9% confidence level. Isometric log-ratio (ilr) transformation was used to provide overall percent correct classification of 88.7%, 75.8%, 88.0%, and 80.9% for ultrabasic, basic, intermediate, and acid rocks, respectively. Given the known mathematical and uncertainty propagation properties, this transformation could be adopted for routine applications. The incorrect classification was mainly for the "neighbour" magma types, e.g., basic for ultrabasic and vice versa. Some of these misclassifications do not have any effect on multidimensional tectonic discrimination. For an efficient application of this multidimensional scheme, a new computer program MagClaMSys_ilr (MagClaMSys-Magma Classification Major-element based System) was written, which is available for on-line processing on http://tlaloc.ier.unam.mx/index.html. This classification scheme was tested from newly compiled data for relatively fresh Neogene igneous rocks and was found to be consistent with the conventional IUGS procedure. The new scheme was successfully applied to inter-laboratory data for three geochemical reference materials (basalts JB-1 and JB-1a, and andesite JA-3) from Japan and showed that the inferred magma types are consistent with the rock name (basic for basalts JB-1 and JB-1a and intermediate for andesite JA-3). The scheme was also successfully applied to five case studies of older Archaean to Mesozoic igneous rocks. Similar or more reliable results were obtained from existing tectonomagmatic discrimination diagrams when used in conjunction with the new computer program as compared to the IUGS scheme. The application to three case studies of igneous provenance of sedimentary rocks was demonstrated as a novel approach. Finally, we show that the new scheme is more robust for post-emplacement compositional changes than the conventional IUGS procedure.

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Programs 219.303 Determining North American Industry Classification System (NAICS) codes and size standards...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 3 2012-10-01 2012-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Programs 219.303 Determining North American Industry Classification System (NAICS) codes and size standards...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 3 2014-10-01 2014-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Determining North American Industry Classification System (NAICS) codes and size standards. Contracting...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 3 2013-10-01 2013-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Determining North American Industry Classification System (NAICS) codes and size standards. Contracting...

Reduze - Feynman integral reduction in C++

NASA Astrophysics Data System (ADS)

Studerus, C.

2010-07-01

Reduze is a computer program for reducing Feynman integrals to master integrals employing a Laporta algorithm. The program is written in C++ and uses classes provided by the GiNaC library to perform the simplifications of the algebraic prefactors in the system of equations. Reduze offers the possibility to run reductions in parallel. Program summaryProgram title:Reduze Catalogue identifier: AEGE_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGE_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions:: yes No. of lines in distributed program, including test data, etc.: 55 433 No. of bytes in distributed program, including test data, etc.: 554 866 Distribution format: tar.gz Programming language: C++ Computer: All Operating system: Unix/Linux Number of processors used: The number of processors is problem dependent. More than one possible but not arbitrary many. RAM: Depends on the complexity of the system. Classification: 4.4, 5 External routines: CLN ( http://www.ginac.de/CLN/), GiNaC ( http://www.ginac.de/) Nature of problem: Solving large systems of linear equations with Feynman integrals as unknowns and rational polynomials as prefactors. Solution method: Using a Gauss/Laporta algorithm to solve the system of equations. Restrictions: Limitations depend on the complexity of the system (number of equations, number of kinematic invariants). Running time: Depends on the complexity of the system.

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2012 CFR

2012-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2013 CFR

2013-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2010 CFR

2010-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2014 CFR

2014-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2011 CFR

2011-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

Use of Deo's classification system on rock : final report.

DOT National Transportation Integrated Search

1983-01-01

A shale from a construction site on Route 23 in Wise County, Virginia, was classified using Deo's classification system, and the usefulness of the classification system was evaluated. In addition, rock that had previously been used in the development...

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

PubMed

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

2017-04-01

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

Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests

NASA Astrophysics Data System (ADS)

Wilschut, L. I.; Addink, E. A.; Heesterbeek, J. A. P.; Dubyanskiy, V. M.; Davis, S. A.; Laudisoit, A.; Begon, M.; Burdelov, L. A.; Atshabar, B. B.; de Jong, S. M.

2013-08-01

Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague.

Stellar Classification Online - Public Exploration

NASA Astrophysics Data System (ADS)

Castelaz, Michael W.; Bedell, W.; Barker, T.; Cline, J.; Owen, L.

2009-01-01

The Michigan Objective Prism Blue Survey (e.g. Sowell et al 2007, AJ, 134, 1089) photographic plates located in the Astronomical Photographic Data Archive at the Pisgah Astronomical Research Institute hold hundreds of thousands of stellar spectra, many of which have not been classified before. The public is invited to participate in a distributed computing online environment to classify the stars on the objective prism plates. The online environment is called Stellar Classification Online - Public Exploration (SCOPE). Through a website, SCOPE participants are given a tutorial on stellar spectra and their classification, and given the chance to practice their skills at classification. After practice, participants register, login, and select stars for classification from scans of the objective prism plates. Their classifications are recorded in a database where the accumulation of classifications of the same star by many users will be statistically analyzed. The project includes stars with known spectral types to help test the reliability of classifications. The SCOPE webpage and the use of results will be described.

Mapping regional distribution of a single tree species: Whitebark pine in the Greater Yellowstone Ecosystem

USGS Publications Warehouse

Landenburger, L.; Lawrence, R.L.; Podruzny, S.; Schwartz, C.C.

2008-01-01

Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data.

Reflective random indexing for semi-automatic indexing of the biomedical literature.

PubMed

Vasuki, Vidya; Cohen, Trevor

2010-10-01

The rapid growth of biomedical literature is evident in the increasing size of the MEDLINE research database. Medical Subject Headings (MeSH), a controlled set of keywords, are used to index all the citations contained in the database to facilitate search and retrieval. This volume of citations calls for efficient tools to assist indexers at the US National Library of Medicine (NLM). Currently, the Medical Text Indexer (MTI) system provides assistance by recommending MeSH terms based on the title and abstract of an article using a combination of distributional and vocabulary-based methods. In this paper, we evaluate a novel approach toward indexer assistance by using nearest neighbor classification in combination with Reflective Random Indexing (RRI), a scalable alternative to the established methods of distributional semantics. On a test set provided by the NLM, our approach significantly outperforms the MTI system, suggesting that the RRI approach would make a useful addition to the current methodologies.

Systemic classification for a new diagnostic approach to acute abdominal pain in children.

PubMed

Kim, Ji Hoi; Kang, Hyun Sik; Han, Kyung Hee; Kim, Seung Hyo; Shin, Kyung-Sue; Lee, Mu Suk; Jeong, In Ho; Kim, Young Sil; Kang, Ki-Soo

2014-12-01

With previous methods based on only age and location, there are many difficulties in identifying the etiology of acute abdominal pain in children. We sought to develop a new systematic classification of acute abdominal pain and to give some helps to physicians encountering difficulties in diagnoses. From March 2005 to May 2010, clinical data were collected retrospectively from 442 children hospitalized due to acute abdominal pain with no apparent underlying disease. According to the final diagnoses, diseases that caused acute abdominal pain were classified into nine groups. The nine groups were group I "catastrophic surgical abdomen" (7 patients, 1.6%), group II "acute appendicitis and mesenteric lymphadenitis" (56 patients, 12.7%), group III "intestinal obstruction" (57 patients, 12.9%), group IV "viral and bacterial acute gastroenteritis" (90 patients, 20.4%), group V "peptic ulcer and gastroduodenitis" (66 patients, 14.9%), group VI "hepatobiliary and pancreatic disease" (14 patients, 3.2%), group VII "febrile viral illness and extraintestinal infection" (69 patients, 15.6%), group VIII "functional gastrointestinal disorder (acute manifestation)" (20 patients, 4.5%), and group IX "unclassified acute abdominal pain" (63 patients, 14.3%). Four patients were enrolled in two disease groups each. Patients were distributed unevenly across the nine groups of acute abdominal pain. In particular, the "unclassified abdominal pain" only group was not uncommon. Considering a systemic classification for acute abdominal pain may be helpful in the diagnostic approach in children.

Multivariate pattern analysis of fMRI data reveals deficits in distributed representations in schizophrenia

PubMed Central

Yoon, Jong H.; Tamir, Diana; Minzenberg, Michael J.; Ragland, J. Daniel; Ursu, Stefan; Carter, Cameron S.

2009-01-01

Background Multivariate pattern analysis is an alternative method of analyzing fMRI data, which is capable of decoding distributed neural representations. We applied this method to test the hypothesis of the impairment in distributed representations in schizophrenia. We also compared the results of this method with traditional GLM-based univariate analysis. Methods 19 schizophrenia and 15 control subjects viewed two runs of stimuli--exemplars of faces, scenes, objects, and scrambled images. To verify engagement with stimuli, subjects completed a 1-back matching task. A multi-voxel pattern classifier was trained to identify category-specific activity patterns on one run of fMRI data. Classification testing was conducted on the remaining run. Correlation of voxel-wise activity across runs evaluated variance over time in activity patterns. Results Patients performed the task less accurately. This group difference was reflected in the pattern analysis results with diminished classification accuracy in patients compared to controls, 59% and 72% respectively. In contrast, there was no group difference in GLM-based univariate measures. In both groups, classification accuracy was significantly correlated with behavioral measures. Both groups showed highly significant correlation between inter-run correlations and classification accuracy. Conclusions Distributed representations of visual objects are impaired in schizophrenia. This impairment is correlated with diminished task performance, suggesting that decreased integrity of cortical activity patterns is reflected in impaired behavior. Comparisons with univariate results suggest greater sensitivity of pattern analysis in detecting group differences in neural activity and reduced likelihood of non-specific factors driving these results. PMID:18822407

A domains-based taxonomy of supported accommodation for people with severe and persistent mental illness.

PubMed

Siskind, Dan; Harris, Meredith; Pirkis, Jane; Whiteford, Harvey

2013-06-01

A lack of definitional clarity in supported accommodation and the absence of a widely accepted system for classifying supported accommodation models creates barriers to service planning and evaluation. We undertook a systematic review of existing supported accommodation classification systems. Using a structured system for qualitative data analysis, we reviewed the stratification features in these classification systems, identified the key elements of supported accommodation and arranged them into domains and dimensions to create a new taxonomy. The existing classification systems were mapped onto the new taxonomy to verify the domains and dimensions. Existing classification systems used either a service-level characteristic or programmatic approach. We proposed a taxonomy based around four domains: duration of tenure; patient characteristics; housing characteristics; and service characteristics. All of the domains in the taxonomy were drawn from the existing classification structures; however, none of the existing classification structures covered all of the domains in the taxonomy. Existing classification systems are regionally based, limited in scope and lack flexibility. A domains-based taxonomy can allow more accurate description of supported accommodation services, aid in identifying the service elements likely to improve outcomes for specific patient populations, and assist in service planning.

A Model Assessment and Classification System for Men and Women in Correctional Institutions.

ERIC Educational Resources Information Center

Hellervik, Lowell W.; And Others

The report describes a manpower assessment and classification system for criminal offenders directed towards making practical training and job classification decisions. The model is not concerned with custody classifications except as they affect occupational/training possibilities. The model combines traditional procedures of vocational…

A Neural Network Aero Design System for Advanced Turbo-Engines

NASA Technical Reports Server (NTRS)

Sanz, Jose M.

1999-01-01

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

Alternative temporal classification of long Gamma Ray Bursts

NASA Astrophysics Data System (ADS)

Alejandro Vasquez, Nicolas; Baquero, Andres; Andrade, David

2015-08-01

In order to increase the understanding on Gamma Ray Bursts, many attempts of classification have been proposed. Starting with the canonical classification into long and short GRBs, alternative classifications taking into account the cosmological origin of GRBs have been analyzed. In the present work we propose an alternative classification based on two temporal estimators, the Auto Correlation Function (ACF) of the light curves and the emission time which considered the time where the bursts engine is active. The time estimators chosen reflects the internal evolution of the GRB and the internal structure. Using a sample of 61 bright GRBs detected by SWIFT satellite with known redshift, we proposed a bimodal distribution of long bursts. The two types of bursts have different internal structure suggesting different progenitors.

BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the NSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David

2000-01-01

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification. A standard supervised maximum likelihood classification approach was used to produce this classification. The data are provided in a binary image format file. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Galaxy Zoo 1: data release of morphological classifications for nearly 900 000 galaxies

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

Linott, C.; Slosar, A.; Lintott, C.

Morphology is a powerful indicator of a galaxy's dynamical and merger history. It is strongly correlated with many physical parameters, including mass, star formation history and the distribution of mass. The Galaxy Zoo project collected simple morphological classifications of nearly 900,000 galaxies drawn from the Sloan Digital Sky Survey, contributed by hundreds of thousands of volunteers. This large number of classifications allows us to exclude classifier error, and measure the influence of subtle biases inherent in morphological classification. This paper presents the data collected by the project, alongside measures of classification accuracy and bias. The data are now publicly availablemore » and full catalogues can be downloaded in electronic format from http://data.galaxyzoo.org.« less

A Visual Basic program to plot sediment grain-size data on ternary diagrams

USGS Publications Warehouse

Poppe, L.J.; Eliason, A.H.

2008-01-01

Sedimentologic datasets are typically large and compiled into tables or databases, but pure numerical information can be difficult to understand and interpret. Thus, scientists commonly use graphical representations to reduce complexities, recognize trends and patterns in the data, and develop hypotheses. Of the graphical techniques, one of the most common methods used by sedimentologists is to plot the basic gravel, sand, silt, and clay percentages on equilateral triangular diagrams. This means of presenting data is simple and facilitates rapid classification of sediments and comparison of samples.The original classification scheme developed by Shepard (1954) used a single ternary diagram with sand, silt, and clay in the corners and 10 categories to graphically show the relative proportions among these three grades within a sample. This scheme, however, did not allow for sediments with significant amounts of gravel. Therefore, Shepard's classification scheme was later modified by the addition of a second ternary diagram with two categories to account for gravel and gravelly sediment (Schlee, 1973). The system devised by Folk (1954, 1974)\\ is also based on two triangular diagrams, but it has 21 categories and uses the term mud (defined as silt plus clay). Patterns within the triangles of both systems differ, as does the emphasis placed on gravel. For example, in the system described by Shepard, gravelly sediments have more than 10% gravel; in Folk's system, slightly gravelly sediments have as little as 0.01% gravel. Folk's classification scheme stresses gravel because its concentration is a function of the highest current velocity at the time of deposition as is the maximum grain size of the detritus that is available; Shepard's classification scheme emphasizes the ratios of sand, silt, and clay because they reflect sorting and reworking (Poppe et al., 2005).The program described herein (SEDPLOT) generates verbal equivalents and ternary diagrams to characterize sediment grain-size distributions. It is written in Microsoft Visual Basic 6.0 and provides a window to facilitate program execution. The inputs for the sediment fractions are percentages of gravel, sand, silt, and clay in the Wentworth (1922) grade scale, and the program permits the user to select output in either the Shepard (1954) classification scheme, modified as described above, or the Folk (1954, 1974) scheme. Users select options primarily with mouse-click events and through interactive dialogue boxes. This program is intended as a companion to other Visual Basic software we have developed to process sediment data (Poppe et al., 2003, 2004).

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please visit http://public.tgen.org/tamu/ofs/ e-dougherty@ee.tamu.edu.

Comments on new classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus and ileosigmoid knotting: necessity and utility.

PubMed

Aksungur, N; Korkut, E

2018-05-24

We read Atamanalp classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus (SV) and ileosigmoid knotting (ISK) in Colorectal Disease [1,2]. Our comments relate to necessity and utility of these new classification systems. Classification or staging systems are generally used in malignant or premalignant pathologies such as colorectal cancers [3] or polyps [4]. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Marine habitat mapping of the Milford Haven Waterway, Wales, UK: Comparison of facies mapping and EUNIS classification for monitoring sediment habitats in an industrialized estuary

NASA Astrophysics Data System (ADS)

Carey, Drew A.; Hayn, Melanie; Germano, Joseph D.; Little, David I.; Bullimore, Blaise

2015-06-01

A detailed map and dataset of sedimentary habitats of the Milford Haven Waterway (MHW) was compiled for the Milford Haven Waterway Environmental Surveillance Group (MHWESG) from seafloor images collected in May, 2012 using sediment-profile and plan-view imaging (SPI/PV) survey techniques. This is the most comprehensive synoptic assessment of sediment distribution and benthic habitat composition available for the MHW, with 559 stations covering over 40 km2 of subtidal habitats. In the context of the MHW, an interpretative framework was developed that classified each station within a 'facies' that included information on the location within the waterway and inferred sedimentary and biological processes. The facies approach provides critical information on landscape-scale habitats including relative location and inferred sediment transport processes and can be used to direct future monitoring activities within the MHW and to predict areas of greatest potential risk from contaminant transport. Intertidal sediment 'facies' maps have been compiled in the past for MHW; this approach was expanded to map the subtidal portions of the waterway. Because sediment facies can be projected over larger areas than individual samples (due to assumptions based on physiography, or landforms) they represent an observational model of the distribution of sediments in an estuary. This model can be tested over time and space through comparison with additional past or future sample results. This approach provides a means to evaluate stability or change in the physical and biological conditions of the estuarine system. Initial comparison with past results for intertidal facies mapping and grain size analysis from grab samples showed remarkable stability over time for the MHW. The results of the SPI/PV mapping effort were cross-walked to the European Nature Information System (EUNIS) classification to provide a comparison of locally derived habitat mapping with European-standard habitat mapping. Cross-walk was conducted by assigning each facies (or group of facies) to a EUNIS habitat (Levels 3 or 5) and compiling maps comparing facies distribution with EUNIS habitat distribution. The facies approach provides critical information on landscape-scale habitats including relative location and inferred sediment transport processes. The SPI/PV approach cannot consistently identify key species contained within the EUNIS Level 5 Habitats. For regional planning and monitoring efforts, a combination of EUNIS classification and facies description provides the greatest flexibility for management of dynamic soft-bottom habitats in coastal estuaries. The combined approach can be used to generate and test hypotheses of linkages between biological characteristics (EUNIS) and physical characteristics (facies). This approach is practical if a robust cross-walk methodology is developed to utilize both classification approaches. SPI/PV technology can be an effective rapid ground truth method for refining marine habitat maps based on predictive models.

Critical evaluation of the PALM-COEIN classification system among women with abnormal uterine bleeding in low-resource settings.

PubMed

Shubham, Divya; Kawthalkar, Anjali S

2018-05-01

To assess the feasibility of the PALM-COEIN system for the classification of abnormal uterine bleeding (AUB) in low-resource settings and to suggest modifications. A prospective study was conducted among women with AUB who were admitted to the gynecology ward of a tertiary care hospital and research center in central India between November 2014 and October 2016. All patients were managed as per department protocols. The causes of AUB were classified before treatment using the PALM-COEIN system (classification I) and on the basis of the histopathology reports of the hysterectomy specimens (classification II); the results were compared using classification II as the gold standard. The study included 200 women with AUB; hysterectomy was performed in 174 women. Preoperative classification of AUB per the PALM-COEIN system was correct in 130 (65.0%) women. Adenomyosis (evaluated by transvaginal ultrasonography) and endometrial hyperplasia (evaluated by endometrial curettage) were underdiagnosed. The PALM-COEIN classification system helps in deciding the best treatment modality for women with AUB on a case-by-case basis. The incorporation of suggested modifications will further strengthen its utility as a pretreatment classification system in low-resource settings. © 2017 International Federation of Gynecology and Obstetrics.

Attachment between Infants and Mothers in China: Strange Situation Procedure Findings to Date and a New Sample

ERIC Educational Resources Information Center

Archer, Marc; Steele, Miriam; Lan, Jijun; Jin, Xiaochun; Herreros, Francisca; Steele, Howard

2015-01-01

The first distribution of Chinese infant-mother (n = 61) attachment classifications categorised by trained and reliability-tested coders is reported with statistical comparisons to US norms and previous Chinese distributions. Three-way distribution was 15% insecure-avoidant, 62% secure, 13% insecure-resistant, and 4-way distribution was 13%…

Semiparametric Bayesian classification with longitudinal markers

PubMed Central

De la Cruz-Mesía, Rolando; Quintana, Fernando A.; Müller, Peter

2013-01-01

Summary We analyse data from a study involving 173 pregnant women. The data are observed values of the β human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six longitudinal responses for each woman. The main objective in this study is to predict normal versus abnormal pregnancy outcomes from data that are available at the early stages of pregnancy. We achieve the desired classification with a semiparametric hierarchical model. Specifically, we consider a Dirichlet process mixture prior for the distribution of the random effects in each group. The unknown random-effects distributions are allowed to vary across groups but are made dependent by using a design vector to select different features of a single underlying random probability measure. The resulting model is an extension of the dependent Dirichlet process model, with an additional probability model for group classification. The model is shown to perform better than an alternative model which is based on independent Dirichlet processes for the groups. Relevant posterior distributions are summarized by using Markov chain Monte Carlo methods. PMID:24368871

Discriminative Bayesian Dictionary Learning for Classification.

PubMed

Akhtar, Naveed; Shafait, Faisal; Mian, Ajmal

2016-12-01

We propose a Bayesian approach to learn discriminative dictionaries for sparse representation of data. The proposed approach infers probability distributions over the atoms of a discriminative dictionary using a finite approximation of Beta Process. It also computes sets of Bernoulli distributions that associate class labels to the learned dictionary atoms. This association signifies the selection probabilities of the dictionary atoms in the expansion of class-specific data. Furthermore, the non-parametric character of the proposed approach allows it to infer the correct size of the dictionary. We exploit the aforementioned Bernoulli distributions in separately learning a linear classifier. The classifier uses the same hierarchical Bayesian model as the dictionary, which we present along the analytical inference solution for Gibbs sampling. For classification, a test instance is first sparsely encoded over the learned dictionary and the codes are fed to the classifier. We performed experiments for face and action recognition; and object and scene-category classification using five public datasets and compared the results with state-of-the-art discriminative sparse representation approaches. Experiments show that the proposed Bayesian approach consistently outperforms the existing approaches.

48 CFR 19.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 19.303 Section 19.303 Federal Acquisition... Classification System (NAICS) codes and size standards. (a) The contracting officer shall determine the...

A new tree classification system for southern hardwoods

Treesearch

James S. Meadows; Daniel A. Jr. Skojac

2008-01-01

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

Incorporating prior knowledge induced from stochastic differential equations in the classification of stochastic observations.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2016-12-01

In classification, prior knowledge is incorporated in a Bayesian framework by assuming that the feature-label distribution belongs to an uncertainty class of feature-label distributions governed by a prior distribution. A posterior distribution is then derived from the prior and the sample data. An optimal Bayesian classifier (OBC) minimizes the expected misclassification error relative to the posterior distribution. From an application perspective, prior construction is critical. The prior distribution is formed by mapping a set of mathematical relations among the features and labels, the prior knowledge, into a distribution governing the probability mass across the uncertainty class. In this paper, we consider prior knowledge in the form of stochastic differential equations (SDEs). We consider a vector SDE in integral form involving a drift vector and dispersion matrix. Having constructed the prior, we develop the optimal Bayesian classifier between two models and examine, via synthetic experiments, the effects of uncertainty in the drift vector and dispersion matrix. We apply the theory to a set of SDEs for the purpose of differentiating the evolutionary history between two species.

Vitamin D3 Analogues with Low Vitamin D Receptor Binding Affinity Regulate Chondrocyte Proliferation, Proteoglycan Synthesis, and Protein Kinase C Activity

DTIC Science & Technology

1997-07-11

REPORT DOCUMENTATION PAGE Form ApprovedOMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour...DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 words) 14. SUBJECT TERMS 15. NUMBER OF PAGES 50 16. PRICE CODE 17. SECURITY CLASSIFICATION 18. SECURITY...CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF THIS PAGE OF ABSTRACT Standard Form 298(Rev. 2-89) (EG) Prescribed byANSI

A Robust Geometric Model for Argument Classification

NASA Astrophysics Data System (ADS)

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

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

Cross-mapping the ICNP with NANDA, HHCC, Omaha System and NIC for unified nursing language system development. International Classification for Nursing Practice. International Council of Nurses. North American Nursing Diagnosis Association. Home Health Care Classification. Nursing Interventions Classification.

PubMed

Hyun, S; Park, H A

2002-06-01

Nursing language plays an important role in describing and defining nursing phenomena and nursing actions. There are numerous vocabularies describing nursing diagnoses, interventions and outcomes in nursing. However, the lack of a standardized unified nursing language is considered a problem for further development of the discipline of nursing. In an effort to unify the nursing languages, the International Council of Nurses (ICN) has proposed the International Classification for Nursing Practice (ICNP) as a unified nursing language system. The purpose of this study was to evaluate the inclusiveness and expressiveness of the ICNP terms by cross-mapping them with the existing nursing terminologies, specifically the North American Nursing Diagnosis Association (NANDA) taxonomy I, the Omaha System, the Home Health Care Classification (HHCC) and the Nursing Interventions Classification (NIC). Nine hundred and seventy-four terms from these four classifications were cross-mapped with the ICNP terms. This was performed in accordance with the Guidelines for Composing a Nursing Diagnosis and Guidelines for Composing a Nursing Intervention, which were suggested by the ICNP development team. An expert group verified the results. The ICNP Phenomena Classification described 87.5% of the NANDA diagnoses, 89.7% of the HHCC diagnoses and 72.7% of the Omaha System problem classification scheme. The ICNP Action Classification described 79.4% of the NIC interventions, 80.6% of the HHCC interventions and 71.4% of the Omaha System intervention scheme. The results of this study suggest that the ICNP has a sound starting structure for a unified nursing language system and can be used to describe most of the existing terminologies. Recommendations for the addition of terms to the ICNP are provided.

Bug Distribution and Statistical Pattern Classification.

ERIC Educational Resources Information Center

Tatsuoka, Kikumi K.; Tatsuoka, Maurice M.

1987-01-01

The rule space model permits measurement of cognitive skill acquisition and error diagnosis. Further discussion introduces Bayesian hypothesis testing and bug distribution. An illustration involves an artificial intelligence approach to testing fractions and arithmetic. (Author/GDC)

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

PubMed

Fainsinger, Robin L; Nekolaichuk, Cheryl L

2008-06-01

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

5 CFR 9901.224 - Appeal to OPM for review of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901...

5 CFR 9901.224 - Appeal to OPM for review of classification decisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901...

Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine.

PubMed

Deschamps, Kevin; Matricali, Giovanni Arnoldo; Desmet, Dirk; Roosen, Philip; Keijsers, Noel; Nobels, Frank; Bruyninckx, Herman; Staes, Filip

2016-09-01

The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making. Copyright © 2016 Elsevier B.V. All rights reserved.

Classification System and Information Services in the Library of SAO RAS

NASA Astrophysics Data System (ADS)

Shvedova, G. S.

The classification system used at SAO RAS is described. It includes both special determinants from UDC (Universal Decimal Classification) and newer tables with astronomical terms from the Library-Bibliographical Classification (LBC). The classification tables are continually modified, and new astronomical terms are introduced. At the present time the information services of the scientists is fulfilled with the help of the Abstract Journal Astronomy, Astronomy and Astrophysics Abstracts, catalogues and card indexes of the library. Based on our classification system and The Astronomy Thesaurus completed by R.M. Shobbrook and R.R. Shobbrook the development of a database for the library has been started, which allows prompt service of the observatory's staff members.

Analysis of classifiers performance for classification of potential microcalcification

NASA Astrophysics Data System (ADS)

M. N., Arun K.; Sheshadri, H. S.

2013-07-01

Breast cancer is a significant public health problem in the world. According to the literature early detection improve breast cancer prognosis. Mammography is a screening tool used for early detection of breast cancer. About 10-30% cases are missed during the routine check as it is difficult for the radiologists to make accurate analysis due to large amount of data. The Microcalcifications (MCs) are considered to be important signs of breast cancer. It has been reported in literature that 30% - 50% of breast cancer detected radio graphically show MCs on mammograms. Histologic examinations report 62% to 79% of breast carcinomas reveals MCs. MC are tiny, vary in size, shape, and distribution, and MC may be closely connected to surrounding tissues. There is a major challenge using the traditional classifiers in the classification of individual potential MCs as the processing of mammograms in appropriate stage generates data sets with an unequal amount of information for both classes (i.e., MC, and Not-MC). Most of the existing state-of-the-art classification approaches are well developed by assuming the underlying training set is evenly distributed. However, they are faced with a severe bias problem when the training set is highly imbalanced in distribution. This paper addresses this issue by using classifiers which handle the imbalanced data sets. In this paper, we also compare the performance of classifiers which are used in the classification of potential MC.

Research on Automatic Classification, Indexing and Extracting. Annual Progress Report.

ERIC Educational Resources Information Center

Baker, F.T.; And Others

In order to contribute to the success of several studies for automatic classification, indexing and extracting currently in progress, as well as to further the theoretical and practical understanding of textual item distributions, the development of a frequency program capable of supplying these types of information was undertaken. The program…

26 CFR 1.962-3 - Treatment of actual distributions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... classified under § 1.959-3 and this section for purposes of section 962(d) as follows: Classification of... purposes of a section 959(c) amount and year classification under paragraph (b) of § 1.959-3, a... Revenue Code. The application of this subparagraph may be illustrated by the following example: Example...

26 CFR 1.962-3 - Treatment of actual distributions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... classified under § 1.959-3 and this section for purposes of section 962(d) as follows: Classification of... purposes of a section 959(c) amount and year classification under paragraph (b) of § 1.959-3, a... Revenue Code. The application of this subparagraph may be illustrated by the following example: Example...

Proximal humeral fracture classification systems revisited.

PubMed

Majed, Addie; Macleod, Iain; Bull, Anthony M J; Zyto, Karol; Resch, Herbert; Hertel, Ralph; Reilly, Peter; Emery, Roger J H

2011-10-01

This study evaluated several classification systems and expert surgeons' anatomic understanding of these complex injuries based on a consecutive series of patients. We hypothesized that current proximal humeral fracture classification systems, regardless of imaging methods, are not sufficiently reliable to aid clinical management of these injuries. Complex fractures in 96 consecutive patients were investigated by generation of rapid sequence prototyping models from computed tomography Digital Imaging and Communications in Medicine (DICOM) imaging data. Four independent senior observers were asked to classify each model using 4 classification systems: Neer, AO, Codman-Hertel, and a prototype classification system by Resch. Interobserver and intraobserver κ coefficient values were calculated for the overall classification system and for selected classification items. The κ coefficient values for the interobserver reliability were 0.33 for Neer, 0.11 for AO, 0.44 for Codman-Hertel, and 0.15 for Resch. Interobserver reliability κ coefficient values were 0.32 for the number of fragments and 0.30 for the anatomic segment involved using the Neer system, 0.30 for the AO type (A, B, C), and 0.53, 0.48, and 0.08 for the Resch impaction/distraction, varus/valgus and flexion/extension subgroups, respectively. Three-part fractures showed low reliability for the Neer and AO systems. Currently available evidence suggests fracture classifications in use have poor intra- and inter-observer reliability despite the modality of imaging used thus making treating these injuries difficult as weak as affecting scientific research as well. This study was undertaken to evaluate the reliability of several systems using rapid sequence prototype models. Overall interobserver κ values represented slight to moderate agreement. The most reliable interobserver scores were found with the Codman-Hertel classification, followed by elements of Resch's trial system. The AO system had the lowest values. The higher interobserver reliability values for the Codman-Hertel system showed that is the only comprehensive fracture description studied, whereas the novel classification by Resch showed clear definition in respect to varus/valgus and impaction/distraction angulation. Copyright © 2011 Journal of Shoulder and Elbow Surgery Board of Trustees. All rights reserved.

Toward automated classification of consumers' cancer-related questions with a new taxonomy of expected answer types.

PubMed

McRoy, Susan; Jones, Sean; Kurmally, Adam

2016-09-01

This article examines methods for automated question classification applied to cancer-related questions that people have asked on the web. This work is part of a broader effort to provide automated question answering for health education. We created a new corpus of consumer-health questions related to cancer and a new taxonomy for those questions. We then compared the effectiveness of different statistical methods for developing classifiers, including weighted classification and resampling. Basic methods for building classifiers were limited by the high variability in the natural distribution of questions and typical refinement approaches of feature selection and merging categories achieved only small improvements to classifier accuracy. Best performance was achieved using weighted classification and resampling methods, the latter yielding an accuracy of F1 = 0.963. Thus, it would appear that statistical classifiers can be trained on natural data, but only if natural distributions of classes are smoothed. Such classifiers would be useful for automated question answering, for enriching web-based content, or assisting clinical professionals to answer questions. © The Author(s) 2015.

Gesteme-free context-aware adaptation of robot behavior in human-robot cooperation.

PubMed

Nessi, Federico; Beretta, Elisa; Gatti, Cecilia; Ferrigno, Giancarlo; De Momi, Elena

2016-11-01

Cooperative robotics is receiving greater acceptance because the typical advantages provided by manipulators are combined with an intuitive usage. In particular, hands-on robotics may benefit from the adaptation of the assistant behavior with respect to the activity currently performed by the user. A fast and reliable classification of human activities is required, as well as strategies to smoothly modify the control of the manipulator. In this scenario, gesteme-based motion classification is inadequate because it needs the observation of a wide signal percentage and the definition of a rich vocabulary. In this work, a system able to recognize the user's current activity without a vocabulary of gestemes, and to accordingly adapt the manipulator's dynamic behavior is presented. An underlying stochastic model fits variations in the user's guidance forces and the resulting trajectories of the manipulator's end-effector with a set of Gaussian distribution. The high-level switching between these distributions is captured with hidden Markov models. The dynamic of the KUKA light-weight robot, a torque-controlled manipulator, is modified with respect to the classified activity using sigmoidal-shaped functions. The presented system is validated over a pool of 12 näive users in a scenario that addresses surgical targeting tasks on soft tissue. The robot's assistance is adapted in order to obtain a stiff behavior during activities that require critical accuracy constraint, and higher compliance during wide movements. Both the ability to provide the correct classification at each moment (sample accuracy) and the capability of correctly identify the correct sequence of activity (sequence accuracy) were evaluated. The proposed classifier is fast and accurate in all the experiments conducted (80% sample accuracy after the observation of ∼450ms of signal). Moreover, the ability of recognize the correct sequence of activities, without unwanted transitions is guaranteed (sequence accuracy ∼90% when computed far away from user desired transitions). Finally, the proposed activity-based adaptation of the robot's dynamic does not lead to a not smooth behavior (high smoothness, i.e. normalized jerk score <0.01). The provided system is able to dynamic assist the operator during cooperation in the presented scenario. Copyright © 2016 Elsevier B.V. All rights reserved.

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 3 2011-10-01 2011-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 3 2010-10-01 2010-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 3 2014-10-01 2014-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 3 2013-10-01 2013-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

46 CFR 76.50-5 - Classification.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 3 2012-10-01 2012-10-01 false Classification. 76.50-5 Section 76.50-5 Shipping COAST... Classification. (a) Hand portable fire extinguishers and semiportable fire extinguishing systems shall be... extinguishing systems are set forth in table 76.50-5(c). Table 76.50-5(c) Classification Type Size Soda acid and...

On the classification of normally distributed neurons: an application to human dentate nucleus.

PubMed

Ristanović, Dušan; Milošević, Nebojša T; Marić, Dušica L

2011-03-01

One of the major goals in cellular neurobiology is the meaningful cell classification. However, in cell classification there are many unresolved issues that need to be addressed. Neuronal classification usually starts with grouping cells into classes according to their main morphological features. If one tries to test quantitatively such a qualitative classification, a considerable overlap in cell types often appears. There is little published information on it. In order to remove the above-mentioned shortcoming, we undertook the present study with the aim to offer a novel method for solving the class overlapping problem. To illustrate our method, we analyzed a sample of 124 neurons from adult human dentate nucleus. Among them we qualitatively selected 55 neurons with small dendritic fields (the small neurons), and 69 asymmetrical neurons with large dendritic fields (the large neurons). We showed that these two samples are normally and independently distributed. By measuring the neuronal soma areas of both samples, we observed that the corresponding normal curves cut each other. We proved that the abscissa of the point of intersection of the curves could represent the boundary between the two adjacent overlapping neuronal classes, since the error done by such division is minimal. Statistical evaluation of the division was also performed.

Public participation GIS: a method for identifying ecosystems services

USGS Publications Warehouse

Brown, Greg; Montag, Jessica; Lyon, Katie

2012-01-01

This study evaluated the use of an Internet-based public participation geographic information system (PPGIS) to identify ecosystem services in Grand County, Colorado. Specific research objectives were to examine the distribution of ecosystem services, identify the characteristics of participants in the study, explore potential relationships between ecosystem services and land use and land cover (LULC) classifications, and assess the methodological strengths and weakness of the PPGIS approach for identifying ecosystem services. Key findings include: (1) Cultural ecosystem service opportunities were easiest to identify while supporting and regulatory services most challenging, (2) participants were highly educated, knowledgeable about nature and science, and have a strong connection to the outdoors, (3) some LULC classifications were logically and spatially associated with ecosystem services, and (4) despite limitations, the PPGIS method demonstrates potential for identifying ecosystem services to augment expert judgment and to inform public or environmental policy decisions regarding land use trade-offs.

43 CFR 2461.1 - Proposed classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

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

43 CFR 2461.4 - Changing classifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

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